AI agents are the ultimate insiders. We grant them permission to read emails, query databases, and trigger API calls. They don’t just retrieve information, they take action. 

Agents offer incredible potential for increased productivity and better customer experiences, but they also come with new security concerns. In our new State of AI infrastructure report, 79% of tech leaders cite security, governance, or operations as their most significant challenge to scaling inference.

While there’s still a crucial role for traditional security tools, the threat model has fundamentally changed. Autonomous workflows have redefined enterprise risk, so it's crucial that we give agents the access they need without compromising security.

Technology leaders are under mounting pressure to modernize infrastructure, control multi-cloud operational spend, and build data foundations for generative AI. However, the discovery required for that level of transformation can entail weeks of manual spreadsheet analysis, mapping in-house infrastructure, and reconciling siloed, piecemeal cost estimates across disparate teams and sources. To help, we’re announcing AI-powered Quick Assessments in Migration Center, which delivers near-instant total cost of ownership (TCO) modeling and automated service mapping.

Compare this to legacy assessment processes, which can stall digital transformation initiatives before they even launch. Manual discovery can delay migration timelines by months, increase engineering overhead, and often miscalculates complex financial models. By replacing manual discovery with AI-assisted automation, IT gains instant, actionable visibility into the TCO and return on investment (ROI) for a given migration initiative. 

Now, organizations can generate comprehensive migration financial models in minutes rather than months. Teams ingest raw infrastructure data or cloud billing reports and quickly receive an optimized target bill of materials (BOM), service mapping coverage, and projected savings. Decision makers interact with an agentic assistant that explains underlying financial assumptions, recommends technical cost optimizations, and exports ready-to-share executive reports.

Inside the AI-powered Migration Center

This is made possible with AI-assisted Quick Assessments alongside enhanced Cloud Billing assessment capabilities, both integrated into the new AI-powered Migration Center.

AI-assisted Quick Assessment for on-premises workloads

Designed for enterprise customers and partners, AI-assisted Quick Assessment automates on-premises infrastructure evaluation to provide rapid financial modeling. Let’s walk through these new capabilities: 

• Instant Compute Engine TCO estimates convert VMware inventory exports (such as RVTools) or aggregated infrastructure inputs into precise Compute Engine cost targets:

• Advanced architecture modeling supports latest-generation Gen4 compute instances and high-performance Hyperdisk storage pools:

• Customizable financial controls allow teams to adjust on-premises baseline cost assumptions to match internal accounting standards:

• Context-aware agentic chat recommends tailored technical cost optimizations aligned with your specific business constraints (such as regional location or compliance needs), clearly explaining the underlying logic and financial assumptions.

• Automated Business Case and Google Sheets export generates ready-to-use reports capturing the complete recommended BOM, TCO comparison, and ROI analysis:

The path forward

Modernizing your infrastructure starts with fast and accurate data. Migration Center’s Gemini-powered features simplify cloud evaluation, empowering IT decision makers to build defensible business cases generated by machine-learning.

Try Migration Center directly in the console today, or take a free migration and modernization assessment to evaluate your workloads and accelerate your strategic cloud journey with Google Cloud.

Few professions are as exacting as the practice of law. A team reviewing a contract or building a case works inside strictly privileged information, firm-specific playbooks, and a body of law that changes constantly. The work thrives on nuanced, professional judgment — and the systems supporting it inherit real obligations: ethical walls that cannot be crossed, matter permissions that cannot be flattened, and a duty of confidentiality that does not bend for convenience.

General-purpose AI, however capable, does not meet that standard on its own. Foundational model intelligence is necessary. For legal work, it is nowhere near sufficient.

What makes the difference is the system built around the model: skills that enhance a firm's own expertise, connections into the systems where matters actually live, agents that complete work rather than return suggestions, and an open ecosystem to extend all of it — with governance running underneath all four. Each is valuable alone. Only in combination do they produce something a firm or a legal department can put into production and actually rely on.

Today we're bringing that to legal practice with Gemini Enterprise for Legal, part of our new suite of purpose-built industry solutions.

Bringing Gemini Enterprise to your legal practice

Four components of Gemini Enterprise for Legal

Developed alongside industry leaders, Gemini Enterprise for Legal provides an integrated, fully governed environment configured for rapid deployment across firms and corporate legal departments:

1. Purpose-built skills for legal work. Skills are reusable packages of instructions and context, designed by domain experts, that teach an agent to run a specialized task while enforcing your firm's playbooks, citation rules, and house style. They cover contract review and redlining, playbook creation, regulatory horizon scanning, legal research, DSAR fulfillment, and more — and they are where a firm's institutional knowledge becomes something the platform can execute rather than something a partner has to re-explain.

2. Connections to trusted systems and data. Secure MCP connectors link agents to the document management systems, case repositories, research services, and industry applications legal teams already rely on — inheriting each platform's existing user permissions and access controls rather than working around them.

3. Agents that act within the data. Skills and connections come together in agents that carry work through: pre-built agents from Google and leading legal software providers deploy out of the box. Specialized agents handle legal and policy research, regulatory screening, and contract drafting — bringing deep legal expertise onto a platform with centralized governance.

4. An open partner ecosystem. Every firm and legal department practices differently. Partnerships with global systems integrators and legal-tech specialists — Accenture, Deloitte, Devoteam, Factor Law, KPMG, Tribe.ai, Valtech, Zazmic, Zencore, and 66degrees — let organizations customize, integrate, and scale across complex enterprise architectures without vendor lock-in.

Running underneath: a governed control plane. A single dashboard for legal IT and risk teams that natively enforces security policies (VPC, CMEK), maintains private data isolation, and holds every output to verifiable grounding with traceable citations.

Unlocking high-value workflows with domain-specific skills

Gemini Enterprise for Legal shifts AI from passive querying to agentic execution, automating high-volume, precision-critical workflows such as:

• Proactive regulatory horizon scanning: Keeps legal and compliance teams ahead of global mandates by autonomously tracking legislative updates, court dockets, and supervisory bodies. It cross-references emerging changes against enterprise policies to flag exposure gaps and generate updated policy drafts for immediate practitioner review.

• Automating data discovery and DSAR response: Modernizes privacy workflows by compiling personal data across fragmented enterprise systems in seconds. It eliminates the manual toil of Data Subject Access Requests (DSARs), and allows for adherence to regulatory timelines while minimizing operational risk.

• Accelerating contract review and negotiation: Compresses turnaround times for inbound vendor agreements, NDAs, and complex M&A documentation by benchmarking terms against enterprise playbooks. It surfaces high-risk clauses and potential exposure, enabling attorneys to focus on strategic negotiation and high-value judgment.

• Building and updating contracting playbooks: Transforms legacy agreement archives into dynamic, actionable playbooks instantly. It automatically extracts key terms, fallback positions, and institutional knowledge to maintain portfolio-wide term consistency and lower negotiation variance across the enterprise.

• Redacting documents for motions to seal: Eliminates the manual burden of preparing court filings and redacting legal documents. It intelligently identifies sensitive terms and PII for rapid practitioner confirmation, dramatically accelerating filing timelines while safeguarding confidentiality.

• Drafting NDA documents: Elevates contract creation through structural fidelity validation that enforces firm standards and logical document hierarchies. It allows legal teams to rapidly generate and evolve non-disclosure agreements with complete formatting confidence and minimal review overhead.

