AI Implementations
Production AI, without the hype.
RAG, agents, model integration and governance — built into your product, not bolted on. We focus on shipping AI that improves a metric, not a demo.
The problem
What we're solving
Most AI projects stall between prototype and production. Models hallucinate, costs spiral, security gets ignored, and the team can't tell which experiment is actually paying off. We've fixed that for ourselves and our clients — and we bring that playbook with us.
Our approach
How we deliver
- Start with a measurable use case, not a model.
- Choose the smallest model that does the job — cost and latency matter.
- Wrap every call with evals, monitoring and guardrails.
- Give your team the tools to iterate after we're gone.
What you get
Deliverables
- ✓RAG pipeline with retrieval evals
- ✓Agent workflows with tool registries
- ✓Model gateway with cost & latency dashboards
- ✓Prompt library + versioning
- ✓Safety guardrails and PII filtering
- ✓Hand-off documentation and team training
Tech stack
Capabilities
Process
From kickoff to delivery
01
Use-case scoping
Pick a single workflow with a measurable target.
02
Prototype
Smallest viable model + retrieval, with eval harness from day one.
03
Productionize
Gateway, monitoring, guardrails, cost controls.
04
Iterate
Weekly evals, prompt updates, model swaps as the market moves.
In practice
Use cases
Internal knowledge assistant
RAG over policies, contracts and tickets — with citations and access control.
Customer-facing copilots
Embedded agents that take action, not just answer questions.
Document automation
Extract, summarize and classify at scale — with human-in-the-loop review.
FAQ
Common questions
Which model should we use?+
It depends on the workload. We benchmark frontier and open-source models against your evals and pick the smallest that meets the bar — usually a mix.
How do you handle hallucinations?+
Retrieval grounding, structured outputs, evals and guardrails. We treat hallucinations as a measurable defect, not an inevitability.
What about data privacy?+
We default to providers with no-train policies, deploy in your cloud where required, and apply PII filtering before any external call.
Can you fine-tune?+
Yes — but only when prompting, retrieval and tool use have been exhausted. Fine-tuning is a maintenance commitment we make deliberately.
Ready to build what's next?
Tell us where you're stuck. We'll come back with a clear plan and a fixed monthly retainer.