Problem solved

Organizations often have critical knowledge scattered across diverse formats—PDFs, documents, screenshots, internal images, help articles, and diagrams. Traditional chatbots provide unverified, generic responses, eroding user trust. Calypso solves this by offering a centralized, multimodal RAG service that retrieves information from all these file types and returns answers with traceable citations. This grounds AI interactions in actual company knowledge, enabling users to independently verify sources and making AI answers actionable in customer support, sales, product documentation, and internal workflows.

Use cases

• Providing an answer widget on a website that instantly responds to visitor questions using PDFs, docs, and FAQs with citations.
• Assisting customer support teams by retrieving answers from screenshots, troubleshooting guides, policies, and manuals.
• Enabling sales teams to ask questions about pricing sheets, comparison docs, case studies, and diagrams to qualify leads faster.
• Building a documentation agent that lets users query across API references, onboarding flows, release notes, and visual guides.
• Integrating into n8n workflows to automatically summarize policies or pull context from knowledge bases for ticket resolution.
• Generating investor-grade summaries, business model extractions, risk-factor analyses, and evidence-based diligence checklists from multimodal filings.

Audience

• Developers
• ML Engineers
• Business Users
• Enterprise

Pros

• Ingests and retrieves from multimodal content including PDFs, images, screenshots, charts, and diagrams alongside text.
• Provides grounded answers with page-aware citations and source references for user verification.
• Reusable knowledge layer that can be deployed across website widgets, AI agents, workflows, and product UIs.
• Integrates with AI clients via MCP server and automation tools like n8n, expanding its reach.
• Simple hosted pricing with clear monthly limits and enterprise options.

Cons

• Restrictive request limits on lower-tier plans (50–200 RAG requests per month), which may be insufficient for high-traffic use cases.
• Heavy reliance on Google’s Gemini File Search, potentially limiting customization and increasing vendor lock-in.
• Primarily a hosted SaaS with no mention of self-hosting options, which may not suit organizations with strict data residency or privacy requirements.