AI that answers from your business, not from the internet.
Chatbots, assistants and retrieval systems built on your documents and data — with citations, guardrails and measurable outcomes.
What's included
- AI chatbots & assistants
- RAG knowledge systems
- Document intelligence & AI search
- OpenAI / Gemini / Groq integrations
Generic AI that invents answers
A raw language model knows nothing about your policies, your catalogue or your customers — so it guesses confidently and wrongly. Meanwhile the knowledge your team needs sits in PDFs, tickets, spreadsheets and inboxes that nobody can search.
- Support answering the same questions dozens of times a day
- Critical knowledge locked inside documents nobody can find
- A chatbot that frustrates customers into calling anyway
- Staff spending hours reading documents to extract a few fields
- An AI pilot that impressed in a demo and died in production
Retrieval-grounded systems with verifiable answers
We build retrieval-augmented systems: your content is chunked, embedded and indexed, and every answer is generated from passages actually retrieved from your knowledge base — with the sources shown. Guardrails constrain scope, evaluation sets measure accuracy before launch, and we monitor real conversations after it. The result is an assistant that resolves questions correctly, escalates when it should, and gets measurably better as your content grows.
Everything the project needs, delivered as defined milestones
No vague retainers. Each item below is a concrete deliverable you receive and own.
AI feasibility & use-case scoping
An honest assessment of what AI will and won't solve for you, with the highest-value use case identified first.
Knowledge base pipeline
Ingestion, chunking, embedding and indexing of documents, sites and databases, with scheduled refresh.
RAG system
Vector search with re-ranking and grounded generation that cites its sources.
Conversational interface
A production chat experience — streaming responses, history, file uploads and human handover.
Document intelligence
OCR, extraction and classification that turn unstructured files into structured, queryable data.
Guardrails & evaluation
Scope limits, refusal behaviour, PII handling and a test set that quantifies answer quality.
Integration & deployment
Embedded on your site, in your product, or connected to WhatsApp, Slack and your CRM.
What we build with, and what it looks like in practice
Technologies
- OpenAI
- Google Gemini
- Groq
- LangChain
- LlamaIndex
- pgvector
- Pinecone
- Qdrant
- Python
- FastAPI
- Next.js
Example projects
- A healthcare assistant answering from a curated clinical knowledge base with citations
- An internal assistant that searches years of policies, contracts and specifications
- Document intelligence that reads invoices and returns structured, validated data
- A sales assistant that qualifies enquiries and books consultations automatically
Case studies from this area
Written up with the problem, the approach and the technology — and honestly labelled.
AI Solutions questions
The things people usually want to know before starting.
AI that answers from your business, not from the internet.
Chatbots, assistants and retrieval systems built on your documents and data — with citations, guardrails and measurable outcomes.
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