Products
We took our own advice.
Every product here started as one specific workflow that was measurably leaking time — not as a platform looking for a use case. That is step M of the method, applied to ourselves.
They share a spine: your own model key, hard tenant isolation, append-only audit records, and honest degradation when a dependency is missing. Governance is a build requirement, not a roadmap item.
Desk
AvailableThe AI-native service desk
Resolves routine tickets end to end, escalates the rest to a human with full context, and proves the deflection rate with analytics your finance team can audit.
- Auto-resolve policy you control
- SLA engine with business hours
- Knowledge base that fills its own gaps
Command
AvailableThe control tower for AI at work
Orchestration, approvals, guardrails and ROI reporting for every AI agent you run — so a working pilot doesn't spend six months waiting for someone to approve it.
- Fleet dashboard
- Approvals and guardrails
- Multi-agent workflows
Guided UAT
Available · WorkdayUser acceptance testing that doesn't collapse
Consultants curate a versioned test library; client testers execute it one step at a time, guided by an agent that knows the tenant design, the personas and the known failure modes.
- Grounded by construction
- Immutable library versions
- Diagnosis against known failure modes
Katie
Early accessA strategy analyst on call
Pose a business question and get back a structured consulting memo — executive summary, key findings, recommendation, risks — inside the same governed run envelope as every other agent you operate.
- Structured memo, every time
- Governed like any other agent
- Triggered from real work
The through-line
Governed by construction, not by policy document.
- Your model, your key
- Bring your own API key with a per-tenant model allow-list enforced on the server. Usage is metered and visible.
- Records that survive an audit
- Audit logs and billing ledgers are append-only, with UPDATE and DELETE blocked at the database. Corrections post a compensating entry rather than rewriting history.
- The model never decides alone
- Deterministic code handles lifecycle, validation and results. The model handles judgement, explanation and drafting — with a human on the consequential calls.
- Degrades honestly
- Lose a model key and the product falls back to its manual path rather than going down. Health endpoints report ok, degraded or unhealthy — not a green light either way.
Next step
See one running against your own data.
We will walk you through the product that fits the workflow you are actually trying to fix — and tell you plainly if none of them do.