Custom internal AI copilots for teams
We build internal AI assistants for business use: they find answers in your policies, procedures and past work, and complete routine tasks in your own systems. Staff get answers with their sources, and access follows the permissions you already have.
What it is and when it fits
An internal copilot is a private assistant for your employees. It searches SharePoint, wikis, ticket histories and databases, answers with citations and can take small actions such as filing a request, drafting a document or pulling a report. We build it around your identity provider, so each person only sees what they are already allowed to see.
A custom copilot makes sense when off-the-shelf assistants cannot reach your key systems, cannot respect your permission model or give answers your team does not trust. If your knowledge lives mainly in Microsoft 365 and generic search is good enough, a licensed tool may cover it. We compare both before recommending a build.
What we build
Knowledge assistants
Question answering over policies, manuals, contracts and project archives, with every answer linked to its source passage.
Role-specific copilots
Assistants tuned for sales, finance, HR or engineering, each with its own sources, tools and instructions.
Task actions
Tools that let the copilot create tickets, fill templates, query reports or draft emails inside the systems your staff use.
Permission-aware retrieval
Document access checked against SSO groups and source-system rights on every query, including for shared and restricted files.
Usage and feedback insights
Reporting on what people ask, which answers get marked wrong and which sources are missing or out of date.
How it works
- 01
Pick the first department
We start with one department and a clear set of questions its people ask every day, and inventory the sources that hold the answers.
- 02
Connect and index sources
We connect the systems, parse documents properly and set up permission checks before anyone can ask a question.
- 03
Test with real questions
Questions collected from the team become the eval set for retrieval and answer quality, rerun on every change.
- 04
Roll out and extend
After the first department uses it daily, we add sources, tools and departments, guided by feedback and usage data.
Related work
Built with
All technologiesFurther reading
How to build a RAG chatbot people can trust: a practical guide
What it takes to turn a promising RAG experiment into a chatbot people trust: ingestion, hybrid search, citations, permissions and evals.
6 min read
How to evaluate RAG: retrieval metrics, faithfulness and golden sets
How to do RAG evaluation properly: separate retrieval from answers, check faithfulness claim by claim and build a golden set you can trust.
4 min read
Common questions
Those tools work well on general documents. A custom copilot is worth it when you need your own systems as sources, precise permission handling, specific actions or answer quality you can measure and control. Many companies run both side by side.
No. We use enterprise model APIs that do not train on your data, or self-hosted open models where required. Indexes, logs and documents stay in your cloud environment, which can be hosted in the EU.
Sources are re-indexed on a schedule or on change, outdated documents can be excluded, and the eval set is rerun regularly. When the copilot cannot find a reliable source, it says so and points to who can help.