Most schemas begin as conversations: a product idea, a warehouse question, a migration plan, a half-remembered business rule. TalkingSchema turns those conversations into database designs your team can inspect, edit, share, and ship.
ERD tools are good at drawing tables. The harder problem is knowing what the tables mean. TalkingSchema is built for that gap: the space between raw requirements and a schema that reflects the real business, not just valid SQL.
TalkingSchema is an AI-powered modeling workspace for engineers, data teams, and architects. Describe what you are building in plain language; the assistant proposes a schema, explains the changes, and shows the result on an interactive ERD canvas before it becomes part of your model.
From there, the same model can become SQL, Prisma, Drizzle, TypeScript/Zod, OpenAPI, GraphQL, or a warehouse design using patterns like Kimball, Data Vault, snowflake schemas, and slowly changing dimensions. One conversation becomes a working schema your team can reason about.
Karan built TalkingSchema to collapse the gap between requirements and production-ready database schemas. He has deep expertise in relational database design, data warehouse architecture (Kimball, Inmon, Data Vault 2.0), and AI-assisted schema automation.
Mishall leads engineering at TalkingSchema. She specializes in software engineering, AI systems, LLM integration, and full-stack development. She built the core AI pipeline, streaming architecture, and React canvas that powers TalkingSchema.
TalkingSchema is designed with data privacy as a first-class concern. We store schema structure only — not the underlying data in your database tables. All subprocessors are SOC 2, GDPR, and CCPA compliant.
For full details on data handling, security practices, and compliance, see our Security & Compliance page.
For product support, feature requests, security reports, or general inquiries: support@talkingschema.com