RAG & Knowledge Systems
AI systems that search, reason over, and surface answers from your own documents, databases, and internal knowledge.
What's Getting in the Way
Your company has a wealth of knowledge trapped in documents, Notion pages, Confluence wikis, and people's heads. New hires take months to get up to speed. Customers ask questions your docs already answer. Support tickets exist because people cannot find the right information fast enough. Teams typically recover 5-10 hours per week previously spent searching for information or asking colleagues.
- New team members spend weeks searching for information that already exists somewhere
- Inconsistent answers across the organisation because different people know different things
- Support tickets raised for questions that are answered in your own documentation
- Onboarding new staff is painful because knowledge is scattered and undocumented
What You Get
Document Ingestion Pipeline
We ingest all your existing knowledge. PDFs, Notion, Confluence, Google Docs, product docs, SOPs. Everything structured and indexed for accurate retrieval.
Vector Database Setup
We build and configure the vector database that powers semantic search across your knowledge base. Fast, accurate, and scalable as your docs grow.
Retrieval Logic and Ranking
We tune the retrieval layer so the system surfaces the most relevant content first. Not just keyword matching. Semantic understanding of what the user actually needs.
Interface or API
A chat interface tailored for your use case, or an API that integrates into your existing tools. Internal team assistant, customer-facing knowledge base, or embedded in your product.
Access Controls and Security
Role-based access so different users see different knowledge. Internal docs stay internal. HR docs stay in HR. We advise on the right architecture for your security requirements.
The Process
Knowledge Audit
We audit all your existing knowledge sources. Documents, wikis, databases, spreadsheets. We map what you have, where it lives, and what needs cleaning before ingestion.
Data Pipeline Build
We build the ingestion pipeline, process and chunk your documents correctly, and create the vector index. Quality here determines answer quality later.
Retrieval Tuning
We test the system against real queries and tune the retrieval logic until answers are accurate, well-cited, and genuinely useful.
Deployment and Access Setup
We deploy the interface or API, configure access controls, set up automated sync so the knowledge base stays current, and train your team.
Pricing
$5K-$12K
RAG & Knowledge Systems
Timeline: 3-5 weeks
Final price depends on scope and complexity. We confirm exact pricing after a free scoping call.
Scope your knowledge systemQuestions About This Service
What file types do you support?
PDFs, Word docs, Notion, Confluence, Google Docs, Markdown, websites, and more. If it contains text, we can ingest it.
How fresh is the data?
We set up automated ingestion pipelines so new or updated documents are indexed continuously. The knowledge base does not go stale.
Can it cite its sources?
Yes. Every answer includes citations to the source document so users can verify and read more. This is standard in our builds.
How is sensitive data handled?
Your data never leaves your infrastructure unless you choose a cloud deployment. We advise on the right architecture for your security and compliance requirements.
Can non-technical staff use it?
Yes. The interface is designed to be as simple as a chat window. No technical knowledge required to use it. We also train your team on managing and updating it.
Often Combined With
Let's build it.
Book a free 45-minute strategy call. No pressure, no obligation.