Secondmind vs Dataiku

Dataiku has a disclosed valuation of $3.7B, while Secondmind's valuation is not publicly available, making a direct size comparison difficult. Dataiku employs 1000+ people.

Dataiku has raised more in total funding at $1B, compared to Secondmind's $25M — a gap of $975M. Combined, the two companies have completed 5 known funding rounds.

Dataiku leads with an Awaira Score of 90/100, while Secondmind sits at 45/100. That 45-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Secondmind was founded by Eric Bax in 2019. Dataiku was founded by Florian Douetteau in 2013. Visit each company's profile on Awaira for a full founder biography.

Secondmind: Secondmind develops Bayesian machine learning optimisation technology for engineering applications, with a primary focus on automotive powertrain and vehicle systems calibration. The Cambridge company builds probabilistic machine learning tools that help automotive engineers optimise complex, multi-variable systems such as engine management, transmission control, and electrification systems with fewer physical experiments and less calibration time than traditional approaches.\n\nThe company raised approximately $25 million in a Series A round and acquired Prowler.io, a multi-agent reinforcement learning startup from Cambridge, in 2021 to expand its AI research capabilities. Secondmind customers include major automotive OEMs using the platform to reduce the number of dyno tests required for powertrain calibration, translating directly into reduced development costs and faster time-to-production for new vehicle programmes.\n\nSeconmind operates in the engineering AI optimisation market, competing with specialist automotive AI vendors and general-purpose Bayesian optimisation tools. The automotive calibration market is driven by increasing powertrain complexity as the industry transitions to hybrid and electric architectures, which require calibrating interactions between internal combustion engines, electric motors, and battery management systems that generate dramatically more control parameters than traditional powertrains. Cambridge University research partnerships provide the company a continuing source of methodological development in Bayesian and probabilistic machine learning. Dataiku: Dataiku builds a collaborative data science and machine learning platform that enables data teams, business analysts, and AI engineers to build, deploy, and monitor machine learning models within a single unified environment. The Paris-founded company platform covers the full ML lifecycle from data preparation and feature engineering through model training, deployment, and governance, supporting both code-based and visual, low-code workflows to serve teams of varying technical sophistication.\n\nThe company raised over $1 billion in total funding including a $400 million Series E led by Tiger Global and ICONIQ Growth, reaching a valuation of $3.7 billion. Dataiku counts over 600 enterprise clients globally including Unilever, GE, Sanofi, and the US Army Corps of Engineers, and reports thousands of active practitioners using the platform daily. The company has offices in New York, London, Paris, Singapore, and Sydney, reflecting a global enterprise sales motion that has made it one of the largest pure-play ML platform vendors in the world.\n\nDataiku competes in the data science platform market against Databricks, SAS, KNIME, and H2O.ai. Its differentiation is the breadth of user personas it serves within a single platform, allowing collaboration between data scientists, ML engineers, and business domain experts without requiring separate tools. The company is considered one of Europe most successful enterprise AI software exports, with the majority of its revenue generated outside France and a valuation that places it among the top independent AI platform companies in the world.

Dataiku got there first, launching in 2013 — that's 6 years of extra runway. Secondmind didn't arrive until 2019. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Secondmind has about 1-50 employees; Dataiku has about 1000+. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Secondmind and Dataiku compete in ML Platform, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.