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Consulting

Applied AI, by the people who run the cluster

Orchestration, RAG, local inference and evaluation. We build the same systems we operate, which is why the advice tends to be about throughput and failure modes rather than about prompt wording.

What we do

Four kinds of engagement

Most projects are one of these, or one leading into another.

Local inference

Specify, install and tune a cluster in your own environment — model selection, serving stack, quantisation, throughput.

  • Hardware sizing
  • Serving stack
  • Quantisation
  • Benchmarks

RAG and retrieval

Get answers grounded in your own documents, with retrieval you can inspect and evaluation that tells you when it regresses.

  • Chunking and indexing
  • Hybrid retrieval
  • Grounding
  • Eval harness

Agent orchestration

Multi-step agents that call your systems: tool design, guardrails, retries, and the boundary between deterministic code and the model.

  • Tool design
  • MCP servers
  • Guardrails
  • Cost control

Evaluation and monitoring

Know whether a change helped. Task-specific evals, regression suites, and monitoring that surfaces drift before a user does.

  • Golden sets
  • Regression suites
  • Drift alerts
  • A/B harness

When to call

The four situations we see most

A demo that will not survive production

It answers well on the five documents you tested and falls apart on the five thousand you have.

No way to tell whether a change helped

Prompts get edited, quality moves, and nobody can say by how much or in which direction.

An agent that fails in surprising ways

Loops, runaway spend, or a tool call that does something nobody intended at 3am.

Data that cannot leave the building

The obvious provider is off the table for reasons that are legal, not technical.

Process

Three steps, no retainer to start

  1. 01

    Scope

    A call to establish what you are running, what it costs today, and whether we are the right answer. Often we say no.

  2. 02

    Benchmark

    We run your workload — your prompts, your documents — on the cluster and show you throughput, latency and quality against your current setup.

  3. 03

    Deploy

    Reserved capacity on our cluster, or the same stack installed in your racks. Either way you leave with something running.

Tell us what is not working

A scoping call costs nothing and quite often ends with us saying the problem is smaller than you thought.