Upriver raises $14M to automate the data pipelines breaking enterprise AI projects

Upriver raises $14M to fix AI's enterprise data problem

The Israeli startup automates the pipeline plumbing that buries data teams. Its founders built large-scale intelligence systems before deciding every company had the same problem. Most enterprise AI projects do not fail because the model is bad. They fail because the data feeding it is a mess: broken pipelines, mismatched systems, and context locked in one engineer's head. Upriver, an Israeli startup, has raised $14M to automate the cleanup, betting that this dull but critical layer is where the AI era is really won or lost. The seed round was led by Valley Capital Partners and Hetz Ventures. Just as telling is the angel list, which reads like a roll call of the data-tooling world: Lew Cirne, who founded the observability giant New Relic; Abe Gong of the data-quality project Great Expectations; and the founders of the Israeli data-security unicorn Cyera. Upriver says it is already used by Unity and the media group DMGT, and partners with Databricks and Snowflake. Plumbing for the AI era Upriver pitches itself as an "AI data engineering platform": an agent that connects to a company's full data stack, Snowflake, Databricks, BigQuery, Airflow, dbt, then explores it, builds and validates pipelines, fixes them when they break, and encodes the "tribal knowledge" that usually lives in people's heads. The promise is that data engineers stop spending their days investigating broken pipelines and stitching together tools that were never built to talk to each other, and instead decide what the data actually means. The founders come at it from an unusual place. Ido Bronstein, the chief executive, and Omri Lifshitz, the chief technology officer, spent a decade building large-scale intelligence systems, work Business Insider reports was done for the Israeli military, before concluding that every company on a modern cloud stack was living the same problem they were. The new funding will go into engineering, sales, and enterprise deployments. The timing fits a broader correction. After two years of spending on models and chips, companies are scrutinising what AI actually returns, and a recurring answer is that it falls over on bad data. A wave of startups, from Capsa in private equity to Upriver in the data stack itself, is selling the same underlying promise: clean, trustworthy data is the thing standing between an AI pilot and something that works. It is a $14M seed, early and unproven at scale. But the bet, that the foundation matters more than the model, is one a lot of money is starting to share.

Upriver raises $14M to automate enterprise data engineering for AI

Upriver raises $14M to automate enterprise data engineering for AI Israeli data engineering startup Upriver Data Ltd. today announced it has raised $14 million in new funding to automate the data work that enterprises depend on to make artificial intelligence projects succeed. Founded in 2024 by Chief Executive Ido Bronstein and Chief Technology Officer Omri Lifshitz, Upriver has built what it calls an artificial intelligence-native platform that connects to an organization's full data stack, resolves data quality issues and maintains pipelines automatically. The company pitches the result as a reliable data foundation that AI systems can run on without constant manual upkeep from engineering teams. The platform handles data engineering workflows end-to-end, including finding and resolving quality problems, maintaining pipelines and creating new datasets. Upriver says it pairs a context engine that maps the structure of an organization's data with a coordinated system of agents that validate results across fragmented data stacks. It is also accessible through AI development tools, including Anthropic PBC's Claude and Cursor. The funding comes amid a backdrop of stalled AI deployments, many of them traced back to poor data rather than the models themselves. Gartner Inc. reported in April that 38% of technology leaders pointed to poor data quality or limited data availability as a direct cause of AI project failure. The firm separately found in January that at least 50% of generative AI projects had been abandoned after the proof-of-concept stage, with data quality among the leading causes. "We're seeing enterprises invest heavily in AI but struggle to see real impact because their data simply isn't ready," Bronstein said. "We built Upriver to take that burden off data teams entirely. Our goal is to make data infrastructure invisible so enterprises can extract their organizational knowledge from the messy data and finally get from AI what was originally promised." Upriver counts Unity Software Inc. and Daily Mail and General Trust plc among its customers and has partnerships with data platforms including Databricks Inc. and Snowflake Inc. Web search infrastructure firm Nimble Way Ltd. reported a 60% productivity increase after deploying the platform, according to Chief Executive Uriel Knorovich. The seed round was led by Valley Capital Partners and Hetz Ventures, with angel backing from New Relic Inc. founder Lew Cirne, Cyera Ltd. founders Yotam Segev and Tamar Bar-Ilan and Great Expectations Labs Inc. founder Abe Gong. Guy Fighel, a partner at Hetz Ventures, said the startup goes deeper than rivals that sit on top of the data stack. "Most platforms in this space sit on top of the stack. Upriver goes into it, and that's the difference between cleaner dashboards and AI you can actually put into production," he said in a statement. Upriver said it will use the capital to expand its engineering and go-to-market teams, deepen product development and accelerate enterprise deployments.