Open ecosystem of connectors across the legal technology stack

Legal work is only as good as its sources, and legal data carries permissions that have to travel with it. Gemini Enterprise for Legal connects directly to core legal systems via secure MCP connectors. Crucially, access is bound by existing role-based access controls, document-level permissions, and trusted data controls inherited from document management and ediscovery systems.

Productivity and collaboration:

• Google Workspace: Connects seamlessly with Google Docs, Gmail, Drive, and Sheets to analyze matter communications, correspondence, and surface internal files while enforcing enterprise access controls.

• Microsoft 365: Integrates directly with Word, Outlook, and SharePoint to triage inquiries, redlines, and securely ground work product across emails and matter folders without breaking workflow context. 

Document management:

• iManage: Gives Gemini Enterprise for Legal permission-bound, auditable access to governed iManage content, including matter history, documents, and institutional knowledge, eliminating the need for bulk exports or custom integrations.

• NetDocuments: Enables Gemini Enterprise to search and analyze an organization's knowledge and expertise while preserving each user's existing permissions and ethical walls. Source documents never leave the governed NetDocuments environment. 

Contract lifecycle and execution:

• Docusign: Integrates agreement metadata, active approval workflows, and contract repositories to surface obligations, track renewal dates, and streamline drafting-to-execution lifecycles.

E-discovery and litigation intelligence:

• Everlaw: Connects Gemini Enterprise to litigation and investigations evidence in Everlaw, allowing legal teams to search and analyze their data, uncover case insights, and build timelines directly in Gemini Enterprise, with responses grounded in the underlying documents and access governed by each user’s existing Everlaw permissions.

• RelativityOne: Allows legal teams to stand up workspaces, organize case data, and manage operations within a secure perimeter. 

Primary law, research, and public dockets:

• Thomson Reuters HighQ: Connects Gemini Enterprise for Legal with HighQ, helping legal teams securely access and reference relevant HighQ content within their workflows. 

• Free Law Project’s CourtListener.com: Provides access to millions of federal and state court opinions, PACER dockets, judicial profiles, and oral arguments.

• Courtroom5: Delivers jurisdiction-aware civil litigation datasets, procedural rules, and deadline calculation logic.

Specialized legal AI and intellectual property:

• Harvey: Bridges Harvey’s legal reasoning intelligence into Gemini Enterprise, supporting complex legal reasoning and research across Vault projects. 

• Solve Intelligence: Links Gemini Enterprise to worldwide patent and non-patent literature, SEP technical standards, and prior art databases for patent drafting and claim charting.

• Legora: Agentic operating system for legal work, supporting lawyers in research, review, and drafting across complex matters 

Third-party agents and implementation partners 

Every firm and legal department practices differently. Through our open platform, organizations can deploy pre-built partner agents or collaborate with systems integrators to scale custom capabilities:

• Deloitte: Contract Summarize Pro Agent that synthesizes complex contracts into clear summaries for rapid insight and informed decision-making. Clause Guard contract redlining agent to accelerate turnaround times, and minimize risk in contract management. 

• Eudia Knowledge agent: Accelerates high-stakes legal and contracting work by combining institutional intelligence with a suite of agents that execute deep legal research, high-volume document analysis, and regulatory compliance screening.

• Global systems integrators & tech partners: Strategic partnerships with Accenture, Deloitte, Devoteam, Factor Law, KPMG, Tribe.ai, Valtech, Zazmic, Zencore, and 66degrees ensure legal teams can customize, integrate, and scale these capabilities across complex enterprise architectures without vendor lock-in.

Gemini Enterprise for Legal offers leading firms a way to manage modern legal work with a secure agentic platform

Developed alongside leading global law firms

We are working closely with leading law firms, including Cleary Gottlieb, Freshfields, Weil, and Williams & Connolly, to ensure these capabilities address the realities of sophisticated legal practice.

“Cleary is committed to embedding AI into our workflows in strategic and competitive ways. Using Google’s Gemini Enterprise, which can slot in seamlessly with other daily work tools, we can unlock greater efficiencies for our teams and help them deliver even higher quality work for our clients.” — Jeff Karpf, Managing Partner, Cleary Gottlieb.

“The legal sector is entering a period of accelerated change and transformation. For Freshfields the opportunity lies in how effectively we combine frontier technology like Gemini Enterprise for Legal with our expertise, robust governance and institutional knowledge to create value for our clients. Our strategic, multi-year partnership with Google Cloud is helping us accelerate that work and enhance how we deliver legal services.” — Alan Mason, Global Managing Partner, Freshfields.

“We’re thrilled to partner with Google Cloud in the early adoption of Gemini Enterprise for Legal. We look forward to integrating Google’s technology to streamline workflow and further support our litigators in shaping outcomes critical to our clients’ futures.” — Joe Petrosinelli, Chairman, Williams & Connolly.

"Our collaboration with Google gives us early access to emerging capabilities while allowing us to help shape the platform based on the realities of sophisticated legal practice. The result is technology that helps us continue to deliver the innovative, high-quality service our clients expect from Weil. We are looking forward to working with Google Cloud engineers and the Gemini Enterprise product team as we further innovate and evolve our AI capabilities." — Ramona Nee, Incoming Executive Partner, Weil.

Weil scales judicial insights with Benchmark, built on Gemini Enterprise

Built on an enterprise-grade foundation

Confidentiality is not a feature of legal technology; it is the precondition for using any at all. Because Gemini Enterprise for Legal runs on Google Cloud infrastructure and the Gemini Enterprise platform, the permissions and access controls your firm already maintains are the boundaries the platform operates within — not settings it asks you to reconstruct.

Client data, firm-specific playbooks, intellectual property, custom agents, and model outputs stay private to your organization, and are never used to train or fine-tune Google's foundation models. Because we operate the full stack, from infrastructure and models through the application layer, we can tune performance and cost together — so expanding what your teams can take on does not mean expanding spend at the same rate.

This is just the beginning

The launch of Gemini Enterprise for Legal represents another defining step in delivering on the promise of Gemini Enterprise: bringing the best of Google AI to every professional, for every workflow, natively tailored to the way they work.

Gemini Enterprise for Legal is available in preview today, launching alongside our new purpose-built solution for Financial Services. We invite law firms and legal teams to explore how Gemini Enterprise can transform their most critical workflows, with solutions for Healthcare, Life Sciences, and other Professional Services on the horizon.

Protecting capital in today's markets requires immense speed and precision. A financial analyst preparing a deal memo works across licensed market data, internal models, and confidential client files. General-purpose AI lacks the real-time accuracy, verifiable data lineage, and strict security that financial institutions demand. While model intelligence is necessary, without deep integration into trusted financial systems, it is not sufficient.

Making AI genuinely useful inside an industry requires four things, together: domain expertise encoded into reusable skills, secure connections to the systems and data the work depends on, agents that can act inside real workflows, and an open ecosystem that extends and scales all of it — with governance running underneath all four. Each is valuable alone. Only together do they produce something an institution can actually put into production and see true return on investment.

Today, we are delivering on this vision with Gemini Enterprise for Financial Services, bringing Google’s agentic AI directly into the workflows of capital markets and corporate banking.

