Alkera AI

Bringing confidence and speed to your agentic data stack. Backed by @ycombinator and @ParetoHoldings.

Alkera is a data engineering, analysis, and science agent aimed at the people who actually query the warehouse, meaning engineers, analysts, and scientists who need answers they can trust rather than plausible-looking code. The pitch behind this launch is that general coding agents can write SQL and Python that runs without errors, but verifying the output is correct is where they fall down, so Alkera was built natively across the entire data stack with strict data governance, reasoning over exact column-level lineage, and a living knowledge base built from the team's work. The launch is timely because Alkera currently sits at the top of UC Berkeley's DataAgentBench, the emerging benchmark for data agents, with a Pass@1 score of 83.28 percent as of July 16, 2026, ahead of SCRIBE (Actioneer), Spacedock (Recce), Altimate Code, Claude Code, and PromptQL. The product runs in the IDE, terminal, or browser, plans complex jobs as a graph so dozens of sub-agents can execute in parallel on local machines or remote CPU and GPU nodes, and connects flat files, warehouses like Snowflake, Databricks, BigQuery, and Redshift, plus transformation and BI layers such as dbt, Airflow, and Power BI. A cross-stack lineage engine lets a user trace one column from source through dbt models to a downstream dashboard and see the blast radius of a proposed change before it runs, while every bash command and SQL query is risk-analyzed under fine-grained permissions. Alkera is part of Y Combinator's S26 batch and is also backed by Pareto Holdings, with Rick Gao, a Yale alum based in the San Francisco Bay Area, serving as CEO . For teams evaluating where AI agents can safely touch production data, this launch is worth a look precisely because Alkera is optimizing for correctness and lineage awareness rather than raw code generation speed.

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