Turn the AI buzz into shipped, measurable wins.
We find the AI opportunities with the best return in your business and build them properly, with evaluations, guardrails and cost controls. Then we put them in front of your team and customers.
Sound familiar?
The signs it's time to bring us in.
Leadership wants an AI strategy, and the team has a dozen disconnected experiments.
Your prototype demoed well but falls apart on real data.
Nobody can tell whether the model's output is getting better or worse.
LLM bills are growing faster than the value they create.
Legal and security are (rightly) nervous about where your data goes.
What you get
Concrete deliverables, not slideware.
AI opportunity map
Use cases scored by impact, feasibility and risk, with a clear first bet.
Production AI features
Copilots, agents, RAG search, document extraction and classification, built into your product or operations.
Evaluation harness
Test sets and automated evaluations, so quality is measured rather than judged by feel.
Guardrails & governance
PII handling, access controls, prompt-injection defenses and audit logs.
Cost & latency tuning
Model routing, caching and batching that keep the cost per request healthy.
Team enablement
Workshops and playbooks so your engineers can ship the next one themselves.
How it works
A clear path, with results every step.
You'll always know what we're working on, what's next and how we're measuring success.
Weeks 1–2
Discover
Map workflows and data, size the opportunities, pick the first bets.
Weeks 3–6
Prototype
A working version on your real data, measured against a baseline.
Weeks 6–10
Productionize
Evaluations, monitoring, guardrails and integration into real workflows.
Ongoing
Scale
Roll out, measure the impact, train your team, go after the next use case.
Outcomes
What changes for you.
- Hours of manual work removed every week
- AI features your customers actually use
- Quality measured on every release
- Predictable model spend
FAQ
AI Transformation: common questions
Which models do you work with?
We aren't tied to any model vendor. We use Anthropic Claude, OpenAI, Google Gemini and open-weight models, and choose by quality, cost, latency and data-residency needs.
Will our data be used to train models?
No. We use enterprise API terms that exclude training on your data, and we can deploy inside your own cloud account where required.
We tried AI before and it didn't stick. Why would this be different?
Most stalled AI projects have no evaluations and never make it into real workflows. We start from a business metric and build the evaluations before we scale.
Do we need a data science team?
No. Most AI work today is solid software engineering. We build it and train your existing engineers along the way.
Related services
Often paired with.
Ready to talk AI Transformation?
Tell us where you are and where you need to be. You'll get a straight answer on whether we can help, and how.
30 minutes · no pitch deck · no obligation