TalkingSchema is an AI-powered data modeling tool and ERD copilot for engineers, data teams, and architects. We are building AI tools that collapse the gap between requirements and production-ready database schemas.
Our Mission
We’re building AI tools that collapse the gap between requirements and production-ready database schemas — letting engineers design ERDs, star schemas, data vault structures, and migration plans from plain language in minutes instead of days.
The Product
TalkingSchema is an AI-first ERD tool. You describe your database requirements in plain language — TalkingSchema’s AI copilot proposes schema changes through a structured checklist (Plan Mode) before anything is applied to the canvas. Every proposed change — add table, rename column, create index — is surfaced as a reviewable item, with a color-coded diff on the ERD.
TalkingSchema exports to 12+ formats including SQL DDL (PostgreSQL, MySQL, SQLite, MSSQL), Prisma, Drizzle, TypeScript/Zod, SQLAlchemy, TypeORM, OpenAPI 3.0, and GraphQL SDL. It supports data warehouse modeling patterns including Kimball star schema, Inmon 3NF, Data Vault 2.0, slowly changing dimensions (SCD Types 1–6), and snowflake schema.
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.