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Bringing Enterprise AI Into Focus

Scaling AI Lynn Heidmann

It’s been nearly six months since our last update on what’s been going here at Dataiku (time flies!). Since our Series B announcement, we’ve been busy not only serving the larger data community as promised (including connecting CDOs in their still new and ever-evolving role), but also doubling our staff and bringing some exciting, innovative new customers on board that are positioned to fundamentally change their businesses (and their industries) with data science.

abstract network of dots connected by lines

We’re proud to be one of the fastest-growing data science software companies and have worked hard to triple our revenue in 2017. But more importantly, we’re incredibly excited about what the future holds in the space of model deployment, deep learning, and artificial intelligence (AI) at Dataiku, with our customers, and out in the world.

Same Dataiku, but Bigger & More to Come!

AI floods the news daily, and it’s painted as the magic solution for everything from data breaches to climate change. But the reality for today’s enterprise is that AI isn’t magical, and in fact takes quite a bit of work and change - organizational as well as technological - to get right.

Throughout 2018, we’ll have our sights set on helping businesses remove the roadblocks standing in the way of operationalized data projects while also providing the structure and stability necessary for long-term success.

bikers biking in a line on a country roadDataiku removes roadblocks and provides structure along the analytics journey for both teams and individuals to thrive.

This means an accelerated focus on deep learning, AI, and deployment to production in our product development roadmap. But what does it mean at a practical, day-to-day level? Here at Dataiku, we have lots of new features in store, but they’ll all forward our mission of being a:

  • Centralized, controlled environment so that the way people work with data stays consistent and secure (regardless of changes in underlying systems, staff, etc.).
  • Repository of best practices, maximizing reusability and leaving more time for more important data matters.
  • Shortcut to model deployment and management so that models are centrally managed and updated from one location, integrating with an API without having to modify or inject anything into existing applications.
  • Unified visual abstraction for analytics to level the playing field and open the doors to becoming truly data-driven.
  • A common ground for experts and explorers, because everyone within the enterprise should be involved in and empowered by data science, machine learning, and AI.
  • Catalyst for the data-powered company, because moving faster means more opportunity for business-impacting models.

Haven’t tried Dataiku yet? Now’s as good a time as any to dive in. 

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