Simple interface with enterprise-grade agentic kernels
A governed capability runtime across your systems of record — one governed exit for every action, not a chatbot bolted on top.
Reliable agents at scale. Knowledge that compounds.
The architecture is built for two outcomes: agents your enterprise can trust with real work — every action governed, approved, and on the record — and a memory layer that turns every reviewed run into enterprise-wide knowledge, an intellectual asset that compounds over time.
Traces, health, cost, and performance for every run; telemetry never replaces audit evidence.
Wraps every layer — nothing runs outside it.
Runs leave data. Review builds knowledge. Plans borrow wisdom.
Memory is organized as a DIKW ladder — data, information, knowledge, wisdom. Every governed run leaves evidence at the bottom, review promotes it upward tier by tier, and at plan time retrieval hands the harness the relevant slice of every tier, each item with provenance.
One plan by default. A team only when it pays.
WorkOS is a governed capability runtime: the harness plans, the capability kernel executes. Planner–executor is the default for predictable, auditable runs; orchestrator–worker steps in only when decomposition genuinely adds value — so a simple request never turns into a multi-agent swarm burning tokens.
One bounded plan on one governed path — no coordination overhead.
The planner brings in an orchestrator only when the job truly decomposes — parallel domain workers, one governed exit.
Reviewed outcomes make future work better.
The governed runtime records what happened. Memory accepts reviewed facts, corrections, and learning candidates, then returns sharper context for future work.
Produces structured evidence of what ran, what stalled, and where a human intervened.
Promotes reviewed outcomes into reusable context, guidance, and playbook candidates.
Completed work leaves structured run evidence — never reconstructed from memory.
People accept, correct, or reject proposed improvements before they become reusable guidance — enforced rules ship only through a versioned policy change.
Approvals and corrections become signal — folded back into the playbook.
AI runs the work. You make the calls.
One request, end to end: the harness plans, the kernel executes. Inspect at any time — pause, approve, cancel, or take ownership at safe persisted checkpoints.
Instructions in Layman's terms.
40 invoices chased, 2 signed off by your credit manager — effects reconciled, every step on the record, and the run filed as a reviewed learning candidate.