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Webhook debugging tool that captures every delivery, shows why it failed and lets you replay the exact payload after a fix.
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Capture every webhook delivery with status and attempts
- ✦Inspect request, response and headers
- ✦Replay and retry exact payloads
- ✦Failure categorization by reason
- ✦Group repeated failures into incidents
- ✦Slack and webhook alerts
- ✦Natural language to SQL conversion
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- →Debugging failed Stripe, GitHub or Shopify webhooks
- →Recovering dropped events
- →Monitoring webhook reliability
- →Alerting on failures before users notice
- →Generating SQL queries from text descriptions.
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms