Google's Gemini ecosystem has rapidly evolved from conversational AI into a full-stack agent development platform. From Vertex AI Agent Builder for enterprise deployments to the open-source Agent Development Kit (ADK) for code-first control, developers now have multiple paths to build agents with Google that reason, plan, and act autonomously.
Still, production deployments of Gemini come up short for enterprise users. Gemini agents can search the web, execute code, and call APIs, but can’t access the most important enterprise knowledge living in systems like Salesforce, SAP, Oracle, and Snowflake. Without live access to this data, agents can’t produce informed answers, security teams block rollouts, and user AI adoption drops.
CData Connect AI is the managed Model Context Protocol (MCP) platform that connects Gemini agents to 350+ enterprise systems in real time. With Connect AI, your agents start to reason over live business context, inherit existing source system permissions, and take action on real data through a single governed endpoint that works across your entire AI stack.
The barrier: governed data access at scale
Google AI Studio makes it easy to prototype. ADK gives developers precise control. Vertex AI Agent Engine handles production scale. But across the Google Gemini ecosystem, the same challenge persists: agents need trusted access to data, and security teams need governance they can approve and control.
Most enterprises hit one of these walls when building out AI with Gemini:
Shadow IT risk: Users spin up individual connectors without IT oversight, creating credential sprawl and audit gaps
Warehouse latency: ETL pipelines introduce hours or days of delay, so agents reason over stale data and make outdated recommendations
Connector sprawl: Each new agent use case requires another point-to-point integration, multiplying maintenance overhead
Connect AI addresses these challenges by providing one governed layer that works across all your Gemini deployments and any other AI platform in your stack.
How Connect AI works with Gemini
By integrating Connect AI, Gemini agents can:
Query live, governed data from Salesforce, Snowflake, NetSuite, ServiceNow, and 350+ additional sources. Every request respects source system permissions at runtime, not connection time.
Use 8 efficient MCP tools instead of thousands. Connect AI's efficient toolset reduces token consumption 20–60% compared to endpoint-specific implementations. Fewer tools means faster agent reasoning, lower costs, and no decision paralysis.
Execute cross-system queries in a single statement. When an agent needs to correlate opportunities in Salesforce with usage data in Snowflake and support tickets in Zendesk, Connect AI federates the query without sequential API calls or manual data stitching with AI reasoning.
Write back to source systems with the same governance that controls reads. Agents can create records, update fields, and trigger workflows in production systems, with every action logged and permission-checked.
Work across your entire AI stack. The same MCP endpoint that powers your Gemini agents works with Copilot Studio, Claude, ChatGPT, n8n, and open-source models. When you add AI platforms or switch providers, you don't rebuild integrations.
AI can access data, introduce sync latency, and only support read operations. Connect AI queries production systems in place so agents always see current data and can write back to source systems. No pipelines, no stale snapshots, no duplicate infrastructure.
Enterprise governance built in
Security teams typically block AI deployments over three concerns. Connect AI addresses each directly.
Credential exposure: Connect AI uses passthrough authentication. Agent queries inherit the end user's identity and permissions via OAuth/SAML with no shared service accounts and no credential sprawl. Source system RBAC is enforced dynamically at runtime.
Audit gaps: Every query is logged with full attribution, including user identity, query text, systems accessed, data returned, and timestamp. Logs export to your SIEM for compliance reporting and incident response.
Scope creep: Workspace isolation ensures agents only access authorized systems. Your finance agent sees finance data; your sales agent sees CRM. Purpose-built tools can combine specific operations with built-in access limits for additional control.
A smarter Gemini agent in action
Consider a customer health monitoring agent built with ADK and deployed to Vertex AI Agent Engine.
Trigger: An account manager asks, "How is Acme Corp doing?"
Plan: The Gemini agent breaks the question into sub-tasks: check recent opportunities, review support ticket trends, analyze product usage, and identify contract renewal dates.
Query: Connect AI fetches live data from Salesforce (opportunities and contacts), Zendesk (support history), Snowflake (usage analytics), and NetSuite (billing status) through a single MCP endpoint using 8 universal tools.
Reason: Gemini synthesizes these signals into a unified assessment, identifying that usage dropped 40% last quarter while support tickets doubled. This churn risk wouldn't surface from the CRM alone.
Act: The agent creates a follow-up task in Salesforce, drafts a proactive outreach email, and alerts the customer success team via Slack through governed MCP write operations.
Audit: Every query and write operation is logged in Connect AI's governance layer with full user attribution, providing complete traceability for compliance reviews.
Building across Google's AI ecosystem
Vertex AI Agent Builder + Agent Engine
For enterprise teams deploying production agents, Connect AI extends Vertex AI's native connectors to cover the long tail of enterprise systems containing key business context. Deploy to Agent Engine with confidence that your data access scales alongside your agents, and that the governance layer you built for pilot carries forward to production without rearchitecting.
Agent Development Kit (ADK)
For developers who want code-first control, Connect AI provides MCP standard tools that integrate natively with ADK's modular architecture. Define your agent logic in Python, TypeScript, Java, or Go while Connect AI handles enterprise authentication, query optimization, and write-back operations. Your code stays clean and your data access stays governed.
Google Workspace Studio
For business teams building no-code automations, Connect AI opens the door beyond Workspace Studio's native integrations. Enable agents that pull live inventory from SAP, update pricing in NetSuite, or analyze customer data across systems that business users couldn't previously reach, with the same governance controls IT requires.
Google AI Studio
For rapid prototyping, Connect AI lets you test agent behaviors against real enterprise data before committing to production architecture. Build and iterate in AI Studio's visual interface, then deploy the same MCP endpoint to ADK or Vertex AI without reconfiguring your data layer.
Why this matters for enterprise AI strategy
The AI platform that wins today won't be the only one next year. Sixty-three percent of executives cite platform sprawl as a concern, and enterprises are moving to multi-model strategies that span OpenAI, Anthropic, Google, and open-source options. Connect AI provides an infrastructure solution that goes beyond any single AI vendor.
For architects and IT leaders: Deploy governed agent infrastructure in days instead of months. Avoid 4–6 months of DIY MCP server development. One layer replaces stitching together individual connectors per agent platform, and the same governance carries forward when you add new AI platforms.
For security teams: Approve AI deployments with confidence. Passthrough security eliminates service account sprawl. Complete audit trails enable rapid incident response. Workspace isolation enforces least-privilege by design.
For business stakeholders: Trust AI agents that operate on live, governed data rather than stale exports. Scale intelligent automation to hundreds of use cases while maintaining consistent governance.
Get started with CData Connect AI and Google Gemini
To begin:
Connect your enterprise data sources in CData Connect AI
Configure permission policies and workspace isolation for your use cases
Register your MCP endpoint with ADK, Vertex AI Agent Builder, or Google AI Studio
Build agents that reason and act with live business context
In minutes, your Gemini agents can evolve from conversational prototypes into production-ready systems that understand customers, orders, inventory, and operations across your entire enterprise.
CData Connect AI gives Google's AI ecosystem the semantic intelligence, enterprise governance, and live data access required for production-ready agents that drive value. Start with one use case, prove value, then scale across teams and platforms with the same governed infrastructure.
Start a free trial of CData Connect AI and begin connecting enterprise data to Gemini agents using MCP.
Explore CData Connect AI today
See how Connect AI excels at streamlining business processes for real-time insights.
