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Chronicles

The story behind the story

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Data analytics startup Sisu emerges from stealth with $52.5M Series B led by NEA, with a16z and Green Bay participating, bringing its total raised to $66.7M

Jillian D'Onfro / Forbes :

Forbes Jillian D'Onfro

Context & Ripple Effects

Sisu's stealth exit lands in a funding wave for business analytics: Sisense had just raised an $80M Series E for cross-source data visualization, and ActionIQ took a Sequoia-led $13M Series A in 2017, so investors were already paying for tools that sit on top of enterprise data.

The cap table is the forward-looking part: Green Bay, a participant in this $52.5M round led by NEA with a16z, went on to lead Sisu's $62M Series C two years later — the same investors doubling down as the category shifted from dashboards to ML-driven analysis.

First-order effects

  • Sisu exits stealth with $66.7M total raised, giving it capital to hire and take its automated-analysis product to market against established BI vendors.
  • NEA, a16z, and Green Bay all take early positions in the decision-intelligence category, with NEA leading its second major analytics bet in the coverage window.

Second-order effects

  • Sisense — which went on to raise $100M at a valuation over $1B with 2,000 customers including Tinder, Philips, and Nasdaq — now faces a funded rival selling machine-generated answers rather than manual dashboards.
  • ActionIQ and similar analytics startups must differentiate against a competitor whose pitch is that ML, not analysts, finds the signal in enterprise data.

Third-order effects

  • If the pattern holds, enterprise analytics splits into dashboard vendors defending visualization workflows and ML-native entrants selling automated conclusions, forcing incumbents to bolt on machine learning to keep up.
  • Repeated mega-rounds in analytics (Sisense's $100M, Sisu's $66.7M) point to venture capital consolidating the category around a few well-funded platforms before the market sorts winners.

The trend: Venture capital is rotating business-analytics funding from manual dashboard tools toward ML-driven 'decision intelligence' platforms, with the same investors re-upping as the category matures.

Discussion

  • @itunpredictable Justin Gage on x
    I really want a tool like this, but I still don't understand how they overcome the biggest issue here, which is factors *not recorded* impacting KPIs (e.g. we changed the length of our free trial offer) https://twitter.com/...
  • @komichiewa Michie Cao on x
    After a year+ of building, it's liftoff for @sisudata! 🚀 I'm proud of what we've been able to accomplish together so far as a small, but incredibly hard-working & passionate team. Really excited for what's still to come https://www.forbes.com/...
  • @sachinrekhi Sachin Rekhi on x
    Would have loved to have a tool like this when I was leading the LinkedIn Sales Navigator business. Huge opportunity. https://www.forbes.com/...
  • @davidnotdave @davidnotdave on x
    I got to spend some time with @pbailis and believe @sisudata is a company to watch. They're being thoughtful and focused in solving a meaningful and complicated problem: helping organizations learn quickly. https://www.forbes.com/...
  • @bryce Bryce Roberts on x
    $70M pre-launch 😳 https://twitter.com/...