Deci AI vs Dataiku

Dataiku has a disclosed valuation of $3.7B, while Deci AI'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 Deci AI's $80M — a gap of $920M. Combined, the two companies have completed 8 known funding rounds.

Dataiku leads with an Awaira Score of 90/100, while Deci AI sits at 48/100. That 42-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Deci AI was founded by Yonatan Geifman in 2019. Dataiku was founded by Florian Douetteau in 2013. Visit each company's profile on Awaira for a full founder biography.

Deci AI: Deci AI developed neural architecture search and model optimisation technology that automated the process of compressing and restructuring deep learning models for faster inference on target hardware, enabling AI teams to deploy models on edge devices, GPUs, and CPUs with significantly lower latency and compute cost than the original training architecture. The Tel Aviv company built AutoNAC, an automated neural architecture construction tool that generates hardware-aware model architectures optimised for specific deployment targets.\n\nThe company raised approximately $80 million in venture funding including a $55 million Series B from investors including Square Peg, Insight Partners, and Jibe Ventures before being acquired by NVIDIA in April 2024. The acquisition gave NVIDIA a model optimisation software layer to complement its GPU hardware, enabling NVIDIA to offer end-to-end AI deployment tools that span hardware, software runtime, and model architecture optimisation. Deci team integrated into NVIDIA developer tools organisation.\n\nDeci competed in the AI model optimisation and neural architecture search market alongside Neural Magic, Hailo, and model compression tools from major framework providers including TensorFlow Model Optimization Toolkit and PyTorch. The acquisition by NVIDIA is consistent with the chip company strategy of acquiring software and tooling companies that deepen customer dependency on the NVIDIA ecosystem. Deci inference acceleration technology provides NVIDIA customers measurable throughput and cost improvements on existing hardware, making it a natural product addition to the CUDA and TensorRT software stack. 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. Deci AI didn't arrive until 2019. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Deci AI 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 Deci AI and Dataiku compete in ML Platform, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.