There is a fast-growing category of enterprise AI vendor that most business leaders have not heard of yet — companies that skip the endless pilot phase and actually ship production AI in a matter of days. Unframe is one of them, and its latest funding round suggests the market is very ready for that approach.

The Israeli AI startup announced a $50 million Series B on May 19, 2026, led by Highland Europe, with participation from Bessemer Venture Partners, Craft Ventures, TLV Partners, Third Point Ventures, Cerca Partners, and Vintage Investment Partners. Total capital raised since the company’s 2024 founding now sits at $100 million.

The more striking number is not the raise itself. It is what happened in the 12 months before it.

From Zero to $100M in Contracts in One Year

Unframe crossed $100 million in total contract value within its first year of operation. Average contract terms run three to five years, which means customers are not experimenting. They are buying production infrastructure they plan to rely on.

Net revenue retention sits at 400%. In plain terms, that means customers who started with one AI use case expanded into four times as much spending within the same year. That pattern repeats enough to be a business model, not an outlier.

COO and co-founder Larissa Schneider described the signal clearly: “Surpassing the $100 million TCV mark within a year shows that enterprises are ready to invest in AI at scale when the solution actually fits their operational reality.”

That last phrase carries weight. A solution that fits operational reality is not a proof of concept. It is not an AI model plugged into a spreadsheet. It is a production-grade system that runs on the company’s own data, integrates with existing workflows, and generates measurable output within days of signing.

The One-Week Model

Unframe’s differentiation is speed and accountability. Their platform, called Framery, is built specifically to bring AI use cases into production in roughly one week. CEO Shay Levi has spoken plainly about why the speed matters to the business model itself: if deployment took four weeks instead of one, the guaranteed-outcome model would not work.

That is a meaningful constraint. Most enterprise AI deployments drag on for months because the vendor is figuring things out in parallel with the customer. Unframe’s architecture uses modular building blocks that can be assembled and connected to customer data quickly, with enterprise-grade security and integration baked in from the start.

The Framery platform brings together enterprise data, operational context, and agentic intelligence in one managed layer, running alongside whatever AI programs the business already has in place.

What This Means for Business Leaders

The Unframe story is a data point in a broader trend. Enterprises are not moving away from AI. They are moving away from AI that does not ship.

The dominant complaint among business leaders in 2025 and early 2026 was not skepticism about AI. It was frustration with deployment reality. Pilots completed. Demos passed. Production never arrived. The gap between what AI promised and what it delivered was mostly a delivery problem, not a technology problem.

What Unframe’s numbers confirm is that companies will pay — and pay well, on multi-year contracts — when that gap closes. The 400% NRR figure suggests customers do not just stick around. They expand aggressively once the first use case works.

This creates a shift in how business owners should evaluate AI vendors. The question is no longer “can this technology do what I need?” The technology has largely cleared that bar. The question is “how long until it is actually running in my business, and who is accountable if it is not?”

Unframe built its entire positioning around answering that question with a specific number: one week.

The Broader Market Signal

Unframe is not alone in this positioning. The enterprise AI market in 2026 is bifurcating. On one side, the big platform vendors — Microsoft, SAP, Salesforce, ServiceNow — are building AI into existing suites. On the other side, a new class of delivery-focused AI companies is emerging that prioritizes speed-to-value over breadth of capability.

That second category is where the venture money is now pointing. It is also where the customer contracts are materializing fastest. When 12-month-old companies are signing $100 million in TCV on multi-year terms, it confirms that the enterprise AI market has moved past its experimentation phase.

The businesses that will benefit most are the ones who stop waiting for the “right moment” to deploy and find partners who remove the deployment risk entirely.

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Enterprise DNA helps business leaders navigate the AI shift across data, operations, and customer experience. If you are evaluating AI deployment options for your team, our advisory service can help you cut through the noise and identify what will actually work for your business.