Kamiwaza AI powers new Signal65 PINNACLE benchmark for measuring real-world enterprise AI performance. Kamiwaza AI Sep 09, 2026, 10:00 ET New independent benchmark moves beyond model rankings and token speeds to measure whether AI completes enterprise work correctly, at scale and at what cost SILVERTHORNE, Colo., Sept. 9, 2026 /PRNewswire-PRWeb/ - Kamiwaza AI, the secure AI orchestration platform that helps enterprises turn distributed data into secure, governed AI action, today announced that Signal65 PINNACLE, a new independent benchmarking framework, co-developed with and powered by Kamiwaza technology, is generally available for enterprise evaluations. This new framework is designed to measure whether AI systems successfully complete enterprise work, how much correct work infrastructure can sustain, and what each correct outcome costs. Co-developed by independent technology research and testing firm Signal65, PINNACLE addresses a growing gap in how enterprises evaluate AI infrastructure. Traditional benchmarks typically measure either model capability or infrastructure performance, leaving businesses without a clear way to determine whether a particular combination of models and hardware can successfully perform the work they actually need AI to do. PINNACLE introduces a new approach centered on correct work, evaluating model intelligence, silicon capacity and solution economics through the same real-world enterprise-focused workloads. At the foundation of this approach is technology developed by Kamiwaza, including its PICARD execution harness and KAMI and RIKER benchmark work. PICARD enables agents to perform multi-step jobs against generated enterprise environments using tools such as filesystems, databases and Python runtimes. Each environment is created with a known answer key held outside the agent's reach, allowing the completed work to be objectively graded in code rather than evaluated by another AI model or human reviewer. "Enterprises are being asked to make major AI infrastructure decisions on benchmarks that tell them the wrong story," said JV Roig, Senior Generative AI Platform Engineer, developer of the technology powering PINNACLE, Kamiwaza AI. "Much of what these tests contain is already sitting in the training data; it's impossible to separate memorization vs real capability. Even a clean score doesn't measure the capability enterprises need including multi-step jobs based on occupational skills, with real tools, messy data, decision-making under ambiguity, and resisting the tendency to hallucinate. Plus, it isn't only about the model, it's whether the combination you've chosen can actually complete the work your business needs done, reliably, at the scale you require and at a cost that makes sense. We built this technology to make that measurable, and Signal65's use of it as the foundation for PINNACLE shows how much that capability matters now." The first PINNACLE data set validates why enterprises cannot identify the right AI model or infrastructure configuration through conventional benchmarks alone and instead need workload-specific evaluation. Signal65 tested 44 configurations across 30 base models from 12 makers, including hosted APIs and open-weight models running on NVIDIA H200, NVIDIA B300 and AMD Instinct MI300X infrastructure. Among the initial findings: * Performance varied significantly by data conditions, as nine configurations completed at least 95% of jobs with clean, governed data, but only two reached that threshold with messy data. * Rankings changed by workload, with smaller and open-weight models competing with or outperforming frontier models on certain tasks. * Token pricing did not reflect the cost of successful work, with input tokens representing 65% to 91% of hosted-model task costs, while output-token pricing alone understated the cost per correct task by three to 11 times. The findings reinforce a core principle behind Kamiwaza's approach to AI orchestration: there is no single model or infrastructure configuration that is right for every enterprise workload. Kamiwaza's model- and infrastructure-agnostic orchestration gives enterprises the flexibility to make those choices based on what works best for their specific environment rather than being locked into a single stack. "These results validate why we've built Kamiwaza around orchestration and choice from the beginning," said Luke Norris, CEO and co-founder of Kamiwaza AI. "Enterprises shouldn't have to bet their AI strategy on one model or infrastructure provider, hoping it works across every workload. I'm incredibly proud of the pioneering work our team continues to develop to help enterprises not only orchestrate across models, infrastructure, data and agent, but make those decisions based on what truly delivers optimum outcomes for their business." "Agentic AI changes what enterprises need from benchmarking," said Ryan Shrout, President and General Manager of Signal65. "It isn't enough to know how capable a model is in isolation or how quickly a piece of hardware can generate tokens. Enterprises need to know whether the entire system can complete useful work correctly and economically. Kamiwaza's technology gave us the foundation to build a benchmark around that question, and Signal65 PINNACLE gives enterprises a way to start answering it with objective data." For enterprises questioning whether their current AI models and infrastructure can deliver the accuracy, scale and economics required for production, PINNACLE provides a new way to evaluate those decisions against the work that actually matters. To explore the results and learn how to evaluate your own AI environment, visit pinnacle.signal65.com. About Kamiwaza AI Kamiwaza AI delivers the distributed inference platform that makes AI deployment safe, governable, and scalable across any environment - cloud, on-prem, or edge. Its orchestration engine enables intelligent agents to run where data lives, with built-in contextual authorization that ensures security and compliance from day one. By unifying model deployment, agent tooling, and enterprise governance, Kamiwaza helps organizations accelerate AI transformation while maintaining full data sovereignty and control. Media Contact SOURCE Kamiwaza AI

