Go from idea to dataset in minutes.
Build datasets in the UI or via MCP in a fully self-serve way. Describe what you need in plain language and get a structured dataset in minutes. No code required.
Write and run ETL code natively in Kadoa. Migrate existing pipelines in and let Kadoa handle scaling, monitoring, and self-healing.
Push data directly into S3, Snowflake, BigQuery, or any data warehouse. No glue code to maintain.
Get real-time updates of market-moving data changes via Slack, email, or webhooks.
In finance, if data is wrong or late, someone feels it. We build the most reliable datasets for investors.

Every value is source-grounded and audit-ready. Click any data point to see the exact page, paragraph, or cell it came from.

We check for completeness, plausibility, and schema adherence on every run. Add your own domain rules on top. Every data point is validated before data reaches your system.

When a workflow breaks, Kadoa detects it and fixes the code automatically. Every fix is logged so you can see what changed, when, and how it was resolved.

If automated recovery fails, you get notified immediately with full context: what broke, what was tried, and what needs human review.
Track success rate, throughput, and incidents for every workflow in one dashboard, or stream metrics into your own monitoring stack.

Our agents generate and maintain deterministic code and do not produce black-box LLM outputs.
You stay in full control of your mission-critical pipelines.
Decomposes tasks and generates scraping code.

How investment firms transform their data stacks to make best use of AI.
What hedge funds actually need to build at scale: the signals worth tracking, the pipeline that holds up, and the compliance layer that doesn't block every new source.
AI and compute scale are making it possible to source public data at scale without a large team or an expensive vendor contract.