Private AI knowledge assistants
A private AI assistant that answers from your own documents, policies and data, shows its sources and stays inside your access rules.
Book a Free Automation AuditRAG stands for retrieval-augmented generation. Instead of relying only on what a general AI model remembers, a RAG chatbot first searches your own documents for the passages that answer the question, then writes the answer from them. This makes the answers specific to your business, lets the assistant cite where each answer came from and makes it easier to keep information up to date: change the document and the assistant follows.
Employees ask questions about SOPs, policies and product manuals and get an answer with the source.
Suggests replies for support agents from past tickets and documentation.
Find the right clause, price or procedure across thousands of files.
People only see answers drawn from documents their role allows.
Every answer links back to the document and passage it came from.
Optionally look up an order, create a ticket or update a record.
| RAG | Fine-tuning | |
|---|---|---|
| Good for | Answering from changing documents | Changing a model's style or specialised behaviour |
| Updating knowledge | Update the documents | Retrain the model |
| Citing sources | Yes | Not by itself |
| Cost and effort | Lower to start | Higher, needs good training data |
| Typical business use | Most knowledge assistants | Specialised classification or tone, once RAG is not enough |
For most business assistants, RAG is the right start. We recommend fine-tuning only when RAG with good prompts does not meet the quality you need.
Documents, wikis, tickets and PDFs. Remove outdated and duplicate material.
Split content into passages and store them for fast, accurate search.
Connect the model with instructions, guardrails and access control.
Test with real questions, check answers against the source and track where it fails.
Re-index when documents change and review unanswered questions regularly.
For a larger organisation, an enterprise AI assistant needs more than a good chatbot. It needs single sign-on and role-based access so people only retrieve documents they may see, audit logs of who asked what, data residency choices, a process for keeping content up to date across teams and a way to measure answer quality. We design these into the project from the start and can deploy with private or self-hosted models when policy requires it.
ChatGPT answers from its general training. A RAG chatbot searches your own documents first and answers from them, with sources. It is built to know your business.
Any AI can be wrong. RAG with source citations, strict instructions and testing reduces the risk a lot, and users can check the cited source.
PDF, Word, Excel, web pages, Google Drive and Notion content, help-centre articles and more.
No. We configure the set-up so your data is not used to train public models, and can use private models where required.
The index is rebuilt when documents change, on a schedule or when files are updated.
Cost depends on the amount of content, integrations, users and hosting. We scope it after a free audit.
Browse: AI Automation · Free automation audit · Pricing · How we work · AI FAQ
Book a free audit. We will review your documents and show what an assistant could answer.
Book a Free Automation Audit