You can build a CRM with AI by describing your sales process, reviewing the generated data model, customizing workflows, and deploying dashboards and AI agents for daily operations. The key is to describe the real business process, not just ask for a generic CRM.
Step-by-step process
Start by describing the business goal, users, records, process stages, approval rules, dashboards, and AI assistant tasks. Review the generated structure before inviting the wider team.
Example prompt
Write a prompt that includes the system purpose, required tables, user roles, workflow rules, reports, and integrations. Specific business language produces a better first version than a generic request.
Generated tables and fields
Review each generated table for ownership, required fields, status values, relationships, validation rules, and permissions. Good data structure is the foundation for reliable workflows and AI agents.
Recommended workflows
Add workflows for submission, review, approval, exception handling, notifications, reporting, and closure. Start with the most common path, then add edge cases after the first launch.
Common mistakes
Avoid vague prompts, too many fields in the first version, missing status definitions, unclear ownership, and dashboards that do not map to real operating decisions.
Frequently Asked Questions
What should my CRM prompt include?
Include lead sources, sales stages, users, deal fields, approvals, reports, and the follow-up tasks your team performs every week.
How long does the first CRM version take?
A first version can be generated quickly, then refined with business users before launch.
Teams can use this page as a planning checklist, then turn the same requirements into tables, workflows, dashboards, APIs, and AI agents in INFORMAT.