A multi-agent orchestration platform that lets an organization deploy, govern, and scale AI agents across teams and channels — with role-based control, audited execution, and a live view of every run.
The network wanted AI agents doing real work across many teams and sub-accounts. Off-the-shelf bots had no concept of an organization, no governance, and no record of what they did.
Agents needed roles, scoped tools, and escalation policies — the same structure as staff.
Every run needed a step-by-step trace, a delegation tree, and a cost attached to it.
Delegation needed approval gates and routing rules, not a free-for-all.
Org → sub-account → team → user, with role-based access and a seat registry defining each agent's responsibility, authority, tools, and escalation path.
Each run is traceable, replayable, schema-validated, and time-boxed — with the cost of every step recorded.
Slack, Telegram, Discord, WhatsApp, and voice, backed by shared memory and an organization-wide knowledgebase.
Org, sub-account, team, and user hierarchy with role-based access, data isolation, seat templates, and sub-account-scoped tools.
Orchestrator, worker, reviewer, and scheduled agents. Inter-agent delegation with approval workflows, and self-improvement proposals gated by a human.
State-machine runs with live steps, pinned replay, tool schema validation, timeouts, a stale-run reaper, and per-step cost tracking.
Persistent memory with semantic search, auto-summaries, an org knowledgebase, a linked knowledge graph, and a fact-checking pipeline that flags contradictions.
A visual, n8n-style builder with triggers, steps, gates, and routers — plus concurrency guards, resume, retry, and test-step APIs.
Four messaging platforms with image understanding, proactive scheduled messaging, ambient monitoring, and a per-agent voice mode.
Roles, scopes, and escalation for every agent.
Every step, every cost, every handoff visible.
New agent, new seat, new channel — without new risk.
The network can stand up a new AI agent, give it a seat, scope its tools, and put it on a channel — then watch it work, step by step, with the cost of every run in front of them. Agents coordinate with each other under human approval instead of running loose.
It’s the difference between “we tried AI” and “we run AI.”
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