sieve helps hedge funds extract and clean data from any source directly into their existing tools
Focus on differentiated analyses and never think about data cleaning again
The problem
Right now, the most sophisticated hedge funds pay over-qualified data engineers to spend hours a day on the under-levered task of data cleaning. It's crazy to anyone outside of the industry, but in finance even earnings dates (the date a company reports earnings) are considered a known hard problem.
Our ask
We've solved this problem and our ask to the YC community is - connect us with anyone you know who works in the investing world and uses data (should be all of them). You can email us at founders@usesieve.com.
Who we are
After studying CS at MIT, I worked at Citadel and McKinsey, and Savannah worked at Bain. We've dealt with this problem first hand and were amazed that there weren't good solutions.
What we've built
sieve lets hedge funds replace manual review in their data pipelines with a simple API call, so their engineers and analysts can get back to more differentiated work. Behind the scenes, we use AI to find and retrieve the appropriate source documents and to extract the requested data. Each data point is reviewed by a team of expert reviewers before being returned to the client. This lets us achieve the level of accuracy hedge funds need, and that AI-only approaches aren't able to achieve.
We offer direct API access and access via other tools like Excel. Watch below to see how the excel integration works!
What the early results look like
- sieve is able to replace manual data cleaning workflows:
- accurately (100% match to data that was hand-collected internally)
- more scalably (weeks of full-time work to review data became a passive background task for the data scientist)
- more cheaply (easily 60-70% cheaper than existing options, even when that existing option is BPO outsourcing)
In our first week of YC, we were told that we need to be at least one of: better, faster, or cheaper.