Bringing Gemini Enterprise into the workflows of capital markets and corporate banking

Four components, built for financial work 

Gemini Enterprise for Financial Services delivers an integrated, secure environment configured for rapid deployment with four core components:

1. Purpose-built financial skills. Skills are reusable packages of instructions and context that teach an agent to run a specialized task the way your institution runs it — applying custom formatting to a report, pulling a specific data cut, following a defined research methodology. They are available inside the Financial Research agent and to any agent your teams build.

2. Secure Model Context Protocol (MCP) connectors. Direct integrations, using MCP, into essential financial platforms and licensed data sources, configured inside your own environment. Access stays bound by the entitlements you already maintain — licensed data stays licensed, and permissioned data stays permissioned.

3. Agents that act. At its core is the Financial Research agent which is a Google-built, Google-managed agent that runs end-to-end research with full explainability. It ships with more than 50 foundational skills and exposes its reasoning through confidence scores, explicit methodologies, data snapshots for auditing, and precise source citations. Analysts can use it directly in the Gemini Enterprise app or wire it into existing agent workflows through Agent-to-Agent (A2A) APIs, and it connects to enterprise data sources over MCP to produce reports and documents in the formats your teams already use. Alongside it, out-of-the-box partner agents cover other workflows and extend the capabilities further.

4. An open partner ecosystem. Scale with global systems integrators and specialized fintech providers including 66degrees, Accenture, Artefact, Capgemini, Cognizant, Deloitte, Genpact, GFT Technologies, Infosys, KPMG, PwC, Quantiphi, Slalom, Tribe AI, and Zencore to customize and integrate the platform into your own architecture, without vendor lock-in.

Running underneath: a governed control plane. A single dashboard for IT and risk teams that natively enforces security policies (VPC, CMEK), maintains private data isolation, and holds every output to verifiable grounding with traceable citations.

Unlocking high-value workflows with domain-specific skills

Whether used by private equity specialists, wealth managers, or compliance teams, the solution adapts to diverse workflows like credit risk assessment, portfolio monitoring, market news synthesis, and investigative financial research:

• Elevate advisor insights: Equips relationship managers and advisors with AI-generated insights, personalized recommendations, and tailored artifacts, enabling higher-quality conversations and fostering loyalty. 
• Deepen Know Your Customer (KYC) research and analysis: Modernizes onboarding and Know Your Customer (KYC) workflows across private banking and prime brokerage by using multi-format ingestion (PDFs, Excel, SEC filings) to map complex corporate hierarchies, evaluate risk personas, and resolve ultimate beneficial owners (UBOs).
• Enhance portfolio resilience: Helps trading desks deal with sudden macroeconomic shocks. It reduces complex bond portfolio risk exposure analysis to a sub-5-minute execution, complete with automated duration-hedging strategy suggestions.
• Uncover credit market opportunities: Transforms credit data into actionable trade ideas by identifying and isolating potential mispricings. This enables teams to expand trading volumes while lowering back-office risk and underwriting latency.
• Accelerate bond issuance: Compresses client pitch presentation timelines from days to minutes so that fixed-income and underwriting teams can proactively target prospects, increase deal capacity, and secure a crucial first-mover advantage to help win more business.

Open ecosystem of connectors across the financial technology stack

Gemini Enterprise connects directly to core financial systems via secure MCP connectors. Access is bound by existing role-based controls, ensuring verifiable grounding and precise source citations:

Productivity and collaboration:

• Google Workspace: Enables seamless analysis and live artifact generation across Docs, Sheets, and Slides while adhering to enterprise DLP policies.

• Microsoft 365: Integrates directly with Excel, Word, and PowerPoint to populate financial models, research memos, and client pitch decks.

Market data and financial fundamentals:

• Daloopa: Provides the structured, source-linked financial data layer that enables finance professionals and AI tools to produce accurate and auditable results. 

• FactSet: Enables secure, authorized access to FactSet's multi-asset class financial and non-financial datasets, powering reliable AI-driven workflows with fully auditable, compliant insights. 

• Finnhub: Provides real-time financial APIs, global fundamentals, and earnings call transcripts for in-depth financial research.

• Fiscal.ai: Delivers institutional-grade financial data within minutes of earnings, covering financials, news, ownership, segments & KPIs, filings, and earnings call transcripts. 

• Guidepoint: Connects to primary research insights and expert network transcripts to inform and validate investment theses.

• S&P Global: Integrates cited, verifiable S&P Global data for a range of workflows, from financial analysis, to peer benchmarking, industry research, and more.

Risk, ratings, and private markets:

• Moody’s: Brings ratings, default risk models, and real time news fused into one lens for counterparty risk assessment. 

• MSCI: Connects to proprietary indexes, data and models spanning public and private assets and also provides risk analytics and factor exposures. 

• PitchBook: Provides comprehensive data and research on private equity, venture capital, credit, M&A, and public markets, including, company financials, deal terms, valuations, and fund performance.

Regulatory and corporate records:

• SEC Edgar: Delivers instant, verifiable retrieval of statutory filings, 10-Ks, 10-Qs, and 8-Ks with precise citation mapping.

• Dun & Bradstreet: Accelerates commercial onboarding and KYB verification through direct access to global corporate hierarchy records.

Digital assets and indices:

• CoinDesk Data and Indices: Supplies institutional-grade digital asset pricing, benchmark indices, and crypto market intelligence for multi-asset strategies.

Introducing Gemini Enterprise for Financial Services

Third-party agents and implementation partners

Organizations can deploy out-of-the-box partner agents or collaborate with global systems integrators to scale custom capabilities without vendor lock-in:

• D&B Business Verification agent: Accelerates commercial onboarding and strengthens KYC compliance.

• FlowX agents: Automate loan pack completeness check, document reconciliation and many other mission critical processes for financial institutions.

• Obin Financial agent: Helps asset management, commercial lending, and insurance teams accelerate complex financial analyses.

• S&P Global agents: Data Retrieval Agent for multi-step analysis, report generation, research workflows, and the Horizons Agents that help turn complex energy and sustainability data into fast insights for finance workflows.

• Global systems integrators and tech partners: Strategic partnerships connect firms with specialist FinTech and leading global systems integrators, including 66degrees, Accenture, Artefact, Capgemini, Cognizant, Deloitte, Genpact, GFT Technologies, Infosys, KPMG, PwC, Quantiphi, Slalom, Tribe AI, and Zencore to manage custom configurations and deploy specialized capabilities at a global scale.

Developed alongside leading global financial institutions

We are developing these capabilities in close collaboration with financial institutions, including Deutsche Bank and CME Group, to ensure they reflect the operational realities of the industry.

“As a design partner for the Financial Research agent, Deutsche Bank has helped shape this capability in view of the realities of a highly regulated industry – from data protection and governance to the workflows our teams use every day,” said Marie-Jeanne Deverdun, Chief Technology, Data and Innovation Officer, and Member of the Deutsche Bank Management Board. “Starting in the Corporate Bank, we see significant potential to reduce manual research effort, improve the consistency and auditability of outputs, and give our teams more time for client conversations. This is an important step in applying AI where it can make a practical difference: safely, responsibly and at scale.”

This launch builds on the rapidly growing momentum of Gemini Enterprise, with many leading financial institutions like BNY,  Citi Wealth, Lloyds Banking Group, Macquarie Bank, and Signal Iduna using it to equip their workforce with advanced, agentic workflow tools to drive growth and efficiency. 

