Retrieval-augmented generation systems that turn fragmented documents, wikis, and databases into a single conversational knowledge layer.
SUCCESS: Architecture deployed. Payload structure matches schema bounds exactly.
Most enterprise knowledge sits in places where people have trouble finding it. Documents in folders. Wikis behind logins. Threads in Slack from quarters past. Decisions get slower as knowledge gets fragmented, and the cost of that fragmentation compounds across every conversation, every onboarding, every customer interaction. RAG & Knowledge Intelligence consolidates that landscape into a unified, queryable knowledge layer.
Total Sync engineers retrieval systems that respect existing access controls, attribute every answer to its source, and update continuously as new content lands. The system becomes the way your teams access institutional memory.
Retrieval-augmented generation systems engineered for enterprise environments. Documents ingest from any source: PDF, DOCX, HTML, databases, wikis, and structured content. Semantic search runs across millions of documents with sub-second response. Every answer comes with source citations. Ingestion respects existing access controls, so sensitive content stays available only to the people who already have permission to see it elsewhere in the stack. The system delivers a single conversational interface for your employees, your customers, or your product.
Document ingestion from any source, including PDF, DOCX, HTML, databases, and wikis.
Semantic search across millions of documents with sub-second retrieval.
Source attribution for every answer, traceable to the document and section.
Permission-aware retrieval respecting existing access controls and roles.
Continuous indexing and update pipelines as new content lands.
Multi-modal support, including text, tables, and images.
Conversational UI or API access for integration into products and workflows.
Unify your fragmented data landscape into an instant, conversational knowledge layer.
Internal knowledge assistants for employees across functions, connecting wikis, docs, and Slack history into one queryable interface.
Customer-facing knowledge support that reduces tier-1 ticket load by instantly providing accurate, cited answers from your documentation.
Sales enablement and product information access, allowing revenue teams to surface specifications and case studies mid-call.
Catalogs your knowledge sources, access patterns, and the questions teams frequently ask.
Covers ingestion architecture, retrieval logic, citation framework, and access control integration.
Ships with the first knowledge source live, expanding to additional sources in phases.
Connects the knowledge layer to daily interfaces (Slack, web, custom apps) and handles accuracy tuning.
Post-launch, the knowledge layer enters a continuous improvement loop, utilizing query patterns to guide content refreshes. Typical timeline runs 4 to 8 weeks.
Knowledge trapped in PDFs, forgotten wikis, and old Slack threads buried in archives.
Unified knowledge access, every answer linked to its source, continuous learning loop.
Schedule a discovery call to catalog your knowledge sources and identify where RAG delivers the strongest impact for your teams or customers.
SharePoint, Confluence, Notion, Google Drive, OneDrive, Box, Slack, Microsoft Teams, custom databases, and proprietary CMS.