Knowledge becomes business context
Retrieval augmentation lets agents work from your existing documents and processing rules.
Connect enterprise knowledge, models and business workflows — turn everyday work into runnable, manageable AI agents.
UAgents is an enterprise agent platform that unifies knowledge, models, tools and workflows — so business teams can adopt and manage AI reliably.
Retrieval augmentation lets agents work from your existing documents and processing rules.
Break complex tasks into orchestrated steps so operators follow a clear execution path.
Private deployment, multi-tenant organizations and audit logs keep enterprise AI managed.
Six coordinated capabilities across the agent lifecycle, reducing gaps between models, data and tools.
Parse documents and build retrieval indexes so answers and tasks have full business context.
Unified management of language models, OCR and speech synthesis services.
Configure agents around role responsibilities — with clear knowledge and tool bindings.
Break tasks into steps, configure conditions and loops, coordinate multi-agent collaboration.
Native tools, MCP and RPA+ connect operations so agents fit into existing workflows.
Runtime logs and resource state help you diagnose issues and iterate on workflows.
A digital worker = role + skills + tools + memory. Role defines "who," memory keeps "what happened"; skills and tools decide "what it can do" — and both can be created or updated in one sentence of natural language.
Describe the goal in one line — the platform matches tools and knowledge, generates a skill and attaches it to the role.
When rules or scenarios change, just tell the platform. No rebuild — skills are team assets, created once and shared.
MCP, RPA+ and Native adapters let skills actually reach business systems.
A supply-chain document review illustrates how knowledge, models, workflows and tools work together. Reference design shown.
Organize the resources a business goal needs, then validate workflow, environment and adoption.
Clarify task boundaries, inputs, outputs and acceptance criteria; pick a first scenario worth prioritizing.
Test retrieval, workflow execution and tool support against real samples; find what to improve.
Configure permissions by org structure, complete deployment and training, then expand adoption.
Codex is a coding agent for engineers; WorkBuddy is a personal desktop agent; UAgents is an enterprise agent hub — they serve different layers.
| Dimension | Codex | WorkBuddy | UAgents |
|---|---|---|---|
| Deployment | Engineer laptop / OpenAI cloud sandbox | Personal computer | Enterprise server (private deployment) |
| Data boundary | Code uploaded to cloud; needs relay in China | Data scattered across personal machines | Data, knowledge and credentials stay on-prem |
| Permissions | Single user | Single user | Tenant / department / role three-tier RBAC |
| Knowledge source | Code repositories | Local files + web pages | Enterprise knowledge base + business systems |
| Deliverable | One task = one PR | One task = one document | A resident digital worker |
| Who governs | Developers themselves | Users themselves | IT / admins, centrally |
| When people leave | Capability leaves with them | Capability leaves with them | Capability stays with the company |
Start with verifiable tasks covering knowledge, workflow and tools. Reference directions shown.
Turn equipment manuals and repair logs into a searchable reference for on-site engineers.
Extract document fields, compare against business rules and produce a review draft for operators.
Aggregate policies, product and service materials to support daily inquiries across teams.
Bring one business question — we’ll map the knowledge, workflow and tools it needs.