ENTERPRISE AI AGENT PLATFORM

Build enterprise
digital workers with ease.

Connect your knowledge, tools and workflows—with reviewed skills, controlled execution and human approval.

Explore capabilities ↓
Knowledge captureWorkflow orchestrationPrivate deployment
Enterprise knowledgeCapture business experience
Workflow orchestrationBreak down tasks · advance steps
Tool connectionLet AI reach business systems
Enterprise governancePublic or private, always manageable
EXPLORE UAGENTS

From platform capabilities to business outcomes.

Explore real use cases, responsible deployment, and how digital employees can fit your team.

01

Digital employees

Define responsibilities in an employee-specific Agent.md, connect approved knowledge and skills, and keep humans in control of consequential actions.

Explore 02

Solutions

Start with a narrow, auditable workflow. Expand only when accuracy, security, costs and human handoffs are measured.

Explore 03

Integrations

UAgents platform source includes tool and integration surfaces, knowledge services and workflow components. Availability depends on connected services and deployment configuration.

Explore 04

Security

Digital employees should operate within explicit permissions, execution boundaries and human review. UAgents includes related application-level components; deployment controls must be independently validated.

Explore
01 / PLATFORM

Connecting enterprise knowledge, models and workflows.

UAgents is an enterprise agent platform that unifies knowledge, models, tools and workflows — so business teams can adopt and manage AI reliably.

01

Knowledge becomes business context

Retrieval augmentation lets agents work from your existing documents and processing rules.

02

Workflows carry complex work

Break complex tasks into orchestrated steps so operators follow a clear execution path.

03

Governance scales adoption

Private deployment, multi-tenant organizations and audit logs keep enterprise AI managed.

02 / CAPABILITIES

From knowledge Q&A to business automation.

Six coordinated capabilities across the agent lifecycle, reducing gaps between models, data and tools.

01 / KNOWLEDGE

Knowledge & retrieval augmentation

Parse documents and build retrieval indexes so answers and tasks have full business context.

  • RAG
  • Knowledge graph
02 / MODELS

Model access & scheduling

Unified management of language models, OCR and speech synthesis services.

  • LLM
  • OCR
  • TTS
03 / AGENTS

Agent configuration & building

Configure agents around role responsibilities — with clear knowledge and tool bindings.

  • Role configuration
  • Knowledge & tool binding
04 / WORKFLOWS

Visual workflow orchestration

Break tasks into steps, configure conditions and loops, coordinate multi-agent collaboration.

  • Conditions
  • Loops
  • Collaboration
05 / TOOLS

Tools & business automation

Native tools, MCP and RPA+ connect operations so agents fit into existing workflows.

  • Native
  • MCP
  • RPA+
06 / OPERATIONS

Run monitoring & audit

Runtime logs and resource state help you diagnose issues and iterate on workflows.

  • Execution trace
  • Resource monitor
  • Logs
SKILLS / AGENT.MD

Skills that evolve through review

Draft → human review → published snapshot → execution. Editing a draft never changes the published skill.

Create through conversation

The built-in skill-creator drafts instructions, scripts and sandbox settings. A human must approve before draft scripts become executable.

Publish deliberately

Skills contain SKILL.md, scripts and reference files. The database is the source of truth; execution uses the published snapshot. GitHub sync updates drafts.

Use personal credentials

Each user supplies the variables declared by a skill’s .env.example. Values are injected per execution and are not returned by endpoints, including admin endpoints.

Isolate executable skills

uagent-service manages Docker sandboxes with a read-only filesystem, non-root user, dropped capabilities and CPU/memory limits. Network access must be declared.

Clear instructions for every digital employee.

Define each digital employee’s role, responsibilities and working guidelines in its Agent.md, directly on the employee’s page. Keep its system prompt in one place so instructions are easy to review and maintain.

MCP and native tools have different lifecycles

MCP servers are registered and managed in the platform. Native tools ship with the code and are authorized there; they do not need a separate binding step.

04 / HOW IT WORKS

One business task, connecting the whole platform.

A supply-chain document review illustrates how knowledge, models, workflows and tools work together. Reference design shown.

From the business problem
  1. 01
    Collect task materialsSupply documents and requirements to define processing scope.
  2. 02
    Augment with knowledgeRetrieve policies and rules to back the review.
  3. 03
    Execute review stepsCombine models and tools to check each field.
  4. 04
    Output a review draftProduce a discrepancy list for a human to confirm.
Supported by the platform
  1. A
    Knowledge matchingRetrieval supplies context; models parse and extract information.
  2. B
    Workflow coordinationOrchestrated steps and branches link inputs to outputs.
  3. C
    Tools & systemsChosen native tools reach the actual business operations.
  4. D
    Records & iterationExecution traces and runtime logs surface issues to iterate on.
05 / DELIVERY

Start with one scenario, expand to the team.

Organize the resources a business goal needs, then validate workflow, environment and adoption.