Built on an enterprise-grade foundation

Because Gemini Enterprise for Financial Services runs on Google Cloud infrastructure and the Gemini Enterprise platform, organizations get the security, governance, compliance, and cost-management capabilities they expect from an enterprise platform. 

Customer data, business rules, intellectual property, custom agents, and model outputs remain private to their organization. Your data is never used to train or fine-tune Google’s foundation models. Furthermore, our full-stack approach - from infrastructure and models to the application layer - allows us to optimize performance and cost, helping organizations maximize the value of their AI investments. 

This is just the beginning

Gemini Enterprise for Financial Services is available in preview today, launching alongside our new purpose-built solution for Legal. We invite enterprise leaders in financial institutions to explore how Gemini Enterprise can transform their most critical workflows, with solutions for Healthcare, Life Sciences, and other Professional Services on the horizon.

※この投稿は米国時間 2026 年 8 月 11 日に、Google Cloud blog に投稿されたものの抄訳です。

ほとんどの企業は、デバイスを通じて顧客と接点を持っています。モバイルアプリを使用した商品の注文、カスタマー サービスへの問い合わせ、コンテンツの閲覧、アカウント管理など、どのような操作においても、カスタマー エクスペリエンスはアプリが顧客のデバイス上でいかにスムーズに動作するかに左右されます。

このため、ローカルで動作するコンポーネントを含むあらゆるエンタープライズ リリースにおいて、多種多様なデバイスでアプリケーションを構築・テストすることは極めて重要です。しかし、デバイスを大規模に調達してホストするには費用がかかり、複雑な作業が必要になります。また、テストは不安定で、判定不能だったり、デバッグが難しかったりすることがよくあります。そのため、多くのデベロッパーは、手元の実機でリリース前のテストを行い、その結果が他のほとんどのデバイスでも通用することを願うしかありません。

この課題を解決するため、このたび Google Cloud において Developer Device Platform（DDP）の公開プレビュー版の提供開始を発表いたしました。DDP は、実機と高並行仮想エミュレータにわたる複数のハードウェア プロファイルに、オンデマンドで即座にアクセスできるフルマネージド クラウド プラットフォームです。DDP は、クラウド デベロッパー向けの Firebase Test Lab の進化版であり、エージェント型開発向けに構築された初のデバイス プラットフォームでもあります。DDP を使用すると、デベロッパーは好みのエージェントを利用して、さまざまなデバイスにわたってアプリのバイブ コーディング、テストの実行、デバッグ、パフォーマンスの最適化を効率的かつ迅速に行うことができます。

アプリを構築してテストし、パフォーマンスを保証する

標準的なモバイル開発ライフサイクルでは、デベロッパーは新しい機能を反復的に開発し、さまざまな対象デバイスでパフォーマンスを保証するために QA テストを実行し、最適化およびデバッグ済みの機能をユーザー向けに本番環境へリリースします。デベロッパー デバイス プラットフォームには、このサイクルを加速させる 2 つの主な機能があります。

デバイス ストリーミングによるインタラクティブなデバッグ: Device Streaming API を使用すると、デベロッパーは選択したエミュレータや実機に直接アクセスし、バイブ コーディング、反復テスト、デバッグ、アプリとのインタラクションをリモートで行うことができます。デバイス ストリーミングを使用すれば、実機のハードウェアでパフォーマンスをモニタリングしながら、カスタマー エクスペリエンスを直接体験し、リアルタイムでスクロールやクリックといった操作を簡単に行うことができます。

デバイスランによる並列テスト: Google の Device Run API を使用すると、デベロッパーは CI / CD パイプラインの一部としてテストを作成し、一度に数百もの異なるデバイスで並列実行できます。得られた結果をもとに、デベロッパーは特定のデバイスに固有の問題をピンポイントで特定してデバッグでき、あらゆる層のデバイスで動作するという確信を持ってコードを本番環境にリリースできます。

DDP エージェント スキルと効率的なテストでモバイルアプリ開発を加速させる

モバイル開発におけるコーディング エージェントの台頭は、特に実機と組み合わせることで新たな可能性を切り開きます。コーディング エージェントは、実機のハードウェアを操作してテストできるため、独自のスマートフォン画面サイズ（折りたたみ式スマートフォンの UI など）や特殊なハードウェア（CPU や GPU など）を活用できます。

Developer Device Platform はまもなく Android Studio と Android CLI に統合され、Device Streaming API を介して実機に直接アクセスできるようになります。DDP エージェント スキルを使用すると、選択した AI コーディング エージェントと連携して開発を加速することもできます。DDP エージェント スキルを使用すると、コーディング エージェントは次のことができます。

• 複数のステップから成るユーザー ジャーニーを単独で実行する

• 視覚的なアーティファクトを検出する

• オンデバイスでチップのパフォーマンスをリアルタイムで分析する

• ハードウェア固有のバグの修正を検証し、デバイス固有の機能に合わせて最適化する

これらのエージェント機能に加えて、DDP ではアプリのパッケージ化や、スマート シャーディングによる並列テストの実行も可能です。これにより、数百台のデバイスにわたるテスト結果をわずか数分で確認できるようになります。スマート自動再試行により、DDP はシャード内で失敗した特定のテストを再試行するため、テストスイート全体を再実行することなく、エラーをより迅速に解決できます。

デベロッパー デバイス プラットフォームで今すぐ開発を始めましょう

8 月 12 日より、Developer Device Platform がすべての Google Cloud ユーザー向けに公開プレビュー版として提供されます。公開プレビュー期間中は、1 分単位の従量課金制モデルに基づいて料金が請求されるため、実際にテストに使用した時間（分）に対してのみ料金が発生します。なお、料金はエミュレータと実機でそれぞれ異なります。

Google Cloud を利用するモバイル デベロッパーが、Developer Device Platform を活用して開発を加速し、増え続ける独自のデバイス機能やオンデバイス AI の可能性を最大限に引き出すことを楽しみにしています。

- Google プロダクト マネージャー、Derek Bekebrede

- プロダクト戦略およびオペレーション担当、Jason Nager

※この投稿は米国時間 2026 年 8 月 14 日に、Google Cloud blog に投稿されたものの抄訳です。

企業が単純なチャット アシスタントの使用から自律型のエージェント ワークロードに移行すると、すぐに厳しい現実に直面します。それは、エージェントが元テーブルを直接使用する際に、不正確な分析情報を生成する傾向があるということです。

BigQuery Graph は、組織がフラットで静的なテーブルから脱却し、現実世界に存在する企業を正確に表現できるように、つまり、現実世界の依存関係を持つ、相互に接続された事業体として表現できるようにします。BigQuery Graph（プレビュー版）でメジャーがサポートされるようになったことで、管理された指標と関係マッピングが統合されます。これにより、エージェントはグラフで収集された複雑な依存関係全体について、メジャーの精度に基づいて推論できます。

関係が重要な理由

従来のデータ構造では、マルチホップのビジネス コンテキストが考慮されないため、次のように、AI エージェントが運用上誤った意思決定を行うことがあります。

• 具体的な問題: 小売業者のエージェントが、シアトルでの冬用ジャケットの売り上げが 12% 減少した理由を尋ねられた場合、フラット テーブルをクエリして、「事実」（12% の減少）を報告することはできますが、「シアトルの注文 ➔ 配送センター ➔ 地域の嵐によるサプライヤーの遅延」という関係パスを追跡できないため、「理由」を特定することはできません。

