The problem in three numbers
Most organisations have already lost the "do we need AI knowledge tools?" debate. The active question is which one, and what it costs to get wrong. Three numbers shape that conversation:
- 9 hours a week per knowledge worker spent looking for documents that exist somewhere in the organisation. At 100 employees that's ~46,000 hours a year, searching, not deciding.
- 15–27% hallucination rate on general-purpose AI assistants. Fine for a brainstorm. Not fine for a policy, regulatory, or audit-bearing question.
- June 2025: Microsoft confirmed under oath that EU-hosted data on its infrastructure can be compelled by US authorities. Hosting region alone no longer resolves the sovereignty question.
AnswerVault is built to solve all three at once: a single governed knowledge layer, grounded answers with citations, and a deployment tier outside US legal exposure.
How your team gets answers
A user asks a question. The retrieval agent queries a knowledge graph built from your approved documents. The managed AI generates a grounded answer with citations back to the source. Three steps. Seconds. No tab-switching, no AI subscription to administer, no LLM API keys to manage.
What makes this different from general-purpose AI: retrieval is scoped. Only documents you've approved can produce an answer. If the answer isn't in your sources, AnswerVault says so instead of guessing. Every reply has a clickable citation to the document of record.
Three steps to get started
1. Connect your knowledge sources
An admin OAuths into SharePoint, Google Drive, or Confluence and picks the folders, drives, or spaces to include, and only those. Credentials aren't stored; the connection uses OAuth tokens scoped to what's been selected. Whatever's connected becomes part of the tenant's curated knowledge base. Most teams have their first connection running in under five minutes.
2. We build your knowledge graph
Documents are parsed, chunked, embedded, and linked into a knowledge graph that maps how policies, procedures, and updates relate. AI is fully managed, no API keys, no LLM subscription, no token bill to track. The graph stays current automatically: when a document changes in the source, the affected chunks re-index.
3. Start asking questions
Web, Teams, Slack, CLI, and (soon) REST API, one knowledge layer behind every surface. Every answer cites its source. Every query is logged against your tenant's audit trail.
Four things general-purpose AI structurally cannot do
Independent of any competitor, these are the product's own advantages, the reasons buyers pick a governed knowledge layer over a chat assistant.
Governed knowledge bases
Answers come from approved, curated document sets, not everything a user can see. The compliance team can sign off on "AnswerVault may answer from these documents", and that's where answers come from. Audit trail on every query.
External access without licences
Contractors, delivery partners, auditors, regulators, and citizens get governed access to a curated knowledge base, no M365 or Google Workspace seat, no tenant access. Copilot can't do this; Glean and Guru don't try.
Cross-ecosystem retrieval
SharePoint, Google Drive, and Confluence indexed with equal depth. Most organisations didn't choose to be multi-ecosystem, it happened through acquisitions, team preferences, or just history. AnswerVault treats all three as first-class.
Graph-powered retrieval, not just vector similarity
A knowledge graph maps relationships between documents, entities, and concepts. The retrieval agent traverses those relationships, not just text similarity, meaning it can follow "this policy supersedes that one", "this procedure implements that policy", or "this team owns this document".
Answers where the question is asked
The point isn't a new tool to learn, it's that the answer arrives in the channel where the question lives. Five surfaces, one knowledge layer:
- Web app at
app.answervault.ai. Full chat experience, conversation history, document explorer. - Microsoft Teams. Mention
@AnswerVaultin any channel, chat, or thread. Answers post in-thread with citations. - Slack. Same pattern:
@AnswerVaultin public channels, private channels, or DMs. - CLI: for developers and automation. Pipeable output, structured JSON mode, fits into scripts and CI.
- REST API: for custom integrations and existing platforms (helpdesk, support tooling). Available on Business and above.
Who it's for
Every team in the organisation has the same problem and a slightly different shape of it:
- Engineering, architecture decisions, runbooks, API docs, post-mortems, on-call procedures.
- HR & People Ops, handbooks, benefits, leave policies, grievance procedures.
- Operations. SOPs, compliance procedures, regulatory guidance, supplier processes.
- Customer support, internal KB, troubleshooting, SLAs, escalation paths.
- External access, governed knowledge for contractors, partners, auditors, citizens.
- Distributed teams, bridge the ecosystem gap across offices, time zones, and tools.
Secure by design, sovereign by tier
Security isn't a feature pinned on at the end. Your documents are processed and stored on EU and UK infrastructure. Business and Enterprise tiers let you choose the data region. The Enterprise sovereign tier deploys entirely on non-US infrastructure, no US-headquartered provider at any layer, for organisations that need to resolve CLOUD Act exposure.
- Encrypted at rest and in transit. AES-256-GCM at rest, TLS 1.3 in transit, mTLS between internal services.
- Per-tenant isolation: separate encryption keys per customer; one tenant's data cannot be decrypted with another's keys.
- Managed AI infrastructure: your documents are never sent to a third-party LLM provider. We run the AI.
- We don't train on your data: your documents answer your questions, full stop.
- Full audit trail: every query, response, and source access is logged.
- GDPR-compliant, ISO 27001 aligned, ISO 42001 in progress, G-Cloud listed.
Full position on the security page; deeper sovereignty argument on the sovereignty topic guide.