Kamiwaza AI expands leadership team to accelerate enterprise and federal growth. Kamiwaza AI Aug 27, 2026, 09:00 ET New executives bring commercial, federal and operational leadership to help customers turn enterprise AI investment into measurable impact SILVERTHORNE, Colo., Aug. 27, 2026 /PRNewswire-PRWeb/ - Kamiwaza AI, the secure AI orchestration platform that helps enterprises turn distributed data into secure, governed AI action, today announced three strategic additions to its leadership team to expand its ability to help enterprise and government customers drive measurable AI outcomes at scale. John Drake joins as Chief Revenue Officer, Joseph Infantino as Vice President of Operations and Finance, and Daniel Davenport as Federal Field Chief Technology Officer. As enterprise AI adoption accelerates, the challenge is shifting from proving the technology works to translating that investment into measurable business and mission outcomes. Organizations need AI that can securely access distributed enterprise data, operate within existing governance boundaries, and take action across increasingly complex environments. Following the general availability of Kamiwaza 1.0, the company is expanding its leadership capabilities across enterprise engagement, federal technical strategy and operations to help customers execute against that opportunity. "Enterprises aren't measuring AI success by how many models or agents they can deploy. They're looking at whether those investments create meaningful mission and business outcomes," said Luke Norris, CEO and co-founder of Kamiwaza AI. "Achieving that takes more than technology. It requires execution, from securely connecting AI to the distributed and sensitive data that drives missions and businesses, to operating across complex customer environments, to building the commercial, operational and delivery foundation required for adoption at scale. Our expanded leadership strength will enhance the organization's ability to help government and enterprise customers turn AI investments into measurable impact while positioning Kamiwaza for its next phase of growth." As CRO, John Drake will lead Kamiwaza's global revenue strategy and go-to-market execution. He will strengthen the company's engagement with and support of its customers, helping them expand their access to secure AI orchestration and sustainably scale their AI environments. Drake brings extensive experience commercializing complex cloud and infrastructure technologies and building the partnerships that help organizations move emerging technologies into broader production use. Drake joins Kamiwaza from Amazon Web Services, where he led global go-to-market strategy for one of AWS's largest storage service portfolios. He previously spent over a decade at Faction, where he helped develop go-to-market relationships across the cloud and infrastructure ecosystem, and contributed to the company's year-over-year double-digit growth. Joe Infantino joins Kamiwaza as Vice President of Operations and Finance, where he will lead the operational and financial functions supporting the fast-growing company and its customers as deployments scale. Infantino brings in-depth experience scaling technology and services organizations, most notably as co-founder and COO of cybersecurity services company Cloudrise, growing the business from its 2019 founding through its 2024 acquisition by Exclusive Networks, and earlier as Vice President of Deloitte's Fusion Managed Services, leading end-to-end business operations from client acquisition to financial goals. At Kamiwaza, he will bring that same experience to bear as the company grows. As Federal Field CTO, Daniel Davenport will serve as a senior customer-facing technical executive for Kamiwaza's federal business unit. He will work with federal customers and industry partners to develop mission-aligned AI architectures and secure deployment patterns across cloud, on-premises, edge and classified environments. In this role, he will bridge emerging AI capabilities with the security, governance, accreditation and operational realities of mission-critical federal systems. Davenport brings more than 21 years of experience in Defense, Intelligence, and Space, and most recently served as Deputy Chief Engineer at SAIC, where his work included the U.S. Air Force Advanced Battle Management System (ABMS) digital infrastructure, building on prior senior SAIC roles. Together, the appointments strengthen Kamiwaza across three critical dimensions of its growth strategy: expanding market adoption, accelerating secure AI deployment in mission-critical environments and building the operational foundation to support a larger and more complex business. To learn more about Kamiwaza's work to scale secure, production-ready AI across enterprise and federal environments, visit: www.kamiwaza.ai. About Kamiwaza AI Kamiwaza AI delivers the distributed inference platform that makes AI deployment safe, governable, and scalable across any environment - cloud, on-prem, or edge. Its orchestration engine enables intelligent agents to run where data lives, with built-in contextual authorization that ensures security and compliance from day one. By unifying model deployment, agent tooling, and enterprise governance, Kamiwaza helps organizations accelerate AI transformation while maintaining full data sovereignty and control. Media Contact SOURCE Kamiwaza AI