You assemble a team of AI agents like a real team, without a line of code. You set one measurable goal. batoon turns it into a plan, works through it in parallel waves, and puts every action through the policy gate first.
AI modelsreplaceable
Anthropic · OpenAI · Google · Mistral · open weights
Teams come from templates, from your project defaults or from a suggestion. If the team lacks a capability, the copilot adds a specialist.
Task queue
The goal becomes a plan that understands dependencies. Whatever can run in parallel does.
Context manager
Context budget, compaction and caching keep model costs in check. If one of these fails, the previous behaviour applies again. The run does not break.
Policy engine
Deterministic rules check every tool call. A brand judge also checks against your brand guide, and it can only tighten a verdict.
Conflict resolver
When two efforts claim the same segment or the same budget, batoon decides by your goal hierarchy. Or brings in a human.
Vendor neutrality
Both sides stay replaceable.
Choose the model at runtime
Six providers are available: Anthropic, OpenAI, Google, Mistral, Moonshot and OpenRouter. You choose per role, and a fallback chain covers outages. Bring your own key and you pay only the platform fee. Documented runs exist on Anthropic so far. Proof on a second provider is still open.
Everything connects through open standards
MCP for tools, AG-UI for the interface, OIDC for identity, the Open Knowledge Format for knowledge and the Agent Skills specification for portable capabilities. The connector catalogue lists 21 systems.
Your knowledge stays yours
Strategy, brand voice, decisions, glossary and playbooks live as YAML and Markdown in an open format that knows nothing about batoon. We want to keep you through usefulness, not through switching costs.
Scale through configuration, not code
A declarative bridge translates REST and SQL interfaces into MCP. A new vendor arrives as a YAML file. Curating it with whitelisting and stable tool names is not overhead. It is the product.
Traceability
This is what a decision looks like in the audit trail.
Action
Verdict
Decided by
Reason
audience.build_segment
allow
Policy engine
Segment size within limits · consent checked · stays within the task [E1, E4]
email.draft_campaign
flag
Brand judge
Two claims unsupported by the brand guide, flagged for review [E7]
ads.create_campaign
escalate
Campaign lead → CMO
Single action over the budget cap, escalated and approved there [E9, E11]
Illustration of the data structure, not customer data.
Every reason points to numbered evidence. An argument that points to no source halts the run instead of inventing an explanation.