Blog
February 19, 2026
Solid Launches to Fix the Biggest Problem Holding Enterprise AI
Yoni Leitersdorf
CEO & Co-Founder
Solid publicly launches to help enterprises make AI reliable at scale. Alongside a $20M funding round, Solid gives AI a trusted, continuously updated understanding of business data - enabling accurate answers, scalable workflows, and AI systems that can move from pilots into real production.
AI isn’t failing because it lacks intelligence - it’s failing because it doesn’t understand how businesses actually work. As companies race to embed AI into decision-making, workflows, and automation, they’re discovering a hard limit. No matter how powerful the models are, AI can’t deliver reliable results unless it understands the data it’s using — what the numbers mean, which rules apply, and which definitions the business actually trusts. That understanding is missing in most enterprises today, and it’s quietly becoming the biggest blocker to real AI impact.
Today, we’re launching Solid - and announcing a $20M funding round to help enterprises close the Data Understanding Gap that keeps AI stuck in pilots instead of production. Solid gives AI a trusted, continuously updated understanding of how a business’s data works, so companies can finally rely on AI to answer questions, power workflows, and take action safely at scale.
Problem: What’s Broken
Enterprise data is complex, fragmented, and constantly changing. Business logic lives across dashboards, SQL, documentation, and - most critically - in people’s heads. Definitions shift. Metrics evolve. Rules vary by context. And companies are relying on connecting their data to AI alone as a solution.
Humans can navigate this complexity with experience and judgment. AI cannot.
So when organizations try to apply AI to their own data:
- Answers conflict across tools
- Automation breaks when logic changes
- AI agents hesitate or fail to act
- Data teams become bottlenecks for every request
Most companies try to patch this by manually maintaining definitions across BI tools, models, and AI systems. But as AI usage grows, that approach collapses under its own weight. Data understanding becomes the slowest, most fragile layer in the stack.
Why We Built Solid
We saw this problem everywhere - not just in one company or one industry, but across every organization trying to turn AI ambition into reality. Teams had invested in modern data platforms and cutting-edge AI tools, yet still couldn’t get consistent answers or reliable automation.
The issue wasn’t effort or talent. It was that no system owned the business meaning of data in a way AI could actually use.
We built Solid to solve that problem directly - not by adding more dashboards or asking teams to document harder, but by giving AI a dependable understanding of how the business works in the real world.
As AI takes on more responsibility, companies need a clear owner for business meaning - someone accountable for defining, validating, and evolving how data is interpreted as the business changes. We believe this will emerge as a new role inside the enterprise: the Semantic Engineer. This role builds naturally on the work analysts already do today, but shifts the focus from producing reports to ensuring AI systems consistently understand and apply the right business logic over time.
Since launching privately, we’ve been partnering with forward-thinking enterprises like SurveyMonkey to put this foundation into practice - helping teams move AI from experimentation to production with a shared, trusted understanding of their data.
What Solid Does
Solid bridges the gap between enterprise data and AI.
It automatically generates, tests, and maintains the semantic models AI needs to safely understand and use enterprise data - working with the platforms companies already rely on, not replacing them.
“As we expand AI across SurveyMonkey, trust in our data is non-negotiable,” said Meenal Iyer, VP of Data at SurveyMonkey. “AI moves fast, but without a shared and reliable understanding of business logic, it breaks just as quickly. Solid has given us a strong framework where definitions stay aligned as our data and business evolve, so AI can deliver answers and power workflows we can actually trust.”
At its core, Solid:
- Learns the structure and meaning of enterprise data, including real-world nuance and edge cases
- Integrates with existing data platforms, BI tools, and AI systems
- Keeps business logic continuously up to date as data and definitions change
- Combines software with hands-on expertise to handle exceptions, capture nuance, and improve accuracy over time
We’re not a BI tool.
We’re not a semantic layer.
Solid is the layer - plus human expertise - that translates how your business works into something AI can reliably understand and act on.
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Why We’re Built for This
Solid is built by people who have spent their careers inside enterprise data, analytics, and AI systems - watching firsthand how fragile data understanding becomes at scale. We’ve lived the pain of inconsistent definitions, broken workflows, and AI initiatives that stall not because of technology limits, but because business meaning couldn’t keep up.
That experience shaped every design choice behind Solid: automation where it scales, human expertise where nuance matters, and a relentless focus on making AI reliable in real-world conditions.
In practice, Solid delivers measurable results:
- Accuracy: Without Solid, AI + data accuracy typically ranges from 20–30%. With Solid, accuracy improves to 85%+.
- Effort: Solid reduces the manual work required to maintain and test semantic models by 50–70%, freeing data teams to focus on higher-value work.
- Time to Value: Solid shortens AI + data initiatives by a factor of 4, reducing deployment timelines from 1–2 years to just 3–6 months.
Launch Details
With today’s launch, Solid continues to work with enterprises to:
- Enable trustworthy chat-with-your-data experiences
- Power AI-driven workflows that don’t break when logic changes
- Support AI agents that can reason, decide, and take action safely
The $20M funding will accelerate product development, expand customer partnerships, and help more organizations move AI from experimentation into day-to-day operations.
If your company is investing in AI - and struggling to trust the results - we’d love to talk.
AI models will keep getting better. Tools will keep multiplying. But without a trusted understanding of enterprise data, AI will continue to create friction instead of leverage.
Solid removes that blocker.
We believe the next era of enterprise AI won’t be defined by smarter models alone - but by systems that understand the business well enough to act on its behalf. We’re excited to help build that future.
To learn more about Solid and our partnership with SurveyMonkey, download the case study here.
*Photograph of Solid Founders Yoni Leitersdorf and Tal Segalov taken by Omer Hacohen.
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