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 means of its Blueprint Strategy, Unframe collaborates with giant enterprises globally to implement options throughout observability, knowledge abstraction, clever brokers, and modernization. Unframe makes use of outcome-based pricing, permitting clients 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 big enterprises searching 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 house that made it the proper time and alternative?
I truly left Noname earlier than the acquisition discussions began. What I noticed was a large wave coming, CIOs have been underneath stress to undertake AI quick, however the tooling obtainable to them simply wasn’t enterprise-ready. They have been both piecing collectively level options with no governance, or ready on inner groups to construct from scratch. Neither path scaled, and each launched threat.
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 strategy you’re taking with Unframe?
Safety is in our DNA. At Noname, we realized that innovation with out governance shortly results in threat. That lesson carries over on to AI. From day one at Unframe, we’ve baked in the proper 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, imposing compliance, or integrating with legacy programs.
Had been there any frequent ache factors throughout enterprises within the API safety house that helped inform your imaginative and prescient for AI adoption?
Undoubtedly. 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 threat – and it slowed all the pieces down.
With AI, we’re seeing the identical sample repeat. Each crew needs to maneuver shortly, however with out the proper construction, you get fragmentation, duplication, and blind spots. That have formed our pondering with Unframe. We needed to provide enterprises a technique to undertake AI in a manner that’s unified, safe, and really works throughout groups and programs – not simply in remoted pockets.
Unframe is gaining traction with main enterprises and achieved ARR within the hundreds of thousands inside a yr – how did you obtain this degree of adoption so shortly?
We didn’t take the normal route of gradual experimentation or restricted pilots. From day one, we have been out out there, partnering with international enterprises on high-impact, real-world initiatives. These weren’t remoted use circumstances – they have been strategic initiatives tied to core components of the enterprise. That’s what earned us belief and helped Unframe turn into a strategic accomplice throughout a number of domains, not only a vendor. While you ship actual outcomes quick, adoption follows.
You’ve spoken about lowering AI deployment from months to hours. Are you able to stroll us by way of how Unframe makes this attainable?
We’ve constructed tons 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 by way of a blueprint that maps these parts to the consumer’s particular wants. That’s how we scale back deployment from months to hours.
Inform us extra concerning the Blueprint Strategy – what makes it distinctive, and why is it so highly effective for enterprise AI use circumstances?
The Blueprint Strategy is how we ship tailor-made AI options at scale – with out ranging from scratch. Every blueprint maps the logic, parts, 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 necessary 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, growing prices, and creating upkeep overhead that the majority organizations aren’t set as much as deal with.
We designed Unframe to work with present trendy fashions in a manner that also delivers tailor-made, high-quality outcomes – with out the complexity. By staying LLM-agnostic, we give enterprises flexibility, sooner time to worth, and the flexibility to evolve because the mannequin panorama modifications. The purpose isn’t to coach fashions – it’s to unravel issues. And you are able to do that extremely properly 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 strong entry level – it makes AI immediately accessible to enterprise customers, with out coaching or technical ramp-up. That’s particularly necessary whenever you’re working with international firms and distributed workforces throughout totally different nations, roles, and languages. A chat-style interface helps degree the taking part in 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 substitute 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 consumer, however to the issue they’re attempting to unravel.
What classes from scaling Noname Safety to a $1B+ valuation and $450M acquisition are you making use of at Unframe?
Give attention to fixing actual, pressing issues – and do it with enterprise-grade execution from day one. At Noname, we realized that scale comes from belief, and belief comes from delivering quick with out reducing 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 strategy to constructing management groups and firm tradition in hyper-growth environments?
In hyper-growth, you don’t have the posh of figuring issues out slowly – so that you want individuals round you who are usually not solely nice at what they do, however who thrive in ambiguity and transfer with urgency. For me, constructing a management crew begins with belief, readability, and shared values. Everybody needs to be aligned on the place we’re going, and equally dedicated to proudly owning their a part of the journey.
Tradition is similar. It’s not ping-pong tables – it’s the way you make selections when issues get onerous. At Unframe, we’ve been intentional about making a tradition of possession, tempo, and honesty. We transfer quick, we pay attention onerous, and we push one another to be higher day by day. That type of tradition doesn’t simply survive hyper-growth – it drives it.
Thanks for the good interview, readers who want to be taught extra ought to go to Unframe.Â
