Scattered knowledge
Answers live across documents, wikis, and people’s inboxes.
Generative & conversational AI
Your knowledge. Easier to use.
Cites sources · Respects permissions
What it solves
The problems teams most often bring to us first.
Slow onboarding
New staff take time to find reliable answers.
Inconsistent answers
Customers get different answers depending on who responds.
Expert time on drafting
Specialists spend hours drafting and summarising.
Where it helps
Each application is scoped around your data, environment and requirements.
Knowledge assistants
Make approved documentation easier to search and understand, with source references where appropriate.
Customer support
Help resolve common questions and capture context before handing complex requests to your team.
Team copilots
Assist with drafting, summarising, and information retrieval while keeping people responsible for decisions.
How it works
A typical flow, configured around your rules and approvals.
- 01
Ask a question
- 02
Retrieve approved context
- 03
Generate a grounded answer
- 04
Review and act
What a project includes
From the first question to a working system your team owns.
- Knowledge and access assessment
- Content preparation and retrieval design
- Assistant configuration and tool integration
- Quality, safety, and permission evaluation
- Team enablement and maintenance plan
Technology & integrations
SharePoint & Google DriveKnowledge bases & wikisVector searchLLM providers & open-weight modelsSSO & permissionsWeb & in-app chat
How we measure it
Acceptance criteria are agreed before a pilot grows into a rollout.
Grounding
Does the answer reflect the approved source information?
Access boundaries
Does the assistant respect user permissions and content scope?
Useful fallback
Does it acknowledge missing context and route unresolved questions appropriately?
Questions, answered
Something else on your mind? Ask us directly.
Can an assistant use our internal documents?
Yes, subject to the permissions and integrations available. We plan how approved content is indexed, updated, and accessed by different users.
Can the AI make mistakes?
Yes. We evaluate answers, show sources where possible, and design fallback behaviour. Human review remains important for consequential or uncertain outputs.
How does it stay up to date?
We agree on how source information changes and choose an update approach. Ongoing evaluation helps identify missing, outdated, or ambiguous content.
