Ask AI Questions on Your Own Data
Your entire knowledge base. Instantly queryable.
Your organisation is sitting on a gold mine of intelligence ; buried in thousands of PDFs, Slack threads, meeting transcripts, CRM notes, internal wikis, and database records. Most of it is never accessed at the speed decisions need to be made. We build a secure AI layer on top of all of it, so anyone in your team can ask a plain-English question and get a cited, accurate answer in under two seconds ; without your data ever leaving your control.
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Your Organisation's Knowledge Is Inaccessible.
The average knowledge worker spends 2.5 hours per day searching for information. Critical decisions are made without access to the full context buried in last year's board deck, the customer complaint filed six months ago, or the technical specification written by someone who left the company. This is not a talent problem ; it is an information architecture problem. And AI solves it.
Connect, Index, Query. In That Order.
We connect to every data source you have ; documents, databases, communication tools, CRM records ; and build a continuously updated vector index. Your AI layer sits on top, providing cited, grounded answers drawn directly from your own data. No hallucinations because every answer is backed by a source. No data leakage because everything runs in your environment.
Data ingestion from 50+ source types: PDFs, Word docs, Notion, Confluence, Google Drive, SharePoint, Slack, email
Database connectors for PostgreSQL, MySQL, SQL Server, MongoDB, Snowflake, BigQuery
CRM integration: Salesforce, HubSpot, Pipedrive
Continuous auto-sync ; new content indexed within minutes
Semantic chunking and hybrid search (vector + keyword) for maximum accuracy
Citation and source attribution on every answer
Conversation history and context memory
Your Data Stays Yours. Always.
Every component of the system runs in your own infrastructure. The vector database is self-hosted. The LLM can be your custom model or a private deployment. All queries and answers are processed inside your network perimeter. Role-based access control ensures people can only query data they are authorised to see ; the same permissions that govern your source systems are automatically inherited by the AI layer.
Self-hosted vector database (Qdrant, Weaviate, or pgvector)
Private LLM deployment ; no third-party API calls required
Row-level and document-level permission inheritance
SSO integration (SAML 2.0, OIDC)
Full audit logging of all queries and access
GDPR-aligned architecture with per-tenant isolation and audit logging
Questions from Professionals Like You
- Virtually any source with an API or file export: Confluence, Notion, Google Drive, SharePoint, Slack, Microsoft Teams, email archives, Salesforce, HubSpot, PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery, Jira, GitHub, and many more. If it has an API, we can connect it.
- Our retrieval-augmented generation architecture grounds every answer in your actual source documents. On typical enterprise deployments, accuracy on a representative QA benchmark is 92-96%. The system cites its sources so users can verify any answer and trust the output.
- Yes. Access control is a first-class feature. Each user's AI queries are automatically restricted to data sources they are authorised to access, using the same permissions that govern those sources. A junior employee cannot use the AI to surface data they would not normally have access to.
- The system monitors your data sources for changes and automatically re-indexes updated documents, typically within minutes. Deleted documents are removed from the index. The AI's knowledge stays current without any manual intervention.
Your knowledge base. Answering questions in seconds.
Imagine if every employee could instantly query every document, every policy, every deal you've ever closed - in plain English. That's what we build. Book a call and we'll show you a live demo on data like yours.