Connect knowledgeAssemble the documents and knowledge scope
Configure agentsBind roles, models and tools
Orchestrate workflowsDefine steps and business rules
Run and iterateTrace execution, refine outcomes

Pace the rollout by business complexity.

01 / SCOPING

Identify the problem

Clarify task boundaries, inputs, outputs and acceptance criteria; pick a first scenario worth prioritizing.

02 / PROTOTYPE

Validate with real business

Test retrieval, workflow execution and tool support against real samples; find what to improve.

03 / ROLLOUT

Run in the enterprise

Configure permissions by org structure, complete deployment and training, then expand adoption.

06 / GOVERNANCE

Designed for enterprise environments and long-term operation.

Private deployment & operations

  • Private deploymentRuns inside the environment your enterprise chooses.
  • Container deliveryShips with Docker and adapts to the target environment.
  • Monitor & auditResource state and runtime logs for traceability and change sync.

From org structure to resource boundaries

  • Multi-userOrganize accounts and their resources
  • Multi-departmentModel your enterprise structure
  • Tiered sharingConfigure resource scope by permission
  • Runtime recordsTrace task and tool execution

Choose the complete data boundary

Private web hosting does not automatically keep model, OCR, speech or tool processing on-premises. Validate every dependency.

Choose the complete data boundary
ConfigurationProcessingVerify before deployment
Hosted servicesSelected cloud application and AI servicesProvider locations, retention and access controls
Private application + external modelsApplication is private; selected model requests leave the networkRedaction, credentials and approved destinations
Private application + local modelsCan remain local when all dependencies and outbound traffic are controlledHardware, model quality, embeddings, tools and telemetry
08 / USE CASES

One platform, serving different business tasks.

Start with verifiable tasks covering knowledge, workflow and tools. Reference directions shown.

MANUFACTURING & OPERATIONS

Equipment knowledge

Put repair experience to work

Turn equipment manuals and repair logs into a searchable reference for on-site engineers.

RETAIL & SUPPLY CHAIN

Document review

Turn repetitive checks into a workflow

Extract document fields, compare against business rules and produce a review draft for operators.

INTERNAL SERVICES

Knowledge assistant

Make business knowledge easier to reach

Aggregate policies, product and service materials to support daily inquiries across teams.

Beyond the chat window

Digital employees & automation

Build, configure, publish and embed agents. Schedule runs or trigger them from incoming email.

Knowledge & workflows

Upload documents, build vector indexes and manage access. Use streaming RAG Q&A and visual multi-step workflows.

Business processes & documents

Organize process trees, review and revise documents, and generate handbooks. Preview Office files with kkFileView and edit with OnlyOffice.

Identity & organization

Multi-tenant organizations and RBAC. Optional OIDC, phone registration with configured backend/SMS provider, and session renewal.

Credits & monitoring

Allocate tenant credits to individuals and view balances, usage and license status.

Attachments & languages

Use image attachments with capable models and revisit files and PDF previews in conversations. Platform languages: English and Simplified Chinese; website languages are configured separately.

Illustrative simulation · synthetic data · no AI or external system connected

Follow an invoice through review

A small example of an exception workflow. This is not a live runtime demonstration.

Invoice INV-DEMO-01: USD 1,250

Purchase order PO-DEMO-01: USD 1,000

Rule: a mismatched total requires human review.

Ready to review the sample.

Prove one workflow before expanding

Agree acceptance criteria using representative, permission-cleared data. Pricing depends on deployment, integrations and support; request a scoped proposal.

  1. Compare against the manual baseline.
  2. Measure correct completions, missed exceptions and review effort.
  3. Track latency and full cost per completed task.
  4. Test permission boundaries and failure recovery before release.

Before you deploy

Can I update a live skill immediately by chatting?

Conversation creates or updates a draft. Published snapshots remain unchanged until human review and publication. The built-in skill-creator is code-versioned and cannot be edited or deleted through the platform.

Is the platform accuracy independently benchmarked?

No independent accuracy benchmark is presented on this website. Request a task-specific evaluation dataset, sample size, date range and calculation method before relying on performance figures.

Can UAgents run on private infrastructure?

The platform supports a configurable service topology. Private application hosting does not by itself guarantee that model inference, document processing or connected services remain private. Review the complete data flow first.

Does the website demo operate a real AI agent?

No. The invoice walkthrough is a clearly labeled local simulation. Request a deployment-specific walkthrough for live agent execution.

Do you offer API and MCP integration?

The platform source contains API and tool integration surfaces. Supported contracts and runtime integrations depend on the installed backend and configuration.

How is pricing determined?

Pilot and deployment proposals depend on workflow scope, infrastructure, model usage, integrations and support requirements.

BUILD WITH UAGENTS

Start building your first digital worker — here.

Bring one business question — we’ll map the knowledge, workflow and tools it needs.

Learn the platformExplore capabilities and discuss directions
Book a demoSee the workflow with your use case
Discuss deploymentAssess environment and integration scope
Visit umamimind.ai