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Unframe introduces a modular AI platform that delivers tailored enterprise solutions within days, eliminating lengthy development cycles and upfront costs. Backed by $50 million in funding, it enables organizations to deploy AI securely without sharing data externally. Its outcome-based pricing and reusable building blocks offer a scalable alternative to legacy systems and point solutions.
Why Legacy Enterprise AI Fails to Deliver
Enterprise software has long been marked by complexity, inefficiency, and high operational costs. Organizations often face a limited set of options: legacy systems that are outdated, rigid point solutions that lack flexibility, or custom development cycles that are slow and expensive. These approaches frequently result in extended implementation timelines, security trade-offs, and tools that fail to scale across the organization. The disconnect between enterprise needs and the tools available to fulfill them continues to create friction in innovation efforts.
Unframe Enters the Scene With a $50M Statement
Unframe has emerged from stealth with $50 million in funding, signaling a shift in how enterprises can approach AI. The company’s leadership team includes CEO and co-founder Shay Levi, who previously built Noname Security. Backers of Unframe include Bessemer Venture Partners, TLV Partners, Craft Ventures, Third Point Ventures, SentinelOne Ventures, Cerca Partners, and Terra Nova Ventures.
Within one year, Unframe has achieved millions in annual recurring revenue and established partnerships with global enterprises. The funding will support continued platform development and expansion into more enterprise environments.
What Makes Unframe’s AI Approach Different
Unframe introduces a turnkey AI platform designed to bypass traditional bottlenecks. Organizations define the use case, and Unframe delivers a fully operational solution within days. The system eliminates upfront payments, removes user or query limitations, and ensures data remains within the enterprise’s secure environment.
At its foundation, the platform uses a library of reusable AI building blocks engineered to solve real enterprise problems. These components are orchestrated through “Blueprints,” which are specification files that control integrations, interfaces, and overall functionality. This modular framework allows companies to implement tailored AI tools without developing them from scratch.
Three Core Areas Unframe Tackles With AI
Unframe’s platform focuses on three main categories:
- Observability: Enhancing system monitoring and transparency
- Data Extraction & Abstraction: Structuring and organizing enterprise data efficiently
- Automation & Agents: Deploying intelligent agents that automate key processes
Each AI solution is composed from pre-built components and is tailored to fit the customer’s technical environment, objectives, and workflows. The modular structure ensures fast deployment without compromising customization or security.
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Why CIOs and CTOs Pay Attention to Unframe
Unframe introduces a low-friction model for AI deployment. Enterprises can test fully functional solutions with no upfront commitments. Pricing is outcome-based, meaning organizations pay only after realizing tangible results.
There is no requirement to export or expose sensitive internal data during setup. The process requires minimal internal resources, with no need to manage multiple disconnected tools.
Key features include:
- Turnkey delivery of enterprise-grade AI
- Modular building blocks tailored to specific use cases
- No vendor lock-in or long implementation cycles
- Built-in flexibility for integration with existing tech stacks
Early Traction Proves the Demand Is Real
Unframe has generated millions in ARR in its first quarter of selling. This traction occurred before its public launch, suggesting early validation among enterprise clients. Companies are already using the platform to streamline internal operations, without the typical trade-offs associated with AI deployment.
Customers report reduced overhead, shorter build times, and secure usage of AI without compromising data privacy. The model eliminates the need for coordinating across fragmented point tools or lengthy internal development pipelines.
What This Means for the Future of Enterprise AI
The adoption of Unframe’s platform reflects a larger trend toward flexible, cost-effective AI that adapts to enterprise complexity. With its Blueprint system and modular approach, Unframe eliminates the traditional delays and inefficiencies found in legacy AI adoption.
Organizations are increasingly looking for tools that integrate seamlessly, deliver measurable results, and maintain control over data. Unframe aligns with this direction by offering scalable AI frameworks tailored to business-specific outcomes.
Unframe Sets a New Benchmark for Agile AI Deployment
Unframe’s emergence is defined by speed, precision, and flexibility. With a modular platform powered by reusable building blocks, enterprises can now access AI tools that fit their exact needs in record time. The outcome-based pricing structure and zero-barrier testing create a model built for enterprise adoption.
As more organizations seek solutions that deliver quick, secure, and adaptable AI, Unframe establishes itself with a model that breaks from the traditional mold.
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