We are building the Conversational Revenue Orchestration layer for Enterprises.

It started with a product too complex to sell from a website.

Before Zigment, our founder Dikshant ran a consumer health business selling personalised supplements. Every customer had questions and every answer depended on their situation. No landing page could do that. A human expert on a call could, but putting an expert next to every interested customer does not scale, and the economics never worked.

The problem was not specific to supplements. Anyone selling something considered knows it. Insurance, healthcare, education, vehicles, homes. The moment a customer shows real interest is the moment most companies go silent, slow, or generic.

When large language models arrived, the shape of the answer became obvious. A knowledgeable, patient, always available expert for every customer, at scale. That was the founding idea, and we started building.

What we learned by going deep is that the agent is the easy part. The hard part is everything around it. The harness that keeps an agent accurate and on policy inside a regulated industry. The memory that carries context across weeks and channels so no customer ever repeats themselves. And the structure underneath, the Conversation Graph, that turns every conversation into something the business can learn from.

That infrastructure is what Zigment is today. The supplements were only the first product too important to be sold by a form.