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. Gemini Enterprise for Financial Services 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: Mod
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