Case Study: Aible
6 Patents.
Gartner Cool Vendor.
GA in 90 Days.
Enterprise AI | AutoML | No-Code Platform | Business Intelligence
What happens when a 6-person startup takes on IBM Watson, SAP, Microsoft, and DataRobot?
6 patents.
Gartner Cool Vendor.
First product ever sold from the Gartner booth.
$100M+ valuation in 90 days.
How?
Finds what customers will pay for.
Builds it in code in weeks.
Powered 34 AI products.
Generated 24 patents.
Delivered $500M+ in customer ROI.
Snowball Sprint — AI-First Product Development Framework
The Challenge
The enterprise AI market belongs to giants. IBM has Watson. Microsoft has Azure ML. SAP and DataRobot are spending hundreds of millions on R&D.
A startup called Aible has 6 employees, no brand recognition, and 90 days to launch at the Gartner Data & Analytics Summit.
Employee #6.
Head of AI Experience Strategy.
90 days to beat IBM at Gartner.
The only way to do that wasn't to outbuild them.
It was to outvalidate them.
The Pivot
What the Market Was Building
Every enterprise AI platform in 2018 — IBM Watson, SAP, Microsoft, DataRobot — optimized for the same thing: Accuracy. Precision. Recall.
Metrics that data scientists loved and business users couldn't interpret. They were all fighting for the same technical buyers with the same technical language. And 85% of their AI projects were failing to deliver ROI.
What Business Customers Actually Needed
Business users didn't want accurate models — they wanted profitable decisions. We stopped building for data scientists and started building for the people who actually needed answers.
We reframed the entire product around one question: What's the dollar impact of getting this prediction right versus wrong?
This insight drove everything — the conversation flow, the interface, the metrics we surfaced. We stopped showing accuracy percentages and started showing dollar signs.
The Snowball Sprint
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The core hypothesis from our Founder & CEO, Arijit Sengupta: we could win against IBM and Microsoft not by being more technically sophisticated, but by being radically simpler and ruthlessly focused on business impact.
I facilitated intensive workshops with the executive leadership to brainstorm and create a novel AI experience.
The breakthrough: A "choose your adventure" conversation flow that would handle 32 complex AI scenarios while feeling like a simple business discussion.
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Rapid customer validation challenged our assumptions.
I interviewed potential customers — business analysts, operations managers, marketing directors. None of them wanted to learn data science. All of them wanted to know: "Will this make us money?"
Key insight: The (patented) scatterplot I designed made it viscerally clear that high-accuracy AI models often underperform the current state when business constraints are factored in. This became our core differentiator.
Traditional AI tools are optimized for accuracy. We ruthlessly simplified the flow and optimized for AI impact.
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37 rapid prototyping iterations. 12-16 hour days. People dropping like flies.
I drove 37 prototype iterations, testing and pivoting in cycles measured in hours, not weeks. Complete audit of all 32 workflow variations to ensure every path delivered business clarity.
What I built:
Conversation-based AI creation flow using business language, not data science terms
"We Have A Winner" results card showing ROI impact vs. next best AI vs. current state
Cost-benefit matrix translating True Positives/False Negatives into dollars
Animated AI "contest" visualization making model selection intuitive
Initial 3 patents filed in the first 3 weeks — innovations in how AI communicates value to business users.
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From prototype to GA at Gartner Summit.
I built the entire marketing website in 3 weeks and recruited the Head of Visual Design, Patent Attorney (specializing in AI interface patents), and Marketing Consultant who created the "AI is a Waste of Money" campaign positioning.
With validated product-market fit, we sprinted to production:
Final visual design and branding polish
Marketing collateral and booth strategy
Analyst briefings and demo preparation
Launch: Gartner Data & Analytics Summit
At the Gartner Summit booth, something unprecedented happened.
Prospects didn't just take brochures. They didn't just schedule follow-up calls. They bought. On the spot. From the booth.
"This was one of the most successful product launches in Gartner Summit history."
In the entire history of Gartner Summits, no product had ever sold directly from the exhibition floor. We were the first. That's what happens when you build AI that speaks the customer's language.
The "When Can I Have It?" Moment
Validated Impact
90 Days
Idea → GA Launch
$100M+
Company valuation increase
3
Patents filed in the first
3 weeks
1st Ever
Product to sell from Gartner booth
6 Patented Insights
Customer research found the problem. Technical innovation solved it. Neither alone would have worked.
The interface innovations I created — translating statistical outcomes into business language, visualizing model performance against business constraints — resulted in the first 3 patents filed in just 3 weeks (3 more patents quickly followed for a total of 6).
This is what the 15% do differently. Validate first. Then build IP worth defending.
Across 34 AI products, I've generated 24 patents for my customers. When you find the right problem, innovation follows.
Tech + Customer Insight = Better AI.
What Leaders Say
"Greg can transform a simple idea into a state-of-the-art experience. Greg's laser focus on users and letting them decide good from bad differentiates him... His in-depth understanding of technology stacks positions him into the most needed leadership space between designers and developers."
— Tejaswi Redkar
CEO & Founder (former Cisco, AppDynamics, Sumo)
"With just a few clicks, I found three million dollars in additional sales leads in two hours. This is not yet another AI toy. This is a real way to deliver impact."
— Charlie Merrow, CEO, Merrow Manufacturing
"Unique among AutoML vendors, Aible gets that a model that maximizes accuracy almost never maximizes business impact."
— Kjell Carlsson, Ph.D. and Mike Gualtieri, Forrester
"Aible's unique value proposition is AutoML focused on business impact, rather than on 'neutral' data science indicators like accuracy and recall."
— Gartner Magic Quadrant for Cloud AI Developer Services
"Greg consistently pushes boundaries—not just in design, but in validating AI product-market fit directly with customers to ensure every feature solved a real-world problem. I'd work with him again in a heartbeat."
— Catherine Davis
VP Product Management, Addigy (former Sumo)
The Bottom Line
Traditional Product Development
(What I fixed)
Time to validate: Post-Launch
Pivot Cost: $1M+ and 6 months
IP generation: Incidental
Market entry: 12-18 months
Customer proof: Internal reviews + Hope & prayer
Analyst reception: Competitive positioning
Snowball Sprint
(What I did)
Time to validate: Week 1
Pivot Cost: 3-4 Hours
IP generation: Systematic (6 patents in 90 days)
Market entry: 90 days (Concept → GA)
Customer proof: Sold from Gartner booth
Analyst reception: "Unique among vendors"
Let’s Talk
You have 90 days. Or 6 months. Or a year.
You have competitors with more resources, more engineers, more brand recognition.
You have one shot to get it right.
The question isn't whether you can build a flashy POC. The question is whether customers will buy it.
Snowball Sprint answers that question before you spend the budget finding out the hard way.
In 30 minutes, we’ll talk through your AI challenges and see whether Snowball Sprint is the right fit.
No pitch — just an honest conversation.