AI transformation in enterprises vs. startups

McKinsey and BCG both report generative AI moving from experiments to line-of-business ownership — but scale breaks naive rollouts.[[mckinseyGenAi2024]][[bcgAi2024]] Deloitte's enterprise surveys echo the same friction: governance, skills, and fragmented tools.[[deloitteEnterprise2025]] Startups feel a different pain: there is no ops team to wire memory, yet the founder still wants an agent that knows last week's pivot.

Enterprises: control the blast radius

• Identity — SSO, SCIM, RBAC; agents inherit real permissions.
• Residency — VPC, dedicated cloud, or air-gapped when contracts require it.
• Audit — who approved what Mor proposed; export for security reviews.
• Phased memory — one division pilot before global Slack connect.
• Vendor fatigue — one brain across Jira, ServiceNow, Teams, and GitHub instead of six AI copilots with six memories.

Startups: compress time to context

• Connect Slack, GitHub, and calendar in an afternoon.
• Let the CEO agent draft the weekly update from actual threads.
• Stay local-first until investors or customers ask for shared cloud.
• YC's Company Brain RFS is aimed squarely at this stage — critical know-how scattered, team small, stakes high.[[ycRfs]]

Same pattern, different packaging

Both need a company brain — not another chat tab. Enterprises buy deployment and governance; startups buy time. Morrow's Enterprise page covers dedicated infrastructure and SLAs; Business and desktop cover fast adoption.

Large org? We run workshops, connect the first business unit, and train admins. Small team? We still help you wire integrations on a demo — you should not spend sprint zero building memory plumbing.