CData Connect AI: Managed MCP Platform for Enterprise Databricks Agents

**Overview** **Connect your Databricks Agent Bricks to 350+ enterprise data sources through CData's fully managed MCP (Model Context Protocol) server. Our platform enables AI agents to seamlessly read, write, and act on live data from systems like Salesforce, Snowflake, NetSuite, SAP, and Microsoft Dynamics without complex integrations or data duplication. With built-in semantic intelligence that understands metadata and relationships across your entire data ecosystem, CData Connect AI empowers your agents to perform sophisticated multi-source analysis while maintaining enterprise-grade security and governance.** **Use cases** **Intelligent Data Orchestration** - Enable AI agents to autonomously query multiple systems, join data across platforms, and execute complex workflows spanning CRM, ERP, data warehouse, and operational databases in real-time **Autonomous Workflow Automation** - Empower AI agents with governed read, write, update, and delete capabilities across enabled connected systems through MCP, enabling them to autonomously execute end-to-end business processes like updating Salesforce opportunities based on NetSuite orders, creating support tickets from customer emails, synchronizing inventory across platforms, or triggering approval workflows based on live data updates **Automated Business Intelligence** - Deploy agents that generate cross-system reports, identify trends across siloed data sources, and proactively surface insights from unified enterprise data **Conversational Analytics** - Build natural language interfaces that users can query and analyze data from any combination of your 350+ supported sources without pre-built integrations **Product details** - **Datasets represented include**: **CRM Objects** (Accounts, Contacts, Opportunities, Cases, Campaigns) **ERP Entities** (Orders, Invoices, Inventory, Vendors, GL_Entries) **Analytics Tables** (Metrics, Dimensions, Aggregations, Time_Series) **Operational Data** (Tickets, Projects, Tasks, Users, Transactions) - **Sample fields include**: **Record identifiers** (id, external_id, created_date, modified_date) **Business attributes** (name, status, type, category, priority) **Relationship mappings** (account_id, owner_id, parent_id) **Metrics and measures** (amount, quantity, score, percentage) **Metadata fields** (source_system, last_sync, data_quality_score) **Additional Insights** **Real-time data accessed in-place** - Query live data directly from source systems without replication or data pipelines **Semantic data intelligence preserved data context**– Natural understanding for AI of data relationships, attributes, and business context across every connector **Enterprise governance and security** – Inherited user permissions, row-level security, OAuth/SSO support, and complete audit trails for compliance **Start in minutes** - Connect any supported data source in minutes with no-code configuration, no deployments or installs needed

搜集汇总

背景与挑战

背景概述

该数据集通过CData Connect AI平台提供对350多种企业数据源的实时访问，支持AI代理进行多源数据分析和智能工作流自动化，同时确保企业级安全治理。平台具备语义智能理解能力，可快速配置连接各类业务系统。