AI Assistant (RAG)
Ask your data directly—answers come with sources
An AI assistant connected to your enterprise databases and documents, so non-technical staff can get analysis with a single question.
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Pain points
Why reports and public AI tools fall short
New analysis requests queue up for report development, often taking days.
Public AI tools don’t understand company data; answers can’t be verified and raise security concerns.
Data is spread across systems, so one question means digging through several reports.
How we do it
A trustworthy enterprise AI assistant
Knowledge base & semantic layer
Turn databases and documents into a knowledge base so AI understands your fields and metric definitions.
Answers with sources
Every answer cites its data source—traceable, with lower hallucination risk.
Existing permissions
Integrates company accounts and permissions (e.g. Microsoft SSO), so people only see the data they should.
Fits your workflow
Embed in Teams or Slack, or use a standalone web interface.
Use cases
Every team can ask the data directly
- Sales“Who were our top 20 customers by purchase value last quarter?” Get the list in one sentence.
- Customer serviceLook up order status, product specs and internal SOPs.
- ManagementReplace digging through multiple reports with a conversation.
Technology options: Enterprise-grade model services such as Amazon Bedrock, Azure OpenAI and Google Vertex AI, deployable in your existing AWS, Azure or Google Cloud environment.
FAQ
FAQ
What is a RAG AI assistant?
RAG (retrieval-augmented generation) first retrieves relevant content from your own databases and documents, then has a large language model generate the answer with cited sources, reducing the risk of AI making things up.
How is company data kept secure?
Deployment is planned around your security requirements—for example, keeping data and model services inside your existing AWS, Azure or Google Cloud account and reusing company accounts and permissions, so people only see the data they should.
What do we need to prepare?
Start by collecting frequently asked questions, the relevant data sources and permission rules. If data is still scattered or inconsistently defined, begin with a data platform.
Can it connect to Teams or Slack?
Yes. We can also provide a standalone web chat interface.
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Is your data ready for an AI assistant?
Book a consultation and we’ll assess your data and the right scope.