LLM-powered knowledge platforms for enterprise decision intelligence

We implement retrieval-augmented generation using your private content, with chunking, embedding, and ranking logic tuned for accuracy, latency, and domain context.

We build automated pipelines to ingest content from Confluence, Google Drive, Notion, SharePoint, Jira, Slack, Dropbox, file systems, and proprietary databases, keeping everything current.

All knowledge retrieval respects your permission model. We integrate with SSO, LDAP, Okta, or custom identity providers so users only access what they’re allowed to see.

We use Weaviate, Qdrant, Pinecone, or FAISS to structure long-term memory, which is optimized for relevance, recall, and embedding refresh strategies.

We deploy knowledge agents via web apps, Slack, Teams, VSCode extensions, or CRM plugins, wherever your team already works.

Track how knowledge is queried, what documents are retrieved, and where errors happen, and optimize your corpus and prompts over time.

We handle prompt templating, LLM provider routing (e.g., GPT-4o vs Claude 3), cost management, versioning, and safe output constraints.

We automate the detection of document updates, deletions, and additions, ensuring your vector index, embeddings, and RAG responses always reflect the latest internal knowledge without manual retraining.