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Applied AI

AI Enablement

Most AI projects stall between prototype and production. We start from the business process you want to improve, prove the model earns its cost on your data, then build the evaluation and monitoring that lets it run unattended.
Idea to evaluated production pilot
6wkIdea to evaluated production pilot
Typical deflection on document-heavy workflows
70%Typical deflection on document-heavy workflows
Throughput on manual review processes
3xThroughput on manual review processes

Capabilities

What this actually involves

The specific work, not a list of technologies.

Opportunity mapping

We audit your workflows for the tasks where language and vision models genuinely outperform rules — and tell you plainly where they do not.

Retrieval architecture

Grounding models in your own documents and data with chunking, embedding and reranking strategies tuned to your corpus, so answers cite real sources.

Evaluation harnesses

Golden datasets, automated scoring and regression gates in CI. You get a number that tells you whether a prompt or model change made things better.

Guardrails and governance

PII redaction, prompt-injection defence, human-in-the-loop escalation and full audit logging for regulated environments.

Deliverables

What you receive

Everything below transfers to you on completion — code, infrastructure and documentation included.
  • AI opportunity assessment with ranked, costed use cases
  • Working pilot measured against a baseline
  • Evaluation suite and quality dashboard
  • Production integration with fallback behaviour
  • Cost and latency monitoring per request
  • Team enablement workshops

Typical stack

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Ideal for

  • Teams with a stalled AI proof of concept
  • Document, ticket or claim-heavy operations
  • Businesses with proprietary data they cannot yet query

Common questions

What clients ask first

If your question isn't here, ask it directly — you'll get a straight answer.

Will our data be used to train third-party models?

No. We deploy against enterprise API tiers with training explicitly disabled, and for sensitive workloads we can run open-weight models entirely inside your own cloud account.

How do you stop the model making things up?

Retrieval grounding with mandatory citation, confidence thresholds that route low-certainty cases to a human, and an evaluation suite that catches regressions before release.

What does it cost to run?

We instrument cost per request from day one and design caching, routing and model-tiering to control it. You see a projected monthly running cost before committing to production.

Start the conversation

Need ai enablement?
Let's talk specifics.

Six questions gets you a recommended package, an indicative timeline and a technology plan. No sales call needed to get a useful answer.

  • Reply within 4 business hours
  • No cost, no obligation
  • NDA on request before you share anything