Cotera

Ibby Syed had built what looked like a successful AI SaaS—he'd hit $150K ARR and had customers paying. But something felt deeply wrong. Customers would call with questions, get an answer, and disappear. They never logged into the product. What Ibby had accidentally built wasn't a SaaS; it was a consulting business wearing a SaaS mask. The wake-up call came when his co-founder solved a customer problem with just 100 lines of OpenAI code—code that outperformed the entire complex data science solution Ibby had spent months building. That moment made the opportunity crystal clear: the real product wasn't custom AI implementations; it was teaching customers to build their own AI agents.

Cotera pivoted from a services-based model to a platform. Instead of building custom AI solutions for each customer, the team built a system that let enterprise customers create prompt-based AI agents on top of their existing data warehouses—Snowflake, BigQuery, and other infrastructure they already owned. The insight was powerful: Series B+ companies didn't want AI in a third-party cloud. They wanted AI capabilities native to their own data infrastructure. This positioned Cotera not as a data science vendor, but as a platform tool—something that enterprises could own and control.

Ibby's outbound strategy was unconventional and remarkably effective. Rather than cold pitching, he built a Reddit monitoring AI agent that identified qualified leads from relevant discussions. He would then send those actual, contextual leads to prospects before the first call—leading with value instead of a pitch. First customers came through LinkedIn outbound, but the Reddit-based lead generation strategy became his most effective channel, converting better than traditional cold prospecting because it demonstrated immediate, concrete value.

The critical pivot was moving from "build for customers" to "teach customers to build." Offering custom implementation services felt scalable at first but created a ceiling on growth and unit economics. The platform model—where customers learned to build their own AI agents—was what actually unlocked scalability. Delivery was shifted from the Cotera team to the customer's own internal capabilities. Enterprise adoption accelerated when the company stopped positioning itself as a services vendor and started positioning itself as a platform for AI agent development on existing data infrastructure.

Cotera now has 15 enterprise customers generating over $1M ARR with a team of 10. The company serves customers who want to build AI capabilities on Snowflake, BigQuery, and similar platforms—exactly the infrastructure-native approach that resonated with large organizations. The lesson embedded in Cotera's journey is that recognizing when your product has become consulting, and then pivoting to empower customers to solve problems themselves, can be the difference between a lifestyle business and scalable SaaS growth.