Your documents, finally queryable by AI.
We turn your PDFs, wikis, procedures and history into a knowledge base your team can query in natural language. Every answer is sourced. Every access respects your permissions.
What we build
- Ingestion pipeline that digests your sources: PDF, Confluence, SharePoint, Notion, S3, business databases.
- Semantic search layer (RAG) that retrieves the relevant passages before generating an answer.
- Conversational interface on the web, in Teams or in Slack — whichever your teams prefer.
- Sourced citations on every answer, with confidence level and a direct link to the source document.
- Access control inherited from your existing systems (Azure AD, Google Workspace, Okta…).
- Feedback loop so the base learns from your validations and corrections.
Typical use cases
- Tier 1 customer support — instantly answer recurring questions with product docs as source.
- Onboarding — give newcomers an assistant that knows your internal procedures.
- Regulatory watch — query a legal, normative or HSE corpus with verifiable citations.
- RFP responses — generate sourced drafts based on your past answers.
- Sales research — find a clause, a price, a client case across thousands of proposals.
GDPR by design — what we take seriously
- EU hosting by default (Belgium, France or Germany depending on your choice).
- Inherited permissions: a user only sees answers about what they already have permission to see in your systems.
- Encryption at rest and in transit, keys managed separately.
- Audit logs on every request: who, when, which source, which answer.
- No training on your data by third-party models.
- Deletion or re-ingestion on request, no vendor lock-in.
Stack & common integrations
- Document sources: SharePoint, Confluence, Notion, Google Drive, Dropbox, S3, SQL databases.
- Models: Claude, GPT, Mistral, open-source models hosted in EU — selection based on your sovereignty requirements.
- Interface: embedded web, Microsoft Teams, Slack, API for custom integration.
- Observability: quality metrics, hallucination tracking, usage dashboard.
Duration and indicative budget
- 4 to 8 weeks from scoping to production of a first scope.
- Budget on request, calibrated on the number and complexity of sources (typically 1 to 3 for an MVP), excluding inference and hosting costs.
- Monthly Run package afterwards, calibrated on query volume and base size.