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A-Team

The AI Application Platform

Describe the outcome.
A-Team builds the system.

Create complete AI applications with skills, connectors, governance, runtime, and UI. Run them with OpenAI, Anthropic, Ollama, SGLang, or compatible models—in A-Team Cloud or your own environment.

Model-independentManaged or self-hostedGoverned runtime
a-team · build

$ a-team build

> Build a customer support operation that can answer policy questions, inspect orders, issue refunds under €100, and escalate exceptions.

  1. Parsing the outcomeIdentifying goals, actions, and boundaries from the description.
  2. Creating skills
  3. Connecting systems
  4. Applying guardrails
  5. Validating topology
  6. Deploying
  7. Test trace passed
step 1 / 7

An agent is a component.
Your business needs a system.

A-Team combines specialized skills, real tools, policies, routing, memory, interfaces, deployment, and operations into one application model.

skill

Agent

One capability

skill

Skills

Specialized roles

connector

Connectors

Tools & data

policy

Policies

Guardrails & routing

ui

Interfaces

Generated UI

Built on A-Team

Meet Ada Mind—the platform working as a product.

Ada Mind is a mobile personal assistant that demonstrates A-Team across everyday domains: email, WhatsApp, documents, nutrition, travel, memory, voice, proactive notifications, and mobile-native actions.

Holds long-term memory across conversations and domains.

Lifecycle

From description to running system.

01

Describe

Outcome and boundaries

goals, constraints, approval limits

02

Generate

Solutions, skills, connectors, policies, UI

the complete application model

03

Validate

Contracts, access, handoffs, quality

topology and permission checks

04

Deploy

Managed runtime and integrations

cloud or self-hosted target

05

Operate

Logs, metrics, tests, versions, rollback

production operations

Your intelligence layer

Choose the model. Change it tomorrow.

A-Team separates the application from the model provider. Use OpenAI or Anthropic APIs, connect Ollama, run SGLang against self-hosted models, or assign different models to different workloads.

  • Mix models by skill or workload
  • Keep private inference inside your network
  • Avoid rewriting application logic during model changes
  • Optimize cost, latency, privacy, and capability independently

Application layer

Skills · Connectors · Policies · UI

OpenAI
Anthropic
Ollama
SGLang

The application stays fixed while model endpoints change beneath it.

Your environment

Use our cloud—or install the platform in yours.

Launch quickly with A-Team Cloud or deploy a self-hosted instance into your own environment through the supported one-click installation path.

A-Team Cloud

Launch quickly on the managed runtime.

Private cloud

Deploy a self-hosted instance in your own cloud account.

On-premises

Install the platform inside your own datacenter.

Restricted networks

Verifying

Operate inside isolated or restricted network environments.

Platform architecture

Everything a complete AI application needs.

  • 1

    Experiences

    Mobile, web, voice, chat, generated widgets

  • 2

    Solutions

    Complete business applications

  • 3

    Skills

    Specialized operational roles

  • 4

    Connectors

    Tools, APIs, systems, data

  • 5

    Governance

    Permissions, approvals, grants, handoffs

  • 6

    Runtime

    Execution, state, memory, routing

  • 7

    Operations

    Tests, logs, metrics, health, Git, releases

  • 8

    Infrastructure

    Cloud or self-hosted, hosted or private models

Operations

Treat AI systems like production software.

Test skills, inspect decision pipelines, trace tool calls, compare definitions with deployed state, analyze bottlenecks, version changes, and roll back safely.

Healthyv2.4.1 · deployedp95 630ms

Execution trace

  • Support skillknowledge.search120ms
  • Order skillcommerce.getOrder240ms
  • Refund skillcommerce.refund180ms
  • Escalationemail.send90ms
Definition matches deployed state

Solutions

What teams build on A-Team.

Customer Support Operations

Answers questions, accesses customer and order systems, performs bounded actions, and escalates exceptions.

Systems connected
Knowledge, Commerce, CRM, Email
Control model
Refund limits and approval on exceptions

Operational Command Center

Monitors live operations, coordinates specialized roles, and executes approved workflows across systems.

Systems connected
Telemetry, Ticketing, Runbooks, Comms
Control model
Role scoping and approved-action gates

Personal AI Companion

Combines long-term context, mobile capabilities, communication, documents, and proactive assistance.

Systems connected
Email, Messaging, Documents, Calendar
Control model
User consent and per-capability grants

Developer experience

Give your AI assistant the hands to build on A-Team.

Connect through A-Team MCP. The assistant can learn the platform specification, study examples, define the solution, validate it, deploy it, test it, inspect logs, and make controlled updates.

a-team · mcp
  1. $Connect MCP
  2. Describe the system
  3. Review architecture
  4. Deploy
  5. Test and improve

Build the application—not the agent stack.

Start with A-Team MCP, explore Ada Mind, or discuss a self-hosted deployment.