How ChatData Sync works

Most chatbot ideas fail before they start — not because the idea is bad, but because the gap between "I want an assistant that tracks X" and "here is a working assistant that tracks X" requires a database schema, a permissions model, workflow state design, API actions, and repeatable deployment. ChatData Sync fills that gap from a plain-English description.

The problem ChatData Sync solves

Building a useful AI assistant for a real workflow requires more than a good language model. It requires:

Schema design — what tables, fields, and relationships should exist?
Permissions — who can read or write which records?
Workflow state — how does a job move from open to complete to invoiced?
Assistant actions — what can the assistant actually do when a user talks to it?
Deployment — how does any of this run reliably without a backend team?

ChatData Sync generates all of it from the description you provide. You never touch a database, write an API, or configure a server.

Three steps from idea to working assistant

Describe what you want to track

Write a plain-English description of the workflow. "Track customers, vehicles, repair orders, parts used, estimates, and invoice status" is enough. You do not need to know field types, indexes, or data modeling patterns. ChatData Sync infers the structure from your intent.

Review the generated schema — before anything is created

ChatData Sync shows you every table, field, relationship, and role it will create. You see the full data model before a single record is written. Adjust field names, remove tables you do not need, or approve as-is. Your tracking space is live the moment you confirm.

Connect your assistant and start talking

ChatData Sync generates a GPT Action connection string and an MCP endpoint for your tracking space. Each includes a scoped security token with strict tenant boundaries. Paste once into your assistant. From that point, log records, retrieve entries, and ask summary questions through conversation — no forms, no spreadsheets.

What gets generated for you

When you approve a schema, ChatData Sync creates and manages:

Data model (tables and fields)Structured from your plain-English description
RelationshipsCustomers → Vehicles → Repair Orders, etc.
Role-based access controlOwner access and scoped assistant tokens
Assistant action endpointsCreate, read, update, list, and summarize
GPT Action connection stringPaste once into any ChatGPT custom GPT
MCP endpointCompatible with Claude and other MCP assistants
OpenAPI contractMachine-readable schema aligned to your data model
Tenant isolationYour data is never shared with other users' spaces

Works with your assistant of choice

ChatGPT

Paste the GPT Action string into your custom GPT settings. Ready in under two minutes.

Claude

Connect via the MCP endpoint. Works with Claude.ai and the API.

Gemini

Connect using the OpenAPI contract for Gemini tool configuration.

See it with a real workflow

Auto repair shop

Customers, vehicles, repair orders, inspections, parts, estimates, approvals, and technician notes — generated from one description.

Service businesses

Pet sitters, tutors, handymen, and freelancers — log clients, jobs, sessions, and invoices through conversation.

Try it free — no credit card required

Describe your workflow, review the generated schema, and connect your assistant. The Free plan includes one tracking space and 200 assistant actions per month.

Describe your first workflow