Cassidy is a no-code AI agent and workflow platform built for internal business teams that want to automate knowledge work — answering questions from company data, running scheduled reports, or triaging inbound requests — without hiring engineers to build custom integrations.
Who it's for
Cassidy is aimed at operations, IT, HR, and customer-facing teams inside mid-size and larger companies that need agents to pull from internal knowledge (documents, wikis, CRM records) and act on it, rather than developers building a bespoke agent product. It fits organizations that already have scattered internal data and want an AI layer that can search and act across it without a large implementation project.
How it works
Teams build agents through a no-code interface, connecting them to internal knowledge sources and giving them the ability to trigger on a schedule or in response to an event, such as a new support ticket or form submission. Cassidy supports multiple underlying AI models so teams aren't locked into a single provider, and agents can act with a degree of autonomy — running workflows and pulling in information — before handing back to a human for anything sensitive or ambiguous. An API is available for teams that want to embed Cassidy's agents into other internal tools.
Pricing
Cassidy is sold on a paid model with no published free tier or flat starting price in our data; billing is metered through a credits system tied to agent usage. Because there's no public self-serve price list, teams should request current pricing directly from Cassidy and budget based on expected agent volume and complexity rather than assuming a fixed monthly figure.
Strengths and trade-offs
Cassidy's strength is being purpose-built for internal knowledge work: no-code setup, flexible scheduling and event triggers, multi-model support so teams can pick the best model for a given task, and SOC 2 compliance for enterprise trust. The trade-off is that pricing isn't transparent up front, and as a credits-billed, cloud-only product, cost and hosting flexibility are less predictable than with a flat-fee or self-hostable alternative. For internal teams that want to put AI agents to work on company knowledge without a large engineering lift, Cassidy is a reasonable option alongside similar internal-agent platforms like Glean and Dust. Teams considering it should weigh the credits-based cost model against their expected agent usage before rolling it out broadly.