Stop switching apps — connect your AI assistant to all workflows via connectors

Knowledge workers in small-to-medium teams waste time switching between apps, copying context, and rebuilding simple automations; this is especially acute for the 20 million SMB teams that already spend roughly $2,500 per year on integrations and AI productivity tooling. The result is fragmented AI value—LLMs are used for chat but can’t reliably take actions, recall private context, or automate cross-app workflows without brittle point-to-point integrations. You could build a unified assistant platform that connects to all major SaaS and on-prem systems via a catalog of low-code connectors and developer SDKs, enabling LLM-driven actions, persistent recalls, and composable automation templates. Deliver a hybrid deployment model (cloud, private cloud, on-prem) with built-in vector stores, audit logs, RBAC, and data residency controls so teams can run sensitive workflows without leaking data. Focus on an easy authoring experience (drag-and-drop flows plus code hooks), an initial library of 50+ vetted connectors, and a marketplace API so partners can contribute integrations. This market is attractive now because the addressable opportunity exceeds $50 billion (20M SMBs × $2,500) and buyer priorities (LLM orchestration, composability, and privacy) align with a product that stitches models into workflows rather than just chat. To stand out you’ll need enterprise-grade security, fast time-to-value, and strong go-to-market partnerships, but expect heavy competition from incumbent integration platforms and major cloud vendors—winning will require disciplined product focus, clear privacy guarantees, and a realistic sales and developer adoption strategy rather than relying on product alone.