Generative AI consulting

Generative AI consulting services for production systems

We help companies choose the right generative AI use cases, then design, build, secure and optimize them. Our strongest application areas are AI agents and document intelligence — the two places generative AI reliably pays for itself.

Where teams get stuck

  • A convincing pilot that breaks on real data
  • No way to measure whether quality is improving
  • Costs and latency that do not survive scale
  • Security review blocking the launch
  • Uncertainty about what to build first

Engagements

How we work on generative AI

  1. 01

    Generative AI strategy and use-case selection

    We review your workflows and data, then shortlist the generative AI use cases worth funding — with an honest read on feasibility, effort and expected return.

  2. 02

    Architecture and proof of concept

    Model choice, retrieval design, tool and system integration, and a working proof of concept that tests the risky parts first instead of the easy demo.

  3. 03

    Production build

    Generative AI agents and document pipelines shipped as maintainable software, integrated with your existing systems and owned by your team afterwards.

  4. 04

    Evaluation, security and cost

    Task-level evaluation, red teaming and guardrails, then latency and cost per task engineered down against real production traffic.

Application areas

Two areas where generative AI earns its keep

Beyond these, we handle the engineering that makes them dependable: retrieval, fine-tuning and alignment, inference and cost optimization, evaluation and AI security.

Generative AI agents

Agents that take real actions across your tools — scoped permissions, human-in-the-loop checkpoints, audit trails and measured reliability rather than open-ended chat.

  • Customer and internal support agents
  • Back-office process automation
  • Multi-agent workflows with tool calling
  • Agent evaluation and monitoring

Document intelligence

Generative models applied to the documents your business already runs on: invoices, claims, contracts, forms and reports, with confidence thresholds and exception review.

  • Classification and information extraction
  • Contract and policy analysis
  • Multi-document reasoning
  • Straight-through processing with human review

Questions

Common questions

What does a generative AI consulting engagement include?
Most engagements start with a focused assessment: the workflow, the data, the constraints and the use cases worth building. From there we either advise your team or build the system ourselves, through evaluation, security review and cost optimization.
Do you only advise, or do you build?
Both. We are engineers first, so advice is grounded in systems we have shipped. Some clients take the architecture and build it in-house; others have us deliver it end to end and hand it over.
We already have a prototype that is not production-ready. Can you help?
That is the most common starting point. We assess the existing system, identify what will fail under real traffic — accuracy, latency, cost, security — and fix those before scaling.

Next step

Have an AI problem to solve? Let's talk.

Bring the workflow, the constraints and the data. We will tell you what is realistic, what it costs and how we would build it.