Jsonify is an AI-driven data extraction and monitoring platform focused on acquiring, processing, and validating data from public websites and mobile apps, then continuously running these extraction pipelines.
Purpose
Jsonify is designed to help users reliably collect public data from the web and keep datasets continuously updated. It is suitable for teams that need to regularly monitor prices, menus, property listings, market quotes, and similar scenarios.
Main capabilities
- AI data engineer Jason: Users describe the data they need in natural language, and Jason plans data sources and checks, builds the extraction pipeline, and remembers how it works.
- Automatic pipeline operation: Pipelines run automatically on the schedule set by the user, apply the same fields and checks on each run, publish immutable dataset versions, and retain the source, timestamp, and pipeline version for every row.
- Automatic repair: When a website or app update causes a run to fail, Jason diagnoses the cause, fixes the pipeline, validates samples, and then resumes the schedule.
- Data validation: Every row of data undergoes checks such as type, null values, and range, and only rows that pass the checks and enter the dataset are counted.
- Multi-source processing: Supports websites and mobile apps, can scrape multiple sources in parallel, and match products by identifiers such as barcodes.
- Data delivery: Datasets can be delivered on a schedule to Google Sheets, Excel, Snowflake, S3, Postgres, and Webhooks, and change alerts can be sent via Slack and email.
- Assistant integration: Can be connected to AI assistants through the ChatGPT plugin store, the Claude connector directory, or MCP to use checked data.
How to use
- Describe the need: Describe the problem in one sentence or list the data already being tracked.
- Agent builds: Jason builds the extraction steps and validates them with samples.
- Pipeline runs: The pipeline runs on schedule, applies the same fields and checks, and publishes a new dataset version.
- Agent repairs: Jason diagnoses failures, fixes the pipeline, and resumes after validating samples.
Users can also connect ChatGPT, Claude, Microsoft 365 Copilot, or other assistants that support remote MCP, and request dataset creation through natural language.
Suitable scenarios
- Retail price tracking: View competitor prices, promotions, and inventory changes.
- Restaurant menus: Understand which venues list products, pricing, and menuchanges.
- Property listings: Track new listings and price cuts on portals and agency websites.
- Market quotes: Monitor seller prices, shipping fees, and ratings for the same product across different markets.
- Other scenarios include insurance, car rental, and utilities.
Limitations
- Specific pricing, a complete list of platform compatibility, performance guarantees, or detailed usage steps are not provided in the public materials.
- Free for 100 rows per month, with per-row billing after that and a minimum monthly fee of $49. Building, previewing, and repairs are free.
- Supports more than 70 languages and any public web or app data worldwide.
- Enterprise security features such as SOC 2 Type II and GDPR DPA can be obtained by contacting the company.
- Connecting an AI assistant requires the assistant to support a remote MCP server and OAuth login.
- The retailers and figures mentioned in the text are illustrative examples.
Other information
- Since 2023, billions of data points have been extracted for teams.
- Extraction accuracy is 98.7%, median pipeline repair time is 18 minutes 46 seconds, and 6,178 global sources have been learned.
- Enterprise security: SOC 2 Type II audit, GDPR DPA and SCC, EU AI Act transparency, and anonymization of personal data.
