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 know-how, he focuses on constructing transformative options.
Unframe is an all-in-one enterprise AI platform headquartered in Cupertino, California, that permits companies to convey any distinctive AI use case to life in hours, quite than months. By means of its Blueprint Method, Unframe collaborates with massive enterprises globally to implement options throughout observability, information abstraction, clever brokers, and modernization. Unframe makes use of outcome-based pricing, permitting prospects to expertise and evolve any resolution they need, risk-free. Unframe is LLM agnostic and does not require fine-tuning or coaching – foundationally altering what is feasible for big 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 house that made it the suitable time and alternative?
I really left Noname earlier than the acquisition discussions began. What I noticed was a large wave coming, CIOs have been underneath strain to undertake AI quick, however the tooling accessible to them simply wasn’t enterprise-ready. They have been both piecing collectively level options with no governance, or ready on inside groups to construct from scratch. Neither path scaled, and each launched threat.
That was the sign. I noticed enterprises didn’t simply want entry to AI – they wanted a platform that gave them management, pace, and adaptability 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 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 suitable guardrails – safe information 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 information flows, implementing 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 the whole lot down.
With AI, we’re seeing the identical sample repeat. Each workforce desires to maneuver shortly, however with out the suitable construction, you get fragmentation, duplication, and blind spots. That have formed our pondering with Unframe. We needed to present enterprises a approach to undertake AI in a means that’s unified, safe, and truly 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 stage of adoption so shortly?
We didn’t take the normal route of sluggish experimentation or restricted pilots. From day one, we have been out available in the market, partnering with world enterprises on high-impact, real-world initiatives. These weren’t remoted use instances – 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 associate throughout a number of domains, not only a vendor. If 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 means of how Unframe makes this potential?
We’ve constructed lots of of deep technical constructing blocks into the Unframe platform. When a brand new resolution is deployed, it’s not ranging from zero – it’s tailor-made by means 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 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, 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 essential 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 almost all organizations aren’t set as much as deal with.
We designed Unframe to work with current fashionable fashions in a means 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 power 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 nicely 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 essential once you’re working with world corporations and distributed workforces throughout totally different nations, roles, and languages. A chat-style interface helps stage the enjoying subject.
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 end 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 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 method 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 should not solely nice at what they do, however who thrive in ambiguity and transfer with urgency. For me, constructing a management workforce 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 identical. It’s not ping-pong tables – it’s the way you make choices 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 sort of tradition doesn’t simply survive hyper-growth – it drives it.
Thanks for the good interview, readers who want to study extra ought to go to Unframe.
