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January 21: From BI to AI (DataRobot, Diversio, Domino, Prophecy, Vectice)

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Prophecy raises Series A to Industrialize Data Refining

Prophecy, a low-code data engineering platform, raised $25M in Series A funding this week. The round was led by Insight Partners, with other participants from existing investors Berkeley SkyDeck and SignalFire, and new investor Dig Ventures. The funding will go towards building out the platform, as well as investing in the go-to-market side. Prophecy seeks to standardize data refinement for use at scale, making the process more predictable and visible.

Vectice Announces $15.6M in Seed and Series A Funding

On January 18, Vectice, a data science knowledge capture company, announced it had raised a $12.6M series A round. The round was co-led by Crosslink Capital and Sorenson Ventures. Additional participants included Global Founders Capital (GFC), Silicon Valley Bank, and Spider Capital. Vectice will use the funds to further expand its team, and to onboard select accounts into their Beta program. Vectice automatically captures the assets that data science teams generate throughout a project, and generates documentation throughout the project lifecycle.

Diversio Announces Series A Funding

Also this week, Diversio, a diversity, equality, and inclusion platform, raised $6.5M in series A funding. Participants included Chandaria Family Holdings, First Round Capital, and Golden Ventures. Plans for the funding include expanding the sales and client success teams, accelerating product development, and amplifying marketing efforts. Diversio combines analytics, AI, and subject matter expertise to understand where DEI efforts at organizations are getting derailed, and offer action plans for setting and meeting DEI goals.


DataRobot’s State of AI Bias Report Reveals 81% of Technology Leaders Want Government Regulation of AI Bias – DataRobot AI Cloud

On January 18, DataRobot released its State of AI Bias Report, assessing how AI bias can impact organizations, along with ways to mitigate said bias. Common challenges organizations face include the inability to understand the reasons for a specific AI decision, or the correlation between inputs and outputs, along with the difficulty of developing trustworthy algorithms and determining what data is used to train a given model. All of these challenges have led to some combination of lost revenue, customers, and employees, along with legal fees and reputation damage to the company; organizations are seeking guidance to avoid these issues.


Domino Data Lab Hosts January 26 Virtual Event: Unleashing Exceptional Performance with Data Science

On Wednesday, January 26, Domino Data Lab will host a free one-hour virtual event: “Unleashing Exceptional Performance,” focusing on data science. Featured speakers include surgeon and author Dr. Atul Gawande, and Janssen Research and Development’s Chief Data Science Officer and Global Head of Strategy and Operations Dr. Najat Khan. There will be two sessions to accommodate various timezones, one at 1300 GMT and one at 11 am PT/2 pm ET. To register for the event, please visit the Domino event registration site.