One of the biggest challenges is populating your product with your customer’s live data as quickly as possible, so that they can start using it, have that ‘aha’ moment and see the value,” Pandya said. “Nowhere is this data silo problem more painful than when onboarding customers. Another client, a hospitality brand, is leveraging Osmos to bring property listings into its operational systems. One brand, an ecommerce company, is using the platform to automate the ingestion of catalog data from multiple distributors and vendors. Osmos counts Bluecore, Mosaic, and Blissfully among its customers. The users fix the errors with more examples and formulas, and the system relearns the transformation logic to handle such exceptions in the future.” New data shows up, and if something breaks, the system notifies the relevant users. the system to learn transformations and clean up data. “More importantly, we have turned into a seamless full-feedback loop. It also ensures that the data that’s uploaded is not just schematically valid, but also passes any business rules ,” Pandya explained. “Using this technology, Osmos is able to automatically learn complex transforms including conditionals, complex multi-column joins, and splits. This explainability is a key differentiator, Pandya believes, because it confers confidence that the system will do the right thing rather than make guesses based on arbitrary confidence values. Companies only need to provide a couple of example rows of what the output should look like, and then Cosmos generates a debuggable data transformation program. Unlike most AI-based systems, Osmos’ technology doesn’t require huge amounts of training data from customers, Pandya says. When it to working with external data and systems … here no end-to-end solution to simplify data collaboration for the modern era … ost solutions in the market that deal with data primarily target technical users - the non-technical frontline teams that actually deal with customers, partners, and vendors make do with Excel or nothing.” Transforming data with AI “Cross-company relationships are becoming more important than ever … a lot of ‘automation’ companies focused on connecting systems, automating workflows, and moving data within the four walls of an organization. “During our time at Google, we noticed a few key trends,” Pandya told VentureBeat in an email Q&A. Prior to Google, Pandya headed the Azure Cosmos DB rollout at Microsoft and worked on wireless mesh technology. Pandya and Naresh Venkat founded Osmos in late 2019 after a stint at Google Cloud, where they led AI and machine learning initiatives. The company’s no-code platform provides users a way to bring in data from their systems or build pipelines to data, leveraging a real-time data transformation engine that automatically learns how to reconcile data. Osmos’ goal is to ease the analytics burden by eliminating data silos, allowing apps to talk directly to each.
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