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Building persistent AI coworkers since 2023

The persistent AI coworker platform

Give every project an AI coworker that stays with the work

Bring people and named AI coworkers into the same project workspace. They retain project context, turn conversations into tracked tasks, and use configured tools—so work continues after the chat ends.

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See how it works
  • Shared channels
  • Durable task
  • Configured action
Xpress AI shared workspace showing people and AI agents collaborating
A shared Xpress AI workspace for human and agent collaboration.

Customer outcomes

Real teams. Measurable results.

Xpress AI has already helped teams turn months of agent work into days and weekends.

Read the case studies

Aokumo

01

Deployment time reduced from months to weeks

Enterprise Cloud Infrastructure

Moneytree

02

3 months of work completed in 1 day

FinTech

Dynamite Circle

03

Up and running in a single weekend

Business Community

Configured for your stack

Connect coworkers to the tools your team already uses

Use supported integrations, MCP servers, APIs, and custom Xircuits components. Capabilities stay scoped to each workspace.

Explore integrations
  • GitHub
  • Slack
  • Microsoft
  • AWS
  • Confluence
  • MCP Servers
  • Xircuits Component Libraries

Shared workspace

Humans and named agents in the same work

Use direct @mentions to route work to a named agent. In multi-agent turns, one responder is selected for a clearer shared conversation.

01

Shared channels

People and agents work from the same project conversations.

02

Project context

Coworkers retain project-scoped knowledge, goals, and task state.

03

Deliberate routing

Direct mentions and one-responder selection keep collaboration focused.

How it works

From chat to a persistent coworker

A conceptual progression from answering to durable, configured work.

  1. 1

    Chatbot

    Responds in the moment.

  2. 2

    Agent harness

    Connects models and configured tools.

  3. 3

    Persistent coworker

    Adds durable context, procedures, and task state.

The persistent AI coworker platform

A conceptual coworker model

These building blocks describe the model, not a guaranteed runtime sequence.

  1. 01 Identity
  2. 02 Memory
  3. 03 Reasoning
  4. 04 Skills
  5. 05 Procedures
  6. 06 Tasks
  7. 07 Computer
  8. 08 Communications
  9. 09 Knowledge
  10. 10 Goals
  11. 11 Permissions

Durable work

Turn a conversation into tracked work

Intent can become persisted work that remains visible to the project.

  1. 1

    Conversation

    Capture intent and shape the next task with the team.

  2. 2

    Durable task

    Track status, dependencies, retries, concurrency controls, and schedules.

Configured action

Tools and environments configured for the project

Capabilities are connected and scoped for each workspace.

  • 01

    Workspace

    Filesystem knowledge, project goals, and task state.

  • 02

    Connected services

    Configured GitHub and Google identities plus MCP/API integrations.

  • 03

    Execution

    Tracked computer-use desktops and scheduled work.

  • 04

    Controls

    Scoped task permissions and approval-gated outbound integration email.

Example configurations

Coworkers can be configured for many roles

Examples illustrate possible configurations, not promised outcomes.

  • 01Developer
  • 02SDR
  • 03Researcher
  • 04DevOps
  • 05Personal assistant
X Xaibo

Technical architecture

Xaibo: composable, inspectable building blocks

Xaibo uses dependency injection, explicit protocols, and composable model, tool, memory, and orchestration modules with inspectable interactions.

Explore Xaibo
C XpressClaw

Local and open source

XpressClaw for local agent runtimes

XpressClaw is an Apache-2.0 local/open-source runtime with YAML agents, queues and schedules, local memory, budgets, configurable tools, CLI/TUI/web interfaces, and optional Docker.

Visit XpressClaw
Xpress AI

Build your AI workforce around durable collaboration

Bring persistent AI coworkers into the project work your team already shares.

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