The Problem With Generic AI

Most AI tools are built on public knowledge — they know about the world, but they don't know about your company. Businesses have enormous amounts of internal data locked in wikis, CRMs, support tickets, sales documents, and internal tools, and off-the-shelf AI solutions can't access any of it. The result is AI that gives generic answers rather than context-aware ones, forcing employees to manually bridge the gap between what the AI knows and what they actually need.

What Cassidy Builds

Cassidy is an AI platform that lets businesses build automated workflows powered by their own internal data. Rather than deploying a generic chatbot, companies connect Cassidy to their existing tools — Notion, Salesforce, Zendesk, Google Drive, and more — and create AI assistants and automated workflows that actually understand the business. A support team can automate ticket triage using their own resolution history. A sales team can generate proposals grounded in their own product documentation and deal history.

The platform is designed to be no-code, enabling non-technical teams to build and deploy sophisticated AI workflows without engineering support. This accessibility, combined with deep integrations across the modern business software stack, positions Cassidy as infrastructure for the AI-augmented enterprise rather than just another chatbot.

Funding and Traction

Cassidy raised a $3.7M seed round in August 2024, with the funding intended to accelerate product development and expand its integration library. The company has attracted customers across industries who are looking to move beyond generic AI tools and build automation that leverages their proprietary data as a competitive advantage. By grounding AI in company-specific context, Cassidy addresses one of the most consistent frustrations teams report when adopting AI in the workplace: the gap between what AI can do and what it actually knows about your business.