DEAP: DingTalk’s Enterprise AI Platform – Building Production-Ready AI Agents
DingTalk has launched DEAP (Dingtalk Enterprise AI Platform), a next-generation enterprise AI platform designed to help organizations build, deploy, and manage high-quality AI agents at scale. This comprehensive platform addresses the growing need for secure, controllable, and production-ready AI solutions in business environments.
What is DEAP?
DEAP is an all-in-one enterprise AI platform that provides end-to-end support from foundational model management to intelligent application deployment. The platform connects four core elements—models, data, skills, and applications—creating a complete pipeline for building AI agents that score 90+ in quality metrics with stable performance, reliable logic, and smooth user experience.
Solving Critical Enterprise AI Challenges
DEAP addresses five major pain points organizations face when implementing AI:
- High Development Barriers: Complex business scenarios require specialized AI expertise to build agents
- Data Security Concerns: Enterprise knowledge and operational data have high privacy requirements, creating risks with cloud deployment
- AI Asset Management: Large organizations struggle with hierarchical governance of models, skills, knowledge bases, and agents
- Integration Complexity: Enterprise-grade agents need to connect with internal systems and embed into existing workflows
- Quality Assurance: Building complex applications from scratch has high trial-and-error costs, and lacks professional evaluation systems
Six Core Functional Modules
1. Agent Management: Comprehensive tools for agent development, testing, and full-chain observability analysis
2. Skills Center: Access to 11 official skills, 15 third-party skills (continuously expanding), plus support for custom MCP skills
3. AI Knowledge Management: Centralized management of knowledge sets, evaluation datasets, and training datasets
4. Model Management: Over 33 models available (continuously updating), with support for integrating proprietary models and custom training
5. Operations Center: Data dashboards tracking agent creation volume, activity levels, satisfaction rates, and other key metrics
6. Security & Permissions: Administrator privileges, sensitive word controls, and API-key management ensuring controlled and secure agent operations
Three Key Application Scenarios
Intelligent Perception: Agents can monitor group messages and events 7×24, combining contextual understanding, knowledge retrieval, and deep analysis to autonomously respond and execute operations. Example: Customer service agents providing 100% instant responses to standard queries.
Intelligent Q&A: Integration with DingTalk documents, local enterprise knowledge, and web content supporting knowledge bases of 5,000+ files. Advanced knowledge optimization capabilities including slice editing, parsing strategy modification, and FAQ additions improve accuracy. Example: After-sales maintenance assistant agents.
Intelligent Data Analysis: Multi-dimensional indicator queries and conversational data analysis with low-barrier, self-service insights. Agents can predict future trends and provide optimization recommendations for data-driven operations. Example: Sales data analysis agents.
Why Choose DEAP?
Safe and Controllable: DEAP inherits DingTalk’s organizational structure and permission system for fine-grained access control, unified AI asset management, lossless integration of existing data permissions, and support for local deployment to meet high compliance requirements.
Deeply Integrated: Full awareness of DingTalk product capabilities, embedded in daily collaboration scenarios, supporting deployment across single chat, group chat, and web channels. Integration options include MCP, Response API, and H5 Copilot for cross-system collaboration.
Guaranteed Effectiveness: Support for fine-tuned knowledge and model optimization, with a closed-loop mechanism of “data observation—effect evaluation—iterative optimization” for continuous AI capability improvement.
DEAP represents a significant step forward in making enterprise AI not just accessible, but truly production-ready and governable at scale.