• 分断されたシステムのリスク: 関係のコンテキストがないため、エージェントが関連性のない 15% オフのキャンペーンを提案し、不必要に利益率を低下させます。さらに、あるチームがサプライヤーの関係を別のグラフ データベースにマッピングし、別のチームが SQL 指標を維持するというように、別々のシステムを維持すると、エージェントは実行時にこれらのスタックを結合せざるを得なくなります。このプロセスは時間がかかり、費用もかさみ、KPI の計算に一貫性がなくなります。

BigQuery Graph のメジャーは、既存のテーブルをプロパティ グラフにインプレースでマッピングし、ETL を不要にすることで、この問題を解決します。この統合された設定により、次のような問い合わせの論理的な進化が可能になります。

1. メタデータのグラウンディングは、存在するデータを確立します。

2. ビジネス指標（メジャー）は、ビジネスのパフォーマンスを計算します。

3. 関係マッピング（グラフ）は、それが起こった理由を明らかにします。

仕組み

従来、グラフ走査中の標準 SQL の結合では行が重複し、集計計算が不正確になっていました。BigQuery Graph は、これをネイティブに解決します。

データモデラーは、プロパティ グラフ DDL 内で直接 MEASURE（SUM や AVG など）を定義します。エンジンは GRAPH_EXPAND 関数と AGG アグリゲータを介して標準 SQL を使用して、指標を評価する前に構造グラフのパスを解決します。これにより、エージェントは計算機（SQL）が必要なときと地図（グラフ）が必要なときを認識できるほどスマートになります。

bigquery-public-data のような一般公開プロジェクトは厳密に読み取り専用であるため、読み取り専用の一般公開テーブルをノードおよびエッジとして直接参照しながら、プレースホルダ変数（YOUR_PROJECT_ID）を使用して独自のプロジェクト内で論理プロパティ グラフをマッピングする必要があります。

BigQuery Studio でグラフ インテリジェンスを民主化

デベロッパーとビジネス ユーザーの双方が、これらの関係ネットワークをスムーズに管理、デプロイできるように、直感的なネイティブ運用ツールを BigQuery Studio に直接組み込みました。

• 視覚的なグラフモデラー: BigQuery Studio 内のノーコードのドラッグ＆ドロップ インターフェースで、複雑な DDL スクリプトを手動で記述することなく、プロパティ グラフ、ノード、エッジを視覚的に構築、編集、マッピングできます。

• 会話型分析（CA）のインテグレーション: ユーザーはグラフと自然にやり取りできます。会話型分析エージェントは、テーブル結合を推測するのではなく、グラフの決定論的な関係認識マップをナビゲートし、自然言語の質問を、境界が制約された正確な GoogleSQL クエリまたは ISO GQL クエリに変換します。これにより、モデルのハルシネーションを防ぎ、セマンティックな一貫性を確保します。

統合されたセマンティクス: Looker とのネイティブなインテグレーション

断片化されたロジック スタックの維持を避けるために、ビジネス指標はデータレイヤに存在する必要があります。Looker（LookML）を、データベース内分析モデルとしての BigQuery Graphs とネイティブに統合することで、コアでロジックを一度定義するだけで済みます。

• データベース管理モデル（sql_analytic_model_name）: sql_analytic_model_name を使用して、Looker にデータベース定義の BigQuery Graph を直接参照させ、標準の LookML のディメンションとメジャーをグラフ プロパティに直接マッピングします。

• Looker 管理モデル（derived_analytic_model）: derived_analytic_model を使用して、LookML ビュー内で BigQuery Graph スキーマを直接定義します。Looker は、SQL DDL ステートメントを動的に生成して実行し、BigQuery 内のグラフを維持します。

• エンタープライズ DevOps ワークフロー: Looker IDE、Git ベースのバージョン管理、継続的インテグレーション（CI）を使用して、グラフのライフサイクル全体を管理します。主要な KPI（離脱率など）は、検証済みで、信頼できる、まったく同じものが維持されます。

- Google Cloud、グループ プロダクト マネージャー、Deepak Dayama

- ソフトウェア開発マネージャー、Yun Zhang

※この投稿は米国時間 2026 年 8 月 8 日に、Google Cloud blog に投稿されたものの抄訳です。

スポーツのライブ配信は、デジタル メディア インフラストラクチャにとって究極のストレステストとなります。運営面の成否はミリ秒単位で評価され、何百万人もの視聴者が生で同時に目にします。2026 FIFA ワールドカップ開催期間中、スペイン語メディアの大手コングロマリットである TelevisaUnivision は、大きな課題に直面しました。メキシコは主要な開催国であると同時に、代表チームが有力な優勝候補であったため、ファンの関心は高く、ラテンアメリカ全域と TelevisaUnivision の ViX ストリーミング プラットフォームで前例のない需要が発生しました。

TelevisaUnivision のような大手放送局にとって、重要なイベントはブランドと評判に直接的かつ長期的な影響を及ぼします。視聴者は、試合の重要な瞬間を、途切れることなく、鮮明に視聴することを求めています。決定的なゴールシーンでの映像の中断、キックオフ時のログイン遅延、ストリーミング解像度の低下は、顧客満足度に直接影響し、サブスクライバーの離脱やブランドの希薄化を招くリスクがあります。トップレベルの世界的スポーツ イベントをストリーミング配信する場合、技術面の運用が消費者の信頼に直接影響するため、プロバイダはダウンタイムなしの可用性と完璧なパフォーマンスを絶対に確保する必要があります。

TelevisaUnivision が Google Cloud を選んだ理由

ISP の細分化が激しく、国境を越えた中継のボトルネックが目立つラテンアメリカの複雑なネットワーキング エコシステムに対応するには、標準的なベンダー関係以上のものが必要でした。TelevisaUnivision は、ネットワーク容量、インフラストラクチャの復元力、カスタム機能の開発に共同で取り組んでくれる戦略的パートナーを必要としていました。TelevisaUnivision が Google Cloud の Media CDN を選んだ理由は、Google Cloud のアーキテクチャと顧客重視の姿勢という 2 つの基本的な差別化要因でした。

プラットフォーム アーキテクチャ 

Media CDN は、送信元インフラストラクチャを保護しながら、ライブ配信のトラフィックの急増を吸収するために特別に構築された、グローバルに分散された復元力のあるインフラストラクチャを提供しました。このアーキテクチャがもたらした主なメリットは次のとおりです。

• ISP 内のディープ エッジ キャッシング: メキシコ、中南米のローカル ISP ネットワーク内に深く埋め込まれた Media CDN のキャッシュ ノードにより、視聴者から 1 ネットワーク ホップ以内の場所に動画セグメントが配置されました。

• ISP とのダイレクト ピアリング: América Móvil や Telefônica などの主要な地域通信事業者とのダイレクト ピアリング接続を確立することで、混雑した多国間の中継ルートを完全に回避するアーキテクチャが実現しました。

• 専用容量の予約: TelevisaUnivision は、リージョン内で専用のヘッドルームを割り当ててライブイベントの容量を予約しました。この方法により、ライブ配信のトラフィックが「ノイジー ネイバー」のリスクから隔離され、ピーク時のトラフィック急増を無理なく吸収できました。

