AI
Real AI wired into the workflows — with evaluation, guardrails, and a fallback when the model is wrong.
What it looks like
How an answer is actually produced
- 01Ingestyour documents
- 02Retrievescoped to the user
- 03Draftmodel + your context
- 04Checkconfidence threshold
- 05Reviewa person signs off
What's included
Everything we cover
One engagement, one team. Take the whole service or the part you need today.
Workflow audit
Finding the work that is repetitive, high-volume, and tolerant of review — before writing a single prompt.
- Candidate workflow shortlist
- Value and risk assessment
- Build-versus-buy recommendation
Model integration
The model doing one narrow job inside a system that already works, not a demo bolted on the side.
- Schema-validated outputs
- Retrieval and context design
- Deterministic fallback path
Evaluation & guardrails
A held-out set scored on every prompt change, so an improvement in one place cannot quietly break another.
- Evaluation harness
- Prompt versioning
- Accuracy and cost monitoring
Human review
Review placed where being wrong is expensive, and removed where it is not.
- Confidence thresholds
- Review and escalation flow
- Audit trail of decisions
Engagement flow
How an AI engagement runs
We start from the workflow and what it costs you, not from the model.
- STEP 01Workflow audit
Where the time and the error cost actually go.
- STEP 02Shortlist & payback
Two or three candidates, priced and scored.
- STEP 03Pipeline & retrieval
Grounding on your content, with permissions.
- STEP 04Evaluation & guardrails
Regression suites and human review steps.
- STEP 05Rollout & measure
Adoption and accuracy tracked in production.
Ready to build something that lasts?
Tell us what you are trying to ship or secure. All we need is a 30-minute call to understand the problem and tell you what it would take.