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Founded Year



Incubator/Accelerator - IV | Alive

Total Raised




About Dataiku

Dataiku develops a centralized data platform. Its solutions include data preparation, visualization, machine learning, analytic applications, and more. The company serves the banking sector, pharmaceuticals, manufacturing telecommunication sector, and more. It was founded in 2013 and is based in New York, New York.

Headquarters Location

902 Broadway 8th Floor

New York, New York, 10010,

United States



Dataiku's Product Videos

ESPs containing Dataiku

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Enterprise Tech / BI & Operational Intelligence

The predictive analytics market is focused on providing businesses with the tools and technologies needed to enhance and automate decision-making processes. This includes standardized machine learning algorithms, comprehensive AI-based monitoring, and platforms that bring together all data and users. The market aims to help organizations scale and responsibly operationalize AI, while also addressi…

Dataiku named as Leader among 12 other companies, including SAS, DataRobot, and

Dataiku's Products & Differentiators


    Dataiku is the platform for Everyday AI. With the explosion of generative AI, everyone is using AI for everyday tasks. Companies want to channel that excitement to transform business outcomes. Dataiku’s single, coherent platform is the only product that welcomes users with a wide range of skills and expertise, covers the full lifecycle of an AI project, and provides value to individuals at every level. Dataiku accelerates AI projects from months to days with a rich visual interface, built-in solutions, and pre-built components that take full advantage of a wide variety of generative AI services and cloud platforms for maximum speed and scale. Dataiku also provides strong MLOps, responsible AI, and governance capabilities, allowing teams and executives to monitor and manage AI projects and build confidence in AI outcomes.


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Dataiku is included in 5 Expert Collections, including Unicorns- Billion Dollar Startups.


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Latest Dataiku News

Is it time to get rid of CIOs? The rise of AI prompts organizational and hierarchical questions