• Valkey 9.0 によるミリ秒未満のセッション: ワールドカップ期間中の大規模なトラフィック急増に対処するため、TelevisaUnivision はセッション ストアを Memorystore for Valkey 9.0 に移行し、エッジ コンピューティング上のサーバーレス マイクロサービスとして稼働させました。このアーキテクチャにより、重要な認証と権限チェックの応答時間が 1 ミリ秒未満になり、手動で容量を予約しなくても、ピーク時の API トラフィックを自動スケーリングで処理できるようになりました。

カスタマー サクセスへのこだわり

TelevisaUnivision が Google Cloud を選んだのには、技術的な能力だけでなく、共同エンジニアリング モデルや運用面での緊密な連携といった理由もありました。

• 24 時間 365 日の共同ウォールーム: 104 試合すべてで、TelevisaUnivision のエンジニアと Google Cloud のスペシャリストが統合コマンド センターで並んで作業しました。

• サービスとしてのプロアクティブなモニタリング: Google Cloud の顧客信頼性エンジニアリング チームが、24 時間体制でプロアクティブなモニタリングと自動アラートを提供しました。

• 運用面の共同権限: 大会前に、両チームが合同で、広範なストレステストとフェイルオーバーのシミュレーションを実施しました。試合のライブ配信中は、統合されたテレメトリーにより、共同リーダーがトラフィックを動的にルーティングし、地域の ISP で輻輳が発生したときに CDN 構成を即座に調整することができました。

まとめ

2026 FIFA ワールドカップにおける TelevisaUnivision と Google Cloud の戦略的パートナーシップは、世界のスポーツ放送の新たな基準を確立しました。TelevisaUnivision は、39 日間にわたるトーナメントの実施期間中、共同インフラストラクチャが以下の成果を上げたと報告しています。

TelevisaUnivision と Google Cloud は、ローカライズされたエッジ配信、ミリ秒未満のサーバーレス コンピューティング、運用における専任の共同エンジニアリングを統合することで、過去最高の世界的規模でライブ ストリーミング イベントを実施するための、実証済みのブループリントを確立しました。

- TelevisaUnivision、プロダクトおよびエンジニアリング担当シニア バイス プレジデント、Alexandro David Campos Vega 氏

- Google Cloud、ネットワーキング、プロダクト管理担当バイス プレジデント、Kevin Hutchins

Few professions are as exacting as the practice of law. A team reviewing a contract or building a case works inside strictly privileged information, firm-specific playbooks, and a body of law that changes constantly. The work thrives on nuanced, professional judgment — and the systems supporting it inherit real obligations: ethical walls that cannot be crossed, matter permissions that cannot be flattened, and a duty of confidentiality that does not bend for convenience.

General-purpose AI, however capable, does not meet that standard on its own. Foundational model intelligence is necessary. For legal work, it is nowhere near sufficient.

What makes the difference is the system built around the model: skills that enhance a firm's own expertise, connections into the systems where matters actually live, agents that complete work rather than return suggestions, and an open ecosystem to extend all of it — with governance running underneath all four. Each is valuable alone. Only in combination do they produce something a firm or a legal department can put into production and actually rely on.

Today we're bringing that to legal practice with Gemini Enterprise for Legal, part of our new suite of purpose-built industry solutions.

Bringing Gemini Enterprise to your legal practice

Four components of Gemini Enterprise for Legal

Developed alongside industry leaders, Gemini Enterprise for Legal provides an integrated, fully governed environment configured for rapid deployment across firms and corporate legal departments:

1. Purpose-built skills for legal work. Skills are reusable packages of instructions and context, designed by domain experts, that teach an agent to run a specialized task while enforcing your firm's playbooks, citation rules, and house style. They cover contract review and redlining, playbook creation, regulatory horizon scanning, legal research, DSAR fulfillment, and more — and they are where a firm's institutional knowledge becomes something the platform can execute rather than something a partner has to re-explain.

2. Connections to trusted systems and data. Secure MCP connectors link agents to the document management systems, case repositories, research services, and industry applications legal teams already rely on — inheriting each platform's existing user permissions and access controls rather than working around them.

3. Agents that act within the data. Skills and connections come together in agents that carry work through: pre-built agents from Google and leading legal software providers deploy out of the box. Specialized agents handle legal and policy research, regulatory screening, and contract drafting — bringing deep legal expertise onto a platform with centralized governance.

4. An open partner ecosystem. Every firm and legal department practices differently. Partnerships with global systems integrators and legal-tech specialists — Accenture, Deloitte, Devoteam, Factor Law, KPMG, Tribe.ai, Valtech, Zazmic, Zencore, and 66degrees — let organizations customize, integrate, and scale across complex enterprise architectures without vendor lock-in.

Running underneath: a governed control plane. A single dashboard for legal IT and risk teams that natively enforces security policies (VPC, CMEK), maintains private data isolation, and holds every output to verifiable grounding with traceable citations.

Unlocking high-value workflows with domain-specific skills

Gemini Enterprise for Legal shifts AI from passive querying to agentic execution, automating high-volume, precision-critical workflows such as:

• Proactive regulatory horizon scanning: Keeps legal and compliance teams ahead of global mandates by autonomously tracking legislative updates, court dockets, and supervisory bodies. It cross-references emerging changes against enterprise policies to flag exposure gaps and generate updated policy drafts for immediate practitioner review.

• Automating data discovery and DSAR response: Modernizes privacy workflows by compiling personal data across fragmented enterprise systems in seconds. It eliminates the manual toil of Data Subject Access Requests (DSARs), and allows for adherence to regulatory timelines while minimizing operational risk.

• Accelerating contract review and negotiation: Compresses turnaround times for inbound vendor agreements, NDAs, and complex M&A documentation by benchmarking terms against enterprise playbooks. It surfaces high-risk clauses and potential exposure, enabling attorneys to focus on strategic negotiation and high-value judgment.

• Building and updating contracting playbooks: Transforms legacy agreement archives into dynamic, actionable playbooks instantly. It automatically extracts key terms, fallback positions, and institutional knowledge to maintain portfolio-wide term consistency and lower negotiation variance across the enterprise.

• Redacting documents for motions to seal: Eliminates the manual burden of preparing court filings and redacting legal documents. It intelligently identifies sensitive terms and PII for rapid practitioner confirmation, dramatically accelerating filing timelines while safeguarding confidentiality.

• Drafting NDA documents: Elevates contract creation through structural fidelity validation that enforces firm standards and logical document hierarchies. It allows legal teams to rapidly generate and evolve non-disclosure agreements with complete formatting confidence and minimal review overhead.

Open ecosystem of connectors across the legal technology stack

Legal work is only as good as its sources, and legal data carries permissions that have to travel with it. Gemini Enterprise for Legal connects directly to core legal systems via secure MCP connectors. Crucially, access is bound by existing role-based access controls, document-level permissions, and trusted data controls inherited from document management and ediscovery systems.

Productivity and collaboration:

• Google Workspace: Connects seamlessly with Google Docs, Gmail, Drive, and Sheets to analyze matter communications, correspondence, and surface internal files while enforcing enterprise access controls.

• Microsoft 365: Integrates directly with Word, Outlook, and SharePoint to triage inquiries, redlines, and securely ground work product across emails and matter folders without breaking workflow context. 

