Answers from your data
Responses grounded in your approved documents.
We build business-specific AI assistants powered by large language models and retrieval-augmented generation (RAG), so answers come from your own approved knowledge.
A large language model on its own doesn't know your policies, products or documents. Retrieval-augmented generation (RAG) finds the relevant information from your knowledge base and gives it to the model, so answers are grounded and can cite sources.
We design the knowledge pipeline, permissions, prompts and evaluation together. Custom solutions are built on models from providers like OpenAI or Anthropic; they are not official products of those companies.
Cleaning, structuring and chunking documents for reliable retrieval.
Every engagement is shaped around your goals. These are the outcomes we design for from day one.
Responses grounded in your approved documents.
Users can check where an answer came from.
Sensitive content stays with authorised people.
Usage monitored and model choice optimised.
Contact us
Tell us what you're trying to achieve. We'll recommend an approach, outline the scope and explain the trade-offs, with no obligation.
A clear sequence from first conversation to measurable results, scaled to the size of your project.
We confirm the problem, the users and whether AI or simple automation is the right tool.
We review the data, integrations, permissions and how errors will be handled.
A working prototype tested against real examples, edge cases and quality targets.
Connected to your systems with access controls, cost limits and human handoff.
Ongoing tracking of quality, cost and usage, with regular improvements.
Strategy, design, engineering, AI and marketing work together, so nothing gets lost between agencies.
Written scope, assumptions and exclusions, regular demos and honest updates when something changes.
Secure defaults, tested releases and documentation, so your solution keeps working long after launch.
Practical guides on software, AI, automation and digital growth.
Can't find what you're looking for? Ask us directly.
RAG retrieves up-to-date information at question time and is usually best for knowledge assistants. Fine-tuning changes a model's behaviour or style. Many projects need only RAG.
Share what you're working on. We'll tell you honestly how we'd approach it, and whether we're the right fit.
What happens next