SDS produces a machine learning tool for the financial services industry which dramatically reduces the cost of harvesting and cleaning data. The company was founded in 2018 by a team of analysts and investment professionals who had formerly worked as part of a development group in a San Francisco angel capital office. Previously, the team had been tasked with building various in-house data solutions, including one to supply structured XBRL financials to subsidiary Revere Data (later acquired by FACTSET). It was through this experience that the basis of SDS as a standalone provider was born. The lightbulb moment for the team came when it moved beyond standard financials (Income Statement/Balance Sheet/Cash Flow) and began mining esoteric tables buried in 10K/Qs, such as REIT FFO (Funds From Operations) for a hedge fund manager client. Although outside of the ordinary workflow, SDS tools easily accomplished the task with a skeleton crew of staff and a microscopic budget (compared to incumbent data purveyors). At that point, the decision was made to commercialize. Since 2018, SDS has been in stealth mode, quietly improving its semantic parsing engine and its user interface, while preparing for a public launch. We intend to disrupt a well established and very static industry which currently relies mostly on manual processes to populate databases. Through automation, our platform improves the efficiency of collecting, maintaining, and updating financial information by an order of magnitude. SDS anticipates an initial release in Fall of 2020.