Understand First.
Build Second.
Ship What Lasts.
Every engagement follows the same disciplined process — find the opportunity, re-engineer the process, build and tune the system, then compound it. Cutting corners early is how AI projects become shelfware.
Discover
We embed with your team for 1-2 weeks. We observe workflows, interview operators, walk the floor, sit in planning meetings, and follow the exceptions. The output is a complete operational map — not a slide deck, but a working document that captures how decisions actually get made, where things break, and where the real opportunities are.
Deliverables
Design
We identify where agents can reduce friction, compress decision cycles, or handle work that doesn't need a person. Then we design the system logic, data flows, integration points, and human-in-the-loop checkpoints — all before writing a single line of code. Some workflows should be improved before automation; we help clean up the process so the agent inherits a good system.
Deliverables
Build
We build production-grade software: tested, observable, version-controlled, and designed to degrade gracefully when something unexpected happens. You'll see the system before it goes live — and you'll understand what it's doing and why. Every agent ships with a full eval suite, monitoring, and rollback capability.
Deliverables
Run & Improve
We monitor performance, tune decision logic, and stay engaged as your operations evolve. Decisions become data. Data strengthens logic. The cycle repeats. The system gets better the longer it runs — and we help you expand to new workflows as the first ones prove out.
Deliverables
Decisions Become Data. Data Strengthens Logic. The Cycle Compounds.
We build a mesh of specialized agents — each handling routine decisions in its domain, feeding outcomes back as signals that improve the next decision.
Signal
Live data from your ERP, MES, WMS, sensors, and team inputs flows in continuously.
Policy
Business rules, playbooks, and institutional knowledge — encoded, visible, and improvable.
Action
Agents execute within boundaries, route exceptions to humans, and feed outcomes back as new signals.
The Difference Between a Demo and Production
Eval Suites
Every agent ships with quantitative evaluation — regression tests, accuracy benchmarks, and failure-mode coverage before anything touches production.
Version Control
Prompt versions, model configs, tool definitions, and guardrails all tracked. Rollback in minutes, not days. Full audit trail for every change.
Security & Access
Role-based access, scoped credentials, input validation, and output filtering. Agents only see and do what they're authorized to.
Observability
Structured logging, trace IDs, latency tracking, cost monitoring, and drift detection. You see exactly what your agents are doing and why.
Continuous Tuning
Production data drives improvement. We monitor, adjust decision logic, and expand scope based on what actually works — not assumptions.
Human-in-the-Loop
Configurable approval gates, escalation paths, and override controls. Agents augment your team — they don't replace judgment.
We've Thought About What Worries You
Our data is messy
So is everyone's. We work with Epicor, Infor, Visual, legacy systems, and decades of accumulated data. We build for messy, not clean.
Our team won't use it
We involve operators during discovery. The system reflects how they actually work. Adoption is designed in from day one.
What if it breaks
Monitoring, alerting, and human override on every agent. Your team can intervene at any point. We're there for the first months of production.
We need on-prem
No problem. On-prem, private cloud, or hybrid. Your data stays where your compliance team needs it.
What happens when you leave
Full documentation, operator runbooks, and knowledge transfer. The system is yours. We stay for ongoing tuning if you want.
We've been burned before
So have we — from the inside. That's why we built this company differently. No 18-month timelines. No vaporware. Production in weeks.
A First Engagement Built to De-Risk the Decision
You shouldn't have to bet the operation to find out if this works. The first engagement is tightly scoped, fixed in timeline, and validated against your real data before anything goes live.
Scoped & fixed
A tightly scoped first workflow with a clear timeline and deliverables — no open-ended commitment.
See it before go-live
You review the system against your real data before it touches production. No surprises.
Eval-validated
Nothing ships without quantitative accuracy benchmarks, regression tests, and failure-mode coverage.
Reversible by design
Version-controlled configs with rollback in minutes, human override on every agent, and full audit trail.
Ready to Start?
Tell us about your operation. We'll give you an honest read on where AI changes the economics.