Generative AI & LLM Solutions
Large language models are remarkable and, out of the box, unreliable for business use — they will answer confidently even when they are wrong. The engineering that matters is everything around the model: retrieval, grounding, guardrails and evaluation.
Large language models are remarkable and, out of the box, unreliable for business use — they will answer confidently even when they are wrong. The engineering that matters is everything around the model: retrieval, grounding, guardrails and evaluation.
We build generative systems that answer from your own content, cite their sources, and are measured against a fixed test set before they ever reach users. The goal is a copilot your team can actually rely on.
Out of the box, a large language model will answer confidently even when it is wrong — which is exactly what makes it dangerous for business use. The engineering that matters is everything around the model: retrieval, grounding, guardrails and evaluation.
We measure before we ship. Every generative system we build is scored against a fixed set of real questions with known-good answers, so quality is a number we can track rather than a feeling. If it cannot ground an answer, the correct behaviour is to say so.
Generative AI & LLM Solutions
Knowledge assistant
Answer staff or customer questions from your own documents, with citations.
Document intelligence
Extract, summarise and structure information from contracts, reports and forms.
Content drafting
Speed up first drafts within your tone and guardrails.
Internal copilot
A grounded helper wired into your tools and knowledge base.
Search that understands
Semantic search that finds by meaning, not just keywords.
Classification & routing
Sort and route large volumes of text reliably.
Ground in your content
We build retrieval so the model answers from your documents, not its training data, and cites every source.
Add the guardrails
We constrain what the system will and will not do, and design honest 'I don't know' behaviour for out-of-scope questions.
Evaluate for accuracy
We build an evaluation set of real questions and score every change against it before release.
Deploy and monitor
We put it live wired into your tools, with monitoring so quality does not silently regress.
A course we chart together
Chart
We map your data, systems and goals into a shared plan.
Build
Pipelines, models and agents built in short, reviewed cycles.
Prove
We validate against real metrics before anything ships.
Sustain
Monitoring, governance and handover so it lasts.
Generative AI & LLM Solutions
Retrieval grounding plus guardrails: the model answers from your documents and cites them, and we evaluate for accuracy before release.
Rarely. Retrieval and prompt design solve most needs; fine-tuning is reserved for cases that genuinely require it.
We design for it — your content stays within your chosen boundaries, and we advise on model and hosting choices that fit your compliance needs.
A fixed evaluation set of real questions with known-good answers, scored on every change so quality never silently regresses.
Ready to chart a course?
Book a 30-minute discovery call. We will tell you honestly whether this is the right first port of call.
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