AI Development & Automation
RAG & AI Knowledge Systems
We build retrieval-augmented generation (RAG) systems that let people ask questions of your documents and get answers with citations — with permissions, evaluation and maintenance planned from the start.
The challenge
Problems we help solve
- Staff spend time searching across folders and tools
- Policies and manuals are long and hard to navigate
- Generic AI tools cannot answer questions about your own documents
- Concerns about exposing confidential information to the wrong people
Our approach
Retrieval-augmented generation combines search with a language model. When someone asks a question, the system first retrieves the most relevant passages from your documents, then asks the model to answer using only those passages and to cite them.
Good RAG depends on the details: how documents are ingested and split, how retrieval is tuned, who is allowed to see what, and how answer quality is measured. We plan each of these explicitly and give you the tools to keep the knowledge base current.
What we offer
RAG & AI Knowledge Systems services
PDF question-and-answer systems
Ask questions of manuals, reports and contracts.
Website knowledge chatbots
Answer visitor questions from your published content.
Document-based AI assistants
Assistants that draft and answer using your internal documents.
Enterprise knowledge search
Natural-language search across multiple knowledge sources.
Private knowledge bases
Access-controlled knowledge for teams or clients.
RAG chatbot development
Conversational interfaces on top of your knowledge.
AI search and retrieval systems
Retrieval pipelines that other applications can use.
Deliverables
What you receive
- Source inventory and ingestion pipeline
- Retrieval tuned and tested on real questions
- Answers with citations to source passages
- Access control aligned with your permissions
- Evaluation set and quality report
- Update and re-indexing process
Exact deliverables are confirmed in the proposal for your project.
Use cases
Where it helps
Policy assistant
Staff ask HR or compliance questions and see the source policy.
Product documentation
Customers get answers from manuals with links to the right section.
Sales enablement
Teams find approved answers from proposals and case material.
Research libraries
Summarise and compare findings across many documents.
Process
How the project runs
Timelines depend on scope and are agreed in writing before work starts.
Discovery and requirements
We clarify goals, users, data, constraints and what success looks like.
Strategy and planning
Scope, architecture, milestones and a written proposal you can review.
Design and prototyping
Wireframes, prototypes or proofs of concept to validate the approach early.
Development and integration
Iterative builds with regular demos and access to a staging environment.
Testing and quality assurance
Functional, responsive, security and — for AI features — output quality testing.
Launch and ongoing support
Deployment, documentation, handover and optional maintenance.
Scope and limitations
Good to know
Answer quality depends on document quality, structure and freshness.
Scanned documents may need OCR before they can be searched.
Permissions must be designed so users only retrieve content they may see.
Knowledge bases need ongoing updates; we plan this with you.
FAQ
Questions about RAG & AI Knowledge Systems
Is our data used to train public AI models?
RAG does not require training a model on your data. We select providers and settings that match your data protection requirements and document how data flows.
What file types can be used?
Common formats such as PDF, Word, web pages and text exports are supported. Scanned images may need text recognition first.
How do you measure accuracy?
We build a set of real questions with expected answers and test retrieval and responses against it, before launch and after changes.
Get in touch
Discuss your RAG & AI Knowledge Systems project
Tell us what you want to achieve. We reply by email with questions, options and next steps.
- 1Send your enquiryA few lines about your goal, users and timeline is enough.
- 2We reply by emailWith questions, options and a suggested approach.
- 3Agree the planScope, deliverables and phases are confirmed in writing.
Related services
Project enquiry
Takes about two minutes. We reply by email.