Shay Levi is the Co-Founder and CEO of Unframe, an organization redefining enterprise AI with scalable, safe options. Beforehand, he co-founded Noname Safety and led the corporate to its $500M acquisition by Akamai in simply 4 years. A confirmed innovator in cybersecurity and expertise, he focuses on constructing transformative options.

Unframe is an all-in-one enterprise AI platform headquartered in Cupertino, California, that permits companies to deliver any distinctive AI use case to life in hours, reasonably than months. By its Blueprint Method, Unframe collaborates with massive enterprises globally to implement options throughout observability, knowledge abstraction, clever brokers, and modernization. Unframe makes use of outcome-based pricing, permitting prospects to expertise and evolve any answer they need, risk-free. Unframe is LLM agnostic and does not require fine-tuning or coaching – foundationally altering what is feasible for giant enterprises looking for scalable, turnkey AI options.

On April third, 2025, Unframe Emerged from Stealth with $50M to Remodel Enterprise AI Deployment.

Following the profitable exit of Noname Safety to Akamai, what motivated you to launch Unframe, and what hole did you determine within the enterprise AI area that made it the fitting time and alternative?

I really left Noname earlier than the acquisition discussions began. What I noticed was an enormous wave coming, CIOs had been beneath stress to undertake AI quick, however the tooling accessible to them simply wasn’t enterprise-ready. They had been both piecing collectively level options with no governance, or ready on inside groups to construct from scratch. Neither path scaled, and each launched danger.

That was the sign. I spotted enterprises didn’t simply want entry to AI – they wanted a platform that gave them management, pace, and suppleness on the similar time. That’s what led to Unframe.

Noname Safety was a pioneer in API cybersecurity. How has your expertise constructing a security-focused firm formed the method you’re taking with Unframe?

Safety is in our DNA. At Noname, we discovered that innovation with out governance shortly results in danger. That lesson carries over on to AI. From day one at Unframe, we’ve baked in the fitting guardrails – safe knowledge dealing with, mannequin transparency, role-based entry – so enterprises can innovate with out introducing new vulnerabilities.

We’re additionally very conscious of how issues break at scale. So whereas Unframe empowers groups to maneuver quick, we’ve designed the platform with enterprise complexity in thoughts – whether or not it’s managing knowledge flows, implementing compliance, or integrating with legacy methods.

Have been there any widespread ache factors throughout enterprises within the API safety area that helped inform your imaginative and prescient for AI adoption?

Positively. At Noname, we noticed how difficult it was for enterprises to achieve visibility and management throughout their environments. Shadow APIs, inconsistent tooling, and siloed groups created actual operational danger – and it slowed every little thing down.

With AI, we’re seeing the identical sample repeat. Each staff desires to maneuver shortly, however with out the fitting construction, you get fragmentation, duplication, and blind spots. That have formed our pondering with Unframe. We wished to provide enterprises a solution to undertake AI in a method that’s unified, safe, and truly works throughout groups and methods – not simply in remoted pockets.

Unframe is gaining traction with main enterprises and achieved ARR within the thousands and thousands inside a 12 months – how did you obtain this degree of adoption so shortly?

We didn’t take the normal route of sluggish experimentation or restricted pilots. From day one, we had been out out there, partnering with international enterprises on high-impact, real-world tasks. These weren’t remoted use instances – they had been strategic initiatives tied to core components of the enterprise. That’s what earned us belief and helped Unframe turn out to be a strategic accomplice throughout a number of domains, not only a vendor. Once you ship actual outcomes quick, adoption follows.

You’ve spoken about decreasing AI deployment from months to hours. Are you able to stroll us via how Unframe makes this doable?

We’ve constructed lots of of deep technical constructing blocks into the Unframe platform. When a brand new answer is deployed, it’s not ranging from zero – it’s tailor-made via a blueprint that maps these elements to the person’s particular wants. That’s how we cut back deployment from months to hours.

Inform us extra in regards to the Blueprint Method – what makes it distinctive, and why is it so highly effective for enterprise AI use instances?

The Blueprint Method is how we ship tailor-made AI options at scale – with out ranging from scratch. Every blueprint maps the logic, elements, workflows, and guardrails for a particular use case, configuring our platform’s library of technical constructing blocks. It’s how we mix pace and precision at scale.

Unframe positions itself as LLM-agnostic and doesn’t require mannequin fine-tuning. Why was it vital so that you can keep away from the necessity for coaching customized fashions?

As a result of most enterprises don’t want customized fashions – they want customized outcomes. The second you begin fine-tuning, you’re locking your self into a particular vendor, rising prices, and creating upkeep overhead that the majority organizations aren’t set as much as deal with.

We designed Unframe to work with current trendy fashions in a method that also delivers tailor-made, high-quality outcomes – with out the complexity. By staying LLM-agnostic, we give enterprises flexibility, quicker time to worth, and the flexibility to evolve because the mannequin panorama adjustments. The purpose isn’t to coach fashions – it’s to unravel issues. And you are able to do that extremely effectively with out touching fine-tuning.

What function does pure language interplay play in Unframe’s platform – and the way far can it go in changing conventional software program UIs?

Pure language is a robust entry level – it makes AI immediately accessible to enterprise customers, with out coaching or technical ramp-up. That’s particularly vital if you’re working with international firms and distributed workforces throughout totally different international locations, roles, and languages. A chat-style interface helps degree the enjoying discipline.

However each Unframe use case is totally different, and the interface must match the duty. Typically meaning a pure language chat. Different occasions, it’s a dynamic desk, an interactive dashboard, or a content material era interface – no matter most closely fits the workflow and the result we’re fixing for.

We don’t see pure language as a alternative for conventional UIs, however as a layer that removes friction the place it issues. The purpose is to make software program really feel intuitive, versatile, and tailor-made – not simply to the person, however to the issue they’re making an attempt to unravel.

What classes from scaling Noname Safety to a $1B+ valuation and $450M acquisition are you making use of at Unframe?

Concentrate on fixing actual, pressing issues – and do it with enterprise-grade execution from day one. At Noname, we discovered that scale comes from belief, and belief comes from delivering quick with out chopping corners. At Unframe, we’re making use of that very same mindset: transfer shortly, construct securely, and keep relentlessly customer-focused.

As a repeat founder, what’s your method to constructing management groups and firm tradition in hyper-growth environments?

In hyper-growth, you don’t have the luxurious of figuring issues out slowly – so that you want individuals round you who should not solely nice at what they do, however who thrive in ambiguity and transfer with urgency. For me, constructing a management staff begins with belief, readability, and shared values. Everybody must be aligned on the place we’re going, and equally dedicated to proudly owning their a part of the journey.

Tradition is identical. It’s not ping-pong tables – it’s the way you make selections when issues get laborious. At Unframe, we’ve been intentional about making a tradition of possession, tempo, and honesty. We transfer quick, we hear laborious, and we push one another to be higher each day. That form of tradition doesn’t simply survive hyper-growth – it drives it.

Thanks for the nice interview, readers who want to study extra ought to go to Unframe.