We build AI systems you can trust in production.
Production-grade AI workflows for organizations that can't afford hallucinations, outages, or accidental commitments.
Most AI projects fail after the demo.
We design and build AI systems that survive real data, real users, and real consequences.
Who this is for
This is for teams who:
- Already have real operations
- Deal with documents, decisions, or workflows at scale
- Know AI could help — but know a mistake would be costly
- Need automation with control, auditability, and guardrails
If you're looking for a quick prototype or a pitch-deck demo, we're not a fit.
The problem we solve
Most AI systems fail in predictable ways:
- They hallucinate and no one notices until it's too late
- They make implicit promises that turn into disputes
- They break when real data shows up
- They become impossible to debug or audit
- They cost more than expected once usage grows
These aren't model problems.
They're system design problems.
What we actually build
We design and implement AI workflow platforms, not one-off features.
That means:
- AI systems with explicit steps, state, and decision points
- Human-in-the-loop controls where judgment matters
- Secure document ingestion and processing
- Model orchestration with cost and failure controls
- Full auditability of what the AI saw, decided, and produced
- Infrastructure that can be paused, inspected, or rolled back
In plain terms
Your AI doesn't "just run."
It executes inside a system designed not to surprise you.
How this is different
Many AI vendors
- Chain prompts together
- Rely on best-case assumptions
- Optimize for demos
We design for
- Worst-case inputs
- Real users behaving unpredictably
- Long-term operation, not novelty
Our background is in building systems that have to keep working — not experiments.
Engagement model
We work with a small number of clients at a time.
Typical engagements begin with the co-design and implementation of a production AI workflow system, tailored to real operational constraints.
This means:
- A proven execution engine is already in place
- Workflows are shaped against your real data, users, and edge cases
- Guardrails, checkpoints, and failure modes are defined explicitly
- The system is hardened through exposure to reality — deliberately, not accidentally
We stay involved to evolve workflows, manage risk, and prevent drift as usage grows.
This is not staff augmentation.
This is not hourly development.
We take responsibility for the system.
What early clients should expect
Early engagements are collaborative by design.
The core architecture and execution engine are already established, but each system is intentionally refined against real-world constraints: actual data, real users, and real failure modes.
This approach prioritizes correctness and durability over speed or novelty — and is how systems meant to operate in production are responsibly built.
What we don't do
We don't:
- Sell prompts
- Ship fragile agents
- Promise "AI transformation"
- Build systems we wouldn't trust ourselves
If something shouldn't be automated, we'll tell you.
Start a conversation
If you're considering AI for a system where mistakes matter, we should talk before you commit to the wrong architecture.