AI & Automation
Generative AI & Agentic AI
From promising pilots to AI that is safe to run in production.
The challenge
Where teams get stuck.
Pragmatic AI and generative AI engineering: we help you choose the right use cases, build them properly, and evaluate them rigorously enough to trust.
- 01
Proofs of concept impress in demos but stall before production.
- 02
It is unclear which use cases justify investment and which are noise.
- 03
There is no reliable way to test the quality, safety or cost of LLM outputs.
- 04
Data privacy, security and governance concerns are blocking adoption.
What we deliver
How we help.
AI opportunity discovery
Workshops and rapid analysis to identify use cases with real business value, feasible data and acceptable risk.
LLM application engineering
Production-grade assistants, copilots and workflow automation built on leading foundation models and your own systems.
Retrieval-augmented generation
Grounding models in your organisation's knowledge with well-designed retrieval, chunking, ranking and citation.
AI agents & automation
Agentic workflows that use tools and APIs to complete multi-step tasks, with clear guardrails and human oversight.
Evaluation & testing of AI
Automated evaluation suites that measure accuracy, safety, latency and cost, so you can change prompts and models with confidence.
Responsible AI & governance
Practical controls for privacy, security and transparency that keep adoption moving without creating unmanaged risk.
Outcomes
What you can expect.
- A prioritised AI roadmap grounded in business value
- Pilots that reach production with measurable quality
- Repeatable evaluation for every prompt and model change
- Guardrails that satisfy security and compliance teams
Technologies we commonly work with
We are tool-agnostic and work with your existing stack. These are typical for this kind of engagement.
- Anthropic Claude
- Azure OpenAI
- Amazon Bedrock
- Snowflake Cortex
- LangChain
- Vector databases
- Python
Questions
Common questions.
How do you test something as unpredictable as an LLM?
With evaluation suites: curated datasets, automated scoring and human review where it matters. This turns subjective impressions into metrics you can track across every prompt, model and data change.
Can we use generative AI without exposing sensitive data?
Yes. We design for data protection from the start, with appropriate hosting choices, access controls, redaction and logging, and we work with your security and compliance teams throughout.
Where should we start?
Usually with a short discovery engagement that surfaces candidate use cases, scores them on value and feasibility, and produces a working prototype of the strongest one.
Let's talk about your next project
Tell us what you are trying to achieve. One of our engineers will listen, ask useful questions and tell you honestly whether we can help.