Document management:

• iManage: Gives Gemini Enterprise for Legal permission-bound, auditable access to governed iManage content, including matter history, documents, and institutional knowledge, eliminating the need for bulk exports or custom integrations.

• NetDocuments: Enables Gemini Enterprise to search and analyze an organization's knowledge and expertise while preserving each user's existing permissions and ethical walls. Source documents never leave the governed NetDocuments environment. 

Contract lifecycle and execution:

• Docusign: Integrates agreement metadata, active approval workflows, and contract repositories to surface obligations, track renewal dates, and streamline drafting-to-execution lifecycles.

E-discovery and litigation intelligence:

• Everlaw: Connects Gemini Enterprise to litigation and investigations evidence in Everlaw, allowing legal teams to search and analyze their data, uncover case insights, and build timelines directly in Gemini Enterprise, with responses grounded in the underlying documents and access governed by each user’s existing Everlaw permissions.

• RelativityOne: Allows legal teams to stand up workspaces, organize case data, and manage operations within a secure perimeter. 

Primary law, research, and public dockets:

• Thomson Reuters HighQ: Connects Gemini Enterprise for Legal with HighQ, helping legal teams securely access and reference relevant HighQ content within their workflows. 

• Free Law Project’s CourtListener.com: Provides access to millions of federal and state court opinions, PACER dockets, judicial profiles, and oral arguments.

• Courtroom5: Delivers jurisdiction-aware civil litigation datasets, procedural rules, and deadline calculation logic.

Specialized legal AI and intellectual property:

• Harvey: Bridges Harvey’s legal reasoning intelligence into Gemini Enterprise, supporting complex legal reasoning and research across Vault projects. 

• Solve Intelligence: Links Gemini Enterprise to worldwide patent and non-patent literature, SEP technical standards, and prior art databases for patent drafting and claim charting.

• Legora: Agentic operating system for legal work, supporting lawyers in research, review, and drafting across complex matters 

Third-party agents and implementation partners 

Every firm and legal department practices differently. Through our open platform, organizations can deploy pre-built partner agents or collaborate with systems integrators to scale custom capabilities:

• Deloitte: Contract Summarize Pro Agent that synthesizes complex contracts into clear summaries for rapid insight and informed decision-making. Clause Guard contract redlining agent to accelerate turnaround times, and minimize risk in contract management. 

• Eudia Knowledge agent: Accelerates high-stakes legal and contracting work by combining institutional intelligence with a suite of agents that execute deep legal research, high-volume document analysis, and regulatory compliance screening.

• Global systems integrators & tech partners: Strategic partnerships with Accenture, Deloitte, Devoteam, Factor Law, KPMG, Tribe.ai, Valtech, Zazmic, Zencore, and 66degrees ensure legal teams can customize, integrate, and scale these capabilities across complex enterprise architectures without vendor lock-in.

Gemini Enterprise for Legal offers leading firms a way to manage modern legal work with a secure agentic platform

Developed alongside leading global law firms

We are working closely with leading law firms, including Cleary Gottlieb, Freshfields, Weil, and Williams & Connolly, to ensure these capabilities address the realities of sophisticated legal practice.

“Cleary is committed to embedding AI into our workflows in strategic and competitive ways. Using Google’s Gemini Enterprise, which can slot in seamlessly with other daily work tools, we can unlock greater efficiencies for our teams and help them deliver even higher quality work for our clients.” — Jeff Karpf, Managing Partner, Cleary Gottlieb.

“The legal sector is entering a period of accelerated change and transformation. For Freshfields the opportunity lies in how effectively we combine frontier technology like Gemini Enterprise for Legal with our expertise, robust governance and institutional knowledge to create value for our clients. Our strategic, multi-year partnership with Google Cloud is helping us accelerate that work and enhance how we deliver legal services.” — Alan Mason, Global Managing Partner, Freshfields.

“We’re thrilled to partner with Google Cloud in the early adoption of Gemini Enterprise for Legal. We look forward to integrating Google’s technology to streamline workflow and further support our litigators in shaping outcomes critical to our clients’ futures.” — Joe Petrosinelli, Chairman, Williams & Connolly.

"Our collaboration with Google gives us early access to emerging capabilities while allowing us to help shape the platform based on the realities of sophisticated legal practice. The result is technology that helps us continue to deliver the innovative, high-quality service our clients expect from Weil. We are looking forward to working with Google Cloud engineers and the Gemini Enterprise product team as we further innovate and evolve our AI capabilities." — Ramona Nee, Incoming Executive Partner, Weil.

Weil scales judicial insights with Benchmark, built on Gemini Enterprise

Built on an enterprise-grade foundation

Confidentiality is not a feature of legal technology; it is the precondition for using any at all. Because Gemini Enterprise for Legal runs on Google Cloud infrastructure and the Gemini Enterprise platform, the permissions and access controls your firm already maintains are the boundaries the platform operates within — not settings it asks you to reconstruct.

Client data, firm-specific playbooks, intellectual property, custom agents, and model outputs stay private to your organization, and are never used to train or fine-tune Google's foundation models. Because we operate the full stack, from infrastructure and models through the application layer, we can tune performance and cost together — so expanding what your teams can take on does not mean expanding spend at the same rate.

This is just the beginning

The launch of Gemini Enterprise for Legal represents another defining step in delivering on the promise of Gemini Enterprise: bringing the best of Google AI to every professional, for every workflow, natively tailored to the way they work.

Gemini Enterprise for Legal is available in preview today, launching alongside our new purpose-built solution for Financial Services. We invite law firms and legal teams to explore how Gemini Enterprise can transform their most critical workflows, with solutions for Healthcare, Life Sciences, and other Professional Services on the horizon.

Protecting capital in today's markets requires immense speed and precision. A financial analyst preparing a deal memo works across licensed market data, internal models, and confidential client files. General-purpose AI lacks the real-time accuracy, verifiable data lineage, and strict security that financial institutions demand. While model intelligence is necessary, without deep integration into trusted financial systems, it is not sufficient.

Making AI genuinely useful inside an industry requires four things, together: domain expertise encoded into reusable skills, secure connections to the systems and data the work depends on, agents that can act inside real workflows, and an open ecosystem that extends and scales all of it — with governance running underneath all four. Each is valuable alone. Only together do they produce something an institution can actually put into production and see true return on investment.

Today, we are delivering on this vision with Gemini Enterprise for Financial Services, bringing Google’s agentic AI directly into the workflows of capital markets and corporate banking.

Bringing Gemini Enterprise into the workflows of capital markets and corporate banking

Four components, built for financial work 

Gemini Enterprise for Financial Services delivers an integrated, secure environment configured for rapid deployment with four core components:

1. Purpose-built financial skills. Skills are reusable packages of instructions and context that teach an agent to run a specialized task the way your institution runs it — applying custom formatting to a report, pulling a specific data cut, following a defined research methodology. They are available inside the Financial Research agent and to any agent your teams build.

2. Secure Model Context Protocol (MCP) connectors. Direct integrations, using MCP, into essential financial platforms and licensed data sources, configured inside your own environment. Access stays bound by the entitlements you already maintain — licensed data stays licensed, and permissioned data stays permissioned.