Nov 28, 2023

Bookmark icon Summary: The generative generation calls for a re-think of traditional tech power structures. But what do we replace them with? Comment bubble icon Here’s a question for you all - should a CIO now be called something else? And if the job title is to remain, where should it be in the pecking order of corporate politics? Still at the top as guardian of all things informational, or demoted to the head of paperclips and other mundanities? It may seem a trivial question but it is, in fact, of increasingly vital importance – both in business, operational fact and in the mists of smoke and mirrors that are the essence of brand image and customer perception. In other words, does CIO still hack it as a title worthy of the C-Suite? There’s another important question according to Conor Jenson, Chief Data Officer of Dataiku - are CIOs now up to doing the job at all? The issue here is that with the coming of AI, Machine Learning and the generative generation, being Chief Information Officer  may no longer adequately describe the complexity, importance, or perhaps relevance of the job. There have been attempts to change the job title in the past, the last one being a few years ago when Chief Digital Officer was touted as a more appropriate alternative. It certainly mapped onto the headline trend of business transformation and the fact that it all hung on the digitalization of as many business processes as possible. In the end, however, there seemed to be a realisation that `digitalizing’ everything was a job with a fairly limited lifecycle for, while there is still a good deal left to be digitalized, it is only a matter of time before even the stuffiest, most fuddy-duddy of businesses follow the transition trend, or finds itself demised. No, the CIO still reigned supreme as the job in charge of the crown jewels of every business, its information. Dataiku, which has facilities in most corners of the world including four each across Europe and North America, is targeting the application of generative AI to business applications, what it terms ‘everyday AI’. To help this along it offers both consultancy services and a wide range of pre-defined solutions for different business tasks and sectors, ready to be picked from an online catalog. These fall into two camps: those that can apply horizontally across any type of business, such as Process Mining, Demand Forecasting, and EU AI Act Readiness , through to tasks focused at specific business departments, such as customer segmentation for banking, optimizing omni-channel marketing, and pharmacovigilance. It has recently introduced a new Large Language Model (LLM) Mesh, an environment designed to help users build safe, secure, enterprise-ready gen AI applications. Should 'the CIO' be a team? It is hardly surprising that AI has caused the CIO issue to raise its head again, for AI is going to be at least as widespread, and as deeply penetrating into the heart of every business as digitalization. In practice, perhaps the real question should be whether there should be more positions included in the C-Suite, if full benefit is to be taken from the capabilities of new technologies – and the ways they can be exploited. In Jenson’s view, however, CIOs themselves are not seeing, let alone seizing, the opportunities tech developments such as AI create. The potential role for the CIO is growing, not least because such individuals are at the helm of a ship that is growing – what constitutes information is growing in size, richness and complexity. And that means not just technological growth, for information is now much more than just what is generated internally by a business. The CIO is the one in charge of the company's information generated from a multiplicity of sources in a multiplicity of ways, using a multiplicity of technologies and processes. Ideally the role should be advancing to be the broker, not just of the information itself, but of the sources and technologies by which it is derived. That role should then be supported by a team of specialists, each one the chief of their own domain – Chief Digitalization Officer, Chief Data Analytics Officer, Chief Technology Utilization Officer and the like (the latter being different to the CTO, who is concerned with the technologies a business uses in its own income-earning products/services. The CTUO is in charge of what tech gets bought to make the ‘machinery of information’’work as cost/effectively as possible). Jenson argues: It's a moving target. AI is a smaller subset of the broader data and analytics ecosystem. The interesting thing that I see in working with a lot of CIOs, though, is how they see their mandate and how they perceive the data and AI world in itself. They look at it primarily just from a capabilities perspective, without a lens on, ‘How are we applying it?’. Jenson’s own background is as a data scientist, so he has formed some hypotheses, though he acknowledges he is still unsure which side of the fence he will eventually find himself. One of the problems here is that the downside of such a structure as outlined above is the creation of what could become a political minefield. For example, would a Chief Data Officer or a Chief Digital Officer be at the top of the pecking order under the CIO? Does the CIO then have the right skills set? Jenson says: I'm not really sure, but that is what CIOs, in most of my experience, lack - being progressively part of the business in going forward and, for example, looking at what the business problems are that we're trying to solve. They aren’t bringing that sort of bridge between, ‘Hey, I'm looking over systems and data, but I'm not proactively looking at how those systems and data are helping us move the company forward’. It feels like, far too often, the CIO mandate is to keep the lights on, and to make sure that servers don't break, and they're not a progressive party that goes forward. He suggests this feeling can be even clearer when compared to the CTO of a business. While the CIO is ensuring that the business is ticking over and nothing important is breaking, the CTO is out there on the bleeding edge of what might be possible as new developments and directions for a business – and finding new ways of making those possible. Server uptimes and SLA performance levels are, of course, important, but worthy of a desk in the C-Suite? In Jenson’s view it is becoming a common question to ask. Are CIOs out of their depth now? The underlying point, therefore, is that the majority of CIOs show many signs of not being prepared to cope with the implementation and subsequent implications of working with AI. Jenson does not dispute that a large number of software companies are now taking the classic marketing step of proclaiming, ‘Yes, we do/have/work with AI’ when the chances are that the connection is at best tenuous. Indeed, his observations suggest that real AI – with its equal measures of very helpful and really quite scary capabilities - is heading at these companies with freight train momentum. The important question coming from Dataiku therefore is. are CIOs about to find themselves out-manoeuvred and out of their depth? Jenson postulates: I think the question that we're trying to ask really is, how important is it to a company that they're investing in AI and having that as part of their strategy as a company? I don't want to make the a priori assumption that every company should be driven by AI. I don't think that's necessarily the case. But if you think about the composition of any C-Suite, the titles that sit in there beyond the standard CEO, CFO, CIO - the de rigueur ones that every C-Suite has - who would you choose to put directly under a CEO, sitting as a proper part of the C-Suite, that indicates what's important to a company, to the market, to your employees, and to your board? To him and Dataiku the underlying questions that follow are very rarely the progressive ones: where should we be going? What should be the direction of the company? How should our technology be supporting that and, of course, the obvious one -why? Jenson concludes: The data space, the AI space is moving so fast it's hurtling at companies faster than your typical three to five year planning cycles and tech investments. It's changing too fast for how typical organizations work. If making AI the pillar of your company is part of your strategy, and you're putting up a true C-Suite, then somebody who reports directly to the CIO and CEO, and who is in charge of that initiative, that I think it's the signal to the market. My take They are brilliant at keeping the lights on and ensuring SLA requirements are met, but are CIOs, in the age of AI, able to impart confidence in customers, the wider marketplace, the employees and even their own Boards that they are on top of those technologies, their implications, and above all, their potential consequences? It is a serious question. It is being asked openly now. The answer is certainly not an automatic 'yes’! Image credit - Pixabay

Dataiku Frequently Asked Questions (FAQ)

  • When was Dataiku founded?

    Dataiku was founded in 2013.

  • Where is Dataiku's headquarters?

    Dataiku's headquarters is located at 902 Broadway, New York.

  • What is Dataiku's latest funding round?

    Dataiku's latest funding round is Incubator/Accelerator - IV.

  • How much did Dataiku raise?

    Dataiku raised a total of $846.6M.

  • Who are the investors of Dataiku?

    Investors of Dataiku include NVIDIA DGX-Ready Managed Services, FirstMark Capital, Battery Ventures, CapitalG, Dawn Capital and 17 more.

  • Who are Dataiku's competitors?

    Competitors of Dataiku include BigML, Databricks, Aindo, DataCanvas, MindsDB and 7 more.

  • What products does Dataiku offer?

    Dataiku's products include Dataiku.

  • Who are Dataiku's customers?

    Customers of Dataiku include Banker's Bank, Unilever, US Venture, Floa Bank and Thrive SPC.


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