A private AI assistant that answers employees' questions from your policies, documents and systems, with sources and access controls.
The problem
Knowledge lives in drives, wikis, chats and people's heads. New hires ask the same questions, and experienced staff spend hours answering them.
How it works
Answers from your own documents and policies, with sources and access controls.
- ConnectWe index approved documents, wikis and selected system data.
- PermissionPeople only see answers from content they are allowed to access.
- AnswerThe assistant answers with citations to the source documents.
- ImproveUnanswered questions reveal missing or outdated content.
Where people stay in control
- Access follows your existing permissions
- Answers cite their sources
- Sensitive content can be excluded
What it connects to
How we deliver ai knowledge assistant
The same method as every AI Agents & Automation engagement: each stage ends with a decision you sign off. We work with teams in Bengaluru, across India and abroad.
We study the problem with the people who live it: workflow, customers, constraints.
Problem brief agreedWe agree what success means, what is in scope and the hypothesis we are testing.
Scope signed offFlows, interfaces and architecture, tested as a prototype before engineering starts.
Prototype approvedWorking software and artefacts, demonstrated every week.
Features acceptedRelease to real users with documentation, monitoring and a runbook.
Release acceptedWe measure what happened and turn it into the next roadmap.
Roadmap reviewedRelated insights
- What is an AI-native company?An AI-native company redesigns workflows, decisions, data access and software so AI is part of how the business runs. What it means, how it differs from adding AI tools, and how to start.
- What should an AI agent be allowed to do? A practical modelA practical permission model for AI agents: four levels of action from read-only to high-impact, how to enforce them in code rather than prompts, and how to design the handoff to people.
- The anatomy of a production AI agentKnowledge, tools, permissions, a provider abstraction, evaluation and observability: the parts that turn an AI demo into a production AI agent a business can rely on.
Is our data used to train the model?+
Enterprise AI APIs we use do not train on your data by default. Your content is retrieved at question time and access is controlled by your permissions.
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