3. Agents that act. At its core is the Financial Research agent which is a Google-built, Google-managed agent that runs end-to-end research with full explainability. It ships with more than 50 foundational skills and exposes its reasoning through confidence scores, explicit methodologies, data snapshots for auditing, and precise source citations. Analysts can use it directly in the Gemini Enterprise app or wire it into existing agent workflows through Agent-to-Agent (A2A) APIs, and it connects to enterprise data sources over MCP to produce reports and documents in the formats your teams already use. Alongside it, out-of-the-box partner agents cover other workflows and extend the capabilities further.

4. An open partner ecosystem. Scale with global systems integrators and specialized fintech providers including 66degrees, Accenture, Artefact, Capgemini, Cognizant, Deloitte, Genpact, GFT Technologies, Infosys, KPMG, PwC, Quantiphi, Slalom, Tribe AI, and Zencore to customize and integrate the platform into your own architecture, without vendor lock-in.

Running underneath: a governed control plane. A single dashboard for IT and risk teams that natively enforces security policies (VPC, CMEK), maintains private data isolation, and holds every output to verifiable grounding with traceable citations.

Unlocking high-value workflows with domain-specific skills

Whether used by private equity specialists, wealth managers, or compliance teams, the solution adapts to diverse workflows like credit risk assessment, portfolio monitoring, market news synthesis, and investigative financial research:

• Elevate advisor insights: Equips relationship managers and advisors with AI-generated insights, personalized recommendations, and tailored artifacts, enabling higher-quality conversations and fostering loyalty. 
• Deepen Know Your Customer (KYC) research and analysis: Modernizes onboarding and Know Your Customer (KYC) workflows across private banking and prime brokerage by using multi-format ingestion (PDFs, Excel, SEC filings) to map complex corporate hierarchies, evaluate risk personas, and resolve ultimate beneficial owners (UBOs).
• Enhance portfolio resilience: Helps trading desks deal with sudden macroeconomic shocks. It reduces complex bond portfolio risk exposure analysis to a sub-5-minute execution, complete with automated duration-hedging strategy suggestions.
• Uncover credit market opportunities: Transforms credit data into actionable trade ideas by identifying and isolating potential mispricings. This enables teams to expand trading volumes while lowering back-office risk and underwriting latency.
• Accelerate bond issuance: Compresses client pitch presentation timelines from days to minutes so that fixed-income and underwriting teams can proactively target prospects, increase deal capacity, and secure a crucial first-mover advantage to help win more business.

Open ecosystem of connectors across the financial technology stack

Gemini Enterprise connects directly to core financial systems via secure MCP connectors. Access is bound by existing role-based controls, ensuring verifiable grounding and precise source citations:

Productivity and collaboration:

• Google Workspace: Enables seamless analysis and live artifact generation across Docs, Sheets, and Slides while adhering to enterprise DLP policies.

• Microsoft 365: Integrates directly with Excel, Word, and PowerPoint to populate financial models, research memos, and client pitch decks.

Market data and financial fundamentals:

• Daloopa: Provides the structured, source-linked financial data layer that enables finance professionals and AI tools to produce accurate and auditable results. 

• FactSet: Enables secure, authorized access to FactSet's multi-asset class financial and non-financial datasets, powering reliable AI-driven workflows with fully auditable, compliant insights. 

• Finnhub: Provides real-time financial APIs, global fundamentals, and earnings call transcripts for in-depth financial research.

• Fiscal.ai: Delivers institutional-grade financial data within minutes of earnings, covering financials, news, ownership, segments & KPIs, filings, and earnings call transcripts. 

• Guidepoint: Connects to primary research insights and expert network transcripts to inform and validate investment theses.

• S&P Global: Integrates cited, verifiable S&P Global data for a range of workflows, from financial analysis, to peer benchmarking, industry research, and more.

Risk, ratings, and private markets:

• Moody’s: Brings ratings, default risk models, and real time news fused into one lens for counterparty risk assessment. 

• MSCI: Connects to proprietary indexes, data and models spanning public and private assets and also provides risk analytics and factor exposures. 

• PitchBook: Provides comprehensive data and research on private equity, venture capital, credit, M&A, and public markets, including, company financials, deal terms, valuations, and fund performance.

Regulatory and corporate records:

• SEC Edgar: Delivers instant, verifiable retrieval of statutory filings, 10-Ks, 10-Qs, and 8-Ks with precise citation mapping.

• Dun & Bradstreet: Accelerates commercial onboarding and KYB verification through direct access to global corporate hierarchy records.

Digital assets and indices:

• CoinDesk Data and Indices: Supplies institutional-grade digital asset pricing, benchmark indices, and crypto market intelligence for multi-asset strategies.

Introducing Gemini Enterprise for Financial Services

Third-party agents and implementation partners

Organizations can deploy out-of-the-box partner agents or collaborate with global systems integrators to scale custom capabilities without vendor lock-in:

• D&B Business Verification agent: Accelerates commercial onboarding and strengthens KYC compliance.

• FlowX agents: Automate loan pack completeness check, document reconciliation and many other mission critical processes for financial institutions.

• Obin Financial agent: Helps asset management, commercial lending, and insurance teams accelerate complex financial analyses.

• S&P Global agents: Data Retrieval Agent for multi-step analysis, report generation, research workflows, and the Horizons Agents that help turn complex energy and sustainability data into fast insights for finance workflows.

• Global systems integrators and tech partners: Strategic partnerships connect firms with specialist FinTech and leading global systems integrators, including 66degrees, Accenture, Artefact, Capgemini, Cognizant, Deloitte, Genpact, GFT Technologies, Infosys, KPMG, PwC, Quantiphi, Slalom, Tribe AI, and Zencore to manage custom configurations and deploy specialized capabilities at a global scale.

Developed alongside leading global financial institutions

We are developing these capabilities in close collaboration with financial institutions, including Deutsche Bank and CME Group, to ensure they reflect the operational realities of the industry.

“As a design partner for the Financial Research agent, Deutsche Bank has helped shape this capability in view of the realities of a highly regulated industry – from data protection and governance to the workflows our teams use every day,” said Marie-Jeanne Deverdun, Chief Technology, Data and Innovation Officer, and Member of the Deutsche Bank Management Board. “Starting in the Corporate Bank, we see significant potential to reduce manual research effort, improve the consistency and auditability of outputs, and give our teams more time for client conversations. This is an important step in applying AI where it can make a practical difference: safely, responsibly and at scale.”

This launch builds on the rapidly growing momentum of Gemini Enterprise, with many leading financial institutions like BNY,  Citi Wealth, Lloyds Banking Group, Macquarie Bank, and Signal Iduna using it to equip their workforce with advanced, agentic workflow tools to drive growth and efficiency. 

Built on an enterprise-grade foundation

Because Gemini Enterprise for Financial Services runs on Google Cloud infrastructure and the Gemini Enterprise platform, organizations get the security, governance, compliance, and cost-management capabilities they expect from an enterprise platform. 

Customer data, business rules, intellectual property, custom agents, and model outputs remain private to their organization. Your data is never used to train or fine-tune Google’s foundation models. Furthermore, our full-stack approach - from infrastructure and models to the application layer - allows us to optimize performance and cost, helping organizations maximize the value of their AI investments. 

This is just the beginning

Gemini Enterprise for Financial Services is available in preview today, launching alongside our new purpose-built solution for Legal. We invite enterprise leaders in financial institutions to explore how Gemini Enterprise can transform their most critical workflows, with solutions for Healthcare, Life Sciences, and other Professional Services on the horizon.