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Founded by Nicole Lu & Savannah Tynan
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.
After studying CS at MIT, Nicole worked at Citadel and McKinsey, and Savannah worked at Bain. They've dealt with this problem first hand and were amazed that there weren't good solutions.
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, sieve uses 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 sieve achieve the level of accuracy hedge funds need—something that AI-only approaches are unable to achieve.
They offer direct API access and access via other tools like Excel. Watch below to see how the excel integration works!
sieve is able to replace manual data cleaning workflows:
In the founders first week of YC, they were told they need to be at least one of: better, faster, or cheaper.
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