The missing layer in Enterprise AI: Why we invested in Solid

Enterprise AI has a context problem.

Enterprises today are racing to deploy AI agents, but the vast majority are seeing these projects stall. The biggest hurdle is not model quality, GPU supply, or talent. It’s context.

AI systems today do not understand enterprise data the way humans do. They do not have a strong grasp of the business, leading to delayed projects that never seem to reach production. And even when AI models are actually given access to internal data, they struggle to know which dataset to pull from, which metrics are canonical, or how definitions might vary across different teams.

When models do not understand your data, they often spit out AI slop, eroding trust and leading to poor outcomes. Solid is solving this exact problem.

The missing layer between raw data and AI agents

Solid transforms complex enterprise data into a unified semantic model that AI systems can pull from. Rather than wiring LLMs directly to raw data for every project, Solid builds a singular context engine that defines metrics, relationships, and business logic across all AI initiatives. With Solid, enterprises can now pull in context from their data warehouses, CRM systems, communication channels, and other systems of record to develop grounded agents with a deep understanding of their business.

The result is dramatic: customers are seeing material improvements in accuracy while bringing development timeframes from years down to just weeks. Initiatives that may have never seen the light of day are now making it to real production, all based on the singular, trusted context from Solid. Customers who may have started focusing only on text-to-insight are now broadening their scope of what is possible with the shared context built on Solid.

Battle-tested builders with customer empathy

Building the semantic backbone of enterprise AI requires founders who have experienced firsthand how fragile data systems become at scale. CEO Yoni Leitersdorf and CTO Tal Segalov have partnered to bring us closer to this vision. Both are repeat founders in data infrastructure and cybersecurity, with decades of experience building mission-critical systems at Fortune 500 scale. 

Together, they have a deep understanding of the problems enterprises face today and a sense of optimism for the agentic future they are building towards. With the AI world moving at breakneck speed, enterprises are not seeking yet another software solution. Instead, they’re looking for trusted partners with a deep sense of where the world is moving.

We are also excited to be partnering again with our friends at Team8, who have been excellent partners through their venture creation platform in helping Solid reach product-market fit quickly.

Trust as the new competitive advantage

Solid represents a broader pattern we are seeing across enterprise AI. The winners in the agent era will build the infrastructure that makes AI trustworthy inside large organizations. Customers are tired of off-the-shelf evals that look great for demos, and are instead looking for purpose-built systems proven to work for their use cases.

Trust is now the gating factor for AI adoption, and founders building enterprise AI need to think beyond model performance and toward real-world results.

With $20 million in funding from Signalfire, Team8, and leading angels, Solid is quickly growing its AI engineering team and expanding its enterprise customer base. This is the beginning of a new category: context engineering for AI. The agent era will reward companies that solve trust at the foundation, and we are proud to be working with Solid on this journey.

(Photo credit: Omer Hacohen)