Excited to share more publicly what @benhamner and I have been working on: techcrunch.com/2025/10/22/su… We are building a knowledge graph for GTM data & have early customers such as @elastic, @figma and @Snowflake

Kaggle launched an LLM eval product kaggle.com/benchmarks This has the potential solve the biggest challenge in the LLM ecosystem: strong and diverse evals

Looking at job posts over the last year, it looks like Amazon is making the broadest AI investment. 228 teams across the company posted jobs with GenAI projects over the past year, considerably more than any other company. blog.sumble.com/companies-wi… Most interest is the breadth of teams and use cases. They made posts from the core research teams, Alexa, customer service, seller experience, fulfillment, and catalog selection teams (full list: sumble.com/l/JrsA4zNSp4). Some examples: - Creative X Team: generating high-quality text, images and video for advertisers (sumble.com/l/EHF2RZQRYD) - Geospatial Science Team: for global address parsing and validation (sumble.com/l/h7GWV4t9JU) - Selection and Catalog Systems Team: improve the completeness and correctness of product data for Amazon shoppers (sumble.com/l/uaddsqaD4v)

The overlooked GenAI use case: cleaning, processing, and analyzing data. blog.sumble.com/the-overlook… Job post data tell us what companies plan to do with GenAI. The most common use case is data analytics projects. Examples: - AstraZeneca: using LLMs on freeform documents to structure results from their Extractables & Leachables testing (sumble.com/l/FgehjrgnvN) - Trafigura: The Document AI team is using LLMs to extract data from a corpus of commodity trading documents to generate credit reports (sumble.com/l/6bY7mhyAHd) The startup ecosystem is overlooking this use case, instead focusing on other areas such as customer support, sales & marketing and code gen.