AI opportunity assessment
A short engagement to map candidate use cases, check data readiness and recommend where to start. You leave with a prioritized roadmap, not a slide of buzzwords.
AI consulting
Practical AI that works against your own data
We help you find the places where AI is genuinely worth using, then build applications that are reliable, measurable and safe to put in front of your staff and customers.
What we do
From first idea to production system
- Strategy and roadmap We review your processes, data and systems to identify use cases with a clear payoff, then sequence them into a realistic plan with costs, risks and dependencies spelled out.
- LLM and agent applications Assistants, copilots and agents that call your tools and APIs, built with sensible prompt design, structured outputs, error handling and human review where it matters.
- RAG and knowledge systems Retrieval over your documents, tickets and records: ingestion pipelines, chunking, embeddings, search tuning and permission-aware access, so answers are grounded and traceable.
- ML integration Connecting models to the applications and workflows that need them, whether that is a hosted model API, an open-weight model or a classic ML model your data team already built.
- Evaluation and governance Test sets, automated evaluations, monitoring and usage policies, so you know how well the system performs, what it costs and where its limits are.
Typical engagements
Common ways we start
Proof of concept to production
We take a promising prototype, or build one, and turn it into a supported service with proper evaluation, logging, access control and cost management.
Internal knowledge assistant
A retrieval-based assistant over your policies, documentation or support history, integrated with the tools your team already uses and respecting existing permissions.
How we approach it
Measure first, then scale
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Define success
We agree what a good answer or outcome looks like and build an evaluation set before writing much code, so progress is measured rather than guessed.
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Build the smallest useful version
A narrow, working slice in front of real users early. Their feedback and the evaluation results decide what gets built next.
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Harden and hand over
Monitoring, guardrails, cost controls and documentation, so your team can operate and improve the system after we step back.
Related services
AI rarely stands alone
Useful AI depends on good data and solid plumbing. These practices often run alongside it.
- Systems IntegrationGetting the right data to your models and the results back into your systems.
- SalesforceBringing AI assistance into the CRM where your sales and service teams already work.
Thinking about an AI project?
Tell us what you want to achieve. We’ll give you an honest view of what is feasible, what it involves and a sensible first step.