When you need an audit
You want to add AI to an existing product
Before anyone touches your codebase, we check whether your data and architecture can actually carry it. The goal is to bolt AI on, not rebuild from scratch.
Your system can't handle the load it's getting
We map what you have today and hand back a short list of changes that make it scale, ranked by impact and effort.
Accuracy is lower than the demo promised
Usually the bug isn't in the model. It's in the data, the evals, or a quiet mismatch between training and production. We find which.
It works, but the bill is absurd
We trace where the spend goes (LLM, infra, retries, idle GPUs) and give you a concrete list of ways to bring it down.
How it works
Scope call
You tell us what you're building or what's broken. We tell you whether an audit makes sense and what it would cost.
Technical review
Data, workflows, infra, cost, security and the model itself, if there is one.
Audit report
Every finding prioritized, scoped and estimated. Something your team can actually plan against.
Engagements that fit the stage you're in
Discovery call
A clear yes/no on whether your AI hypothesis is technically real, from our co-founders.
Ideal for:
- A live business ready to invest in AI
- Non-technical founders or executives who need tech validation
- Teams considering AI and wanting an honest read
AI Audit Package
A full review of your code, data and infrastructure with a written report and a task list with estimates.
Ideal for:
- Accuracy that's stuck below target
- Stalled development or runaway maintenance costs
- Teams about to add AI and wanting to start right
Deliverables:
- Full code, data and infra review
- Reproducible model evaluation
- Data quality assessment
- Scaling recommendations
- Written audit report
Book your scope call
30 minutes with our co-founders. Honest read on whether an audit is the right move.