In most companies, getting a specific data answer means filing a request and waiting for a data analyst to write a query — a bottleneck that grows as more people across the company want data-driven answers. Chat-with-your-data tools promise to remove that wait, but many are prone to confidently making up numbers. Upsolve AI's pitch is doing this properly: fast AND grounded in your actual data. Upsolve AI is a platform for building and deploying "data agents" that answer natural-language questions about a company's data, built around a three-layer context architecture (Structure, Meaning, Trust) specifically designed to reduce hallucinated answers. It connects to 30+ SQL databases (Snowflake, BigQuery, Redshift, Databricks, Postgres, MySQL, and more), can import an existing dbt project, and deploys across Slack, Teams, Claude, ChatGPT, Cursor, or embedded via SDK. Agent Studio gives data teams observability into every question asked, full conversation tracing, and a built-in evaluation agent that grades answers for hallucination before they reach end users. It's a Y Combinator (W24) company founded by a team that built HyperAuto at Palantir.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Équipes trading (matières premières/énergie), supply chain, cabinets de conseil, e-commerce/retail, entreprises | — | |
| 2 | Équipes SaaS Product/Revenue en petite et mid-market cherchant l'analytique de cohortes et churn sans BI complexe | — | |
| 3 | Website owners and teams wanting cookieless analytics with revenue insight | — | |
| 4 | Financial analysts and quantitative researchers needing SEC XBRL fundamentals | — | |
| 5 | Website owners and teams wanting privacy-first analytics with session replay and uptime monitoring | — | |
| 6 | Développeurs voulant présenter leur portfolio GitHub de façon originale, ou trouver des issues open-source abordables | — | |
| 7 | Développeurs construisant des pipelines de capture de données sans infra lourde | — | |
| 8 | Équipes data et ingénierie nécessitant souveraineté des données et contrôle d'infrastructure | — | |
| 9 | Data engineers, analystes, praticiens ML voulant prototyper des pipelines rapidement | — | |
| 10 | Analytics engineers et équipes data utilisant dbt, ayant besoin de données de test réalistes sans accès aux données de production | — | |
| 11 | Développeurs et ingénieurs data ayant besoin de générer de gros volumes de données de test cohérentes | — | |
| 12 | Consommateurs européens, chercheurs et journalistes suivant les comparaisons de prix et indicateurs économiques dans l'UE | — |
Instead of learning SQL or waiting for someone on the data team to build a chart, Findly lets a supply chain manager or trader type a plain-English question about their data — "how did shipping costs change last month" — and get back an answer, a chart, a
Turns the customer and revenue data already sitting in your Google Sheets into churn, retention and cohort analytics in seconds, no formulas or BI tool required.
Cookieless, privacy-first web analytics with an AI chat interface — a paid, open-source alternative to Google Analytics.
Extracts standardized S&P 500 fundamental financial data directly from SEC XBRL filings for financial analysis.
Privacy-first, cookieless web analytics with session replay, error tracking, and uptime monitoring, open-source and self-hostable.
Turns your GitHub repositories into a walkable 3D town — stars and forks become building height and width — so you can explore a portfolio, or find beginner-friendly open-source issues, as a game instead of a list.
Python library that captures streaming data durably into Iceberg tables with no broker, daemon, or catalog service to run.
Open-source ETL platform that builds data pipelines visually or in code and runs them on DuckDB, with no vendor lock-in.
Open-source visual builder for data and ML pipelines that lets you preview each transformation live and export clean pandas/Polars Python code.
A command-line tool that reads a database schema and generates a full, realistic fake dataset plus a ready-to-run dbt project — no production data or manual scaffolding needed.
A synthetic data generator that lets you describe your data model in a simple language, then compiles it into fast native code to produce large, coherent test datasets.
A free daily dashboard comparing fuel, electricity, groceries, wages, and other cost-of-living numbers across all 27 EU countries.
