An AI assistant that lives in Microsoft Teams or Webex, connected to your documents, databases, infrastructure, monitoring, and code. Role-based access control enforced. Your data never used for training. Deployed on-prem, private cloud, or SaaS.
A data pipeline first. An assistant second. Content flows from your systems through a secure ingestion pipeline to the people who need it.
Connects to your data sources, indexes content, and keeps it current through automated re-indexing. Documents are chunked and embedded for semantic retrieval; structured sources like SQL are queried in real time.
Runs inside Teams or Webex as an integrated bot. Determines relevant data sources, retrieves authorized content, and generates grounded responses with full source citations.
Role-based access enforced at the retrieval layer, not the interface. If a user lacks access to a document or database, the assistant cannot surface that content regardless of query.
Golden Retriever's ingestion pipeline indexes Office documents on network file shares and Confluence pages via API. Documents are processed, chunked, and made retrievable through natural language queries.
This turns file shares and wikis that are effectively invisible to most employees into a searchable, conversational knowledge base — without migrating data or changing how documents are stored.
Connect your Git repositories and give authorized users natural language access to your codebase. Engineers and technical leads can ask about implementation details, search for how specific functions are used, and get contextual answers grounded in your actual code.
Golden Retriever connects to Kubernetes clusters, Azure Log Analytics, and Nagios monitoring via API. Operations teams can query cluster status, pull log data, check alert states, and investigate issues through natural language.
Connect to your SQL databases and give any authorized user the ability to ask business questions in plain language. The system translates natural language queries into SQL, executes them against read-only connections, and returns structured answers.
A VP asking “what were our top 10 accounts by revenue last quarter” gets an accurate, granular answer pulled directly from the source system — no analyst queue, no report request, no waiting.
Beyond retrieval, Golden Retriever can produce deliverables. Users can request Word documents, PowerPoint presentations, and filled templates directly through the chat interface. The assistant pulls from indexed data to generate drafts, populate templates, and compile information from multiple sources.