The agents off-the-shelf
tools can’t build, shipped
to production.
Production-grade AI agents, eval-proven, governed, and sandboxed before they ever touch your data.
Anyone can demo an agent,
almost no one can keep one running.
The last 5% of reliability is harder than the first 95%. Agents that dazzle in a demo break on real inputs, hallucinate quietly, drift over time, and open brand-new attack surfaces — prompt injection, tool poisoning, credential abuse.
Gartner, 2026
>40%
Enterprises will pull autonomous agents back out of production by 2027.
Gartner, 2025
>40%
Agentic-AI projects will be scrapped by end of 2027, on cost, unclear value, or weak risk controls.
Gartner
~25%
Enterprise breaches will trace back to AI-agent abuse by 2028.
The pattern is clear, agents don’t fail on capability, they fail on reliability, cost, and control. So that’s what we engineer in from the first commit.
Book a working sessionA build pipeline,
not a prompt and a prayer.
A named roster of specialised agents builds against a horizontal core, accelerated by a 100+ workflow template library.
Architect
Design against the horizontal core.
Build
Designer + Coder generate, executed sandboxed.
Eval
Scored against ground truth before ship.
Deploy
Into your stack, with an audit trail.
We prove it works before it ships, not after.
A QA agent and eval harnesses score every agent on reliability, tool-call accuracy, and tail-latency against ground-truth data — before it goes live. You get numbers, not a vibe.
Nothing ships unproven — failing builds bounce back.
Built to survive the security review.
Every agent runs inside a VM sandbox — no host filesystem, no host network, which is what lets an agent run code safely at all. Access is governed by a Capability Lease: a signed, capability-scoped credential envelope issued per call, deny-by-default, behind agent firewalls.
Sealed in a VM — one scoped lease, behind an agent firewall.
Governance baked into the build not bolted on after an incident.
Governance invariants are part of the architecture, not a separate GRC tool: policy gates with no bypass, human approval for consequential actions, and an append-only, replayable ledger that makes every decision traceable and audit-ready.
Gates in the path — not bolted on after.
Deployed into your stack,
not rip-and-replace.
Multi-tenant deployment. The operating surface is a set of Claude skills and plugins plus a human review console, wired to your systems via API and MCP across 10+ external services, each with an audit trail.
Production-grade and proven.
One mid-market enterprise went from spec to a governed, in-production agent, eval-passed and security-reviewed, in six weeks.
40+
Production agents shipped.
99.9%
Production uptime.
100+
Workflow templates.
3–5 days
Approved PRD to deployed agent.
Questions, answered.
Can't find what you're looking for? Talk to our team.
Eval harnesses gate reliability and tool-call accuracy before ship; confidence is reported as a range; a Skeptic agent challenges consequential decisions; and humans approve the high-stakes ones.
Bring us the workflow you don’t trust to AI yet.