Stitch Insights
Dmitri Pavlov realized that Fortune 100 consumer brands were operating blind when it came to understanding what their customers actually cared about. "They're running surveys on all of their customers. But what they're not doing is they're not surveying all of their competitors' customers at that same scale," he explains. The insight came from working with luxury groups, fashion retailers, and consumer electronics companies on sustainability initiatives—companies investing in multi-billion dollar strategies around animal welfare and carbon emissions, but with no actual data on which specific attributes mattered to customers.
After launching in 2018, Pavlov brought on co-founders Dr. Hannes Heikstad (now at Stanford's Human Artificial Intelligence Lab) and Dr. Angel Schwartz. The founding team invested about a quarter million dollars of their own money and secured a 3.5 million dollar non-dilutive government grant to develop the underlying technology. Neither co-founder took salaries for the first year and a half. They built a deep learning platform that could analyze customer feedback at a granular, attribute-level dimension—not just sentiment or overall brand performance, but specific product dimensions that drive loyalty and adoption.
In 2020, Pavlov was running POCs with major brands like Sephora, exploring what the product could solve. The breakthrough came from direct engagement with C-level executives. Over the past year, he personally spoke with 30-40 Fortune 100 C-suite executives (CDOs, CTOs, CSOs, CMOs, CEOs). These conversations revealed the true pain point and unlocked the go-to-market strategy: offer a $10,000 snapshot analysis of one product against a competitive category set, which then converts into a $10,000 monthly subscription. By the time of this interview, the company had moved from nine pilot customers in 2020 to a handful of true annual recurring revenue contracts.
The shift from month-to-month POC revenue to annual contracts transformed the business. Early on, Pavlov offered multiple channels (Amazon, Twitter, support request channels) at $10,000 per month each, and expansion revenue came from extending into additional channels. The company discovered that once they had built data pipelines for each channel, they could deploy the platform with minimal engineering effort—zero development happening by the time of this interview. This allowed the team to shrink from six full-time employees down to three, focusing 100% on sales rather than product development. Pavlov noted that "the pilots and the subscriptions that we're launching are through channels that we're already already a full analysis of. So we're just deploying our platform right now."
Stitch Insights sits at under $700k ARR with a pipeline of large contracts coming in. Pavlov is targeting $1.3 million ARR by Q1 next year (requiring roughly $110k per month in revenue), which would put him in position to raise Series A. He's in the middle of closing a $3 million seed-plus round—having raised about $110k in an earlier seed at a $4 million valuation—and is hiring aggressively, planning to grow from three full-time employees to six or seven by the end of November. The company operates with the same core technical founding team but is now adding dedicated sales and support staff. Investors have been reaching out proactively; Pavlov wasn't initially seeking capital but was convinced that additional resources would help him capture a pipeline that's grown too large for the current team to handle.
- •The founding team identified a specific, quantifiable gap in how Fortune 100 brands make billion-dollar strategic decisions—they benchmark themselves but never systematically benchmark against competitors' customers—which created an urgent, high-stakes problem only this solution could solve.
- •Direct outreach to C-level executives revealed that the true willingness-to-pay came from offering a low-risk $10k snapshot analysis first, which then converted into recurring $10k monthly subscriptions, proving that go-to-market strategy matters more than product pivots.
- •By building reusable data pipelines for each enterprise customer channel, the company achieved a capital-efficient model where new customer deployments required zero additional engineering, allowing the team to shift entirely to high-touch sales without scaling headcount.
- •The founders' willingness to self-fund with personal capital and secure non-dilutive government grants, combined with taking no salary for 18 months, enabled them to stay independent long enough to prove the enterprise sales model without dilution pressure.
- 1.Identify a specific operational blindspot in Fortune 100 decision-making by interviewing practitioners in a narrow vertical (e.g., luxury, fashion, or electronics), then validate that this gap directly blocks multi-billion dollar strategic decisions.
- 2.Build a minimum viable analysis product that solves one narrow use case exceptionally well, then offer it as a fixed-price snapshot engagement ($10k) to C-level buyers, which serves as a conversion funnel into recurring subscriptions rather than competing on price upfront.
- 3.Create reusable, componentized backend infrastructure (data pipelines, analysis modules) that can be deployed to new customer channels with minimal engineering work, freeing your founding team to focus 100% on direct enterprise sales instead of continuous product development.
- 4.Systematically conduct 30-40 direct conversations with relevant C-level titles (CDOs, CMOs, CSOs, CTOs) at your target company list to identify the actual buying trigger and decision-maker, rather than relying on inbound channels or assumptions about buyer personas.
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