Lynx, together with founding industry participants Critical Software, Edera, Metavonics, OmniTrust, PACE, RunSafe Security, and TASKING, today announced launch of AI Deployment Gap Initiative, a vendor-neutral coalition dedicated to advancing deployment of trustworthy physical AI in mission-critical systems. Initiative invites AI ecosystem to help define best practices for deploying physical AI at edge that is deterministic, governable, secure, and sustainable in real-world environments. Announcement was made from San Jose, California, on September 9, 2026.
AI models keep improving at rapid pace, but organizations deploying AI in aerospace, defense, robotics, industrial automation, transportation, critical infrastructure and other mission-critical domains face separate problem entirely: getting those models to operate predictably, securely and sustainably under real-world constraints. Systems built for lab don't automatically hold up in field, and initiative sets out to close gap.
Initiative began with publication of "Closing the AI Deployment Gap: A Manifesto for Deployable AI." Manifesto lays out principles of safe AI deployment while identifying four challenges industry must address:
Execution Gap - AI must execute deterministically and predictably.
Integration Gap - AI must coexist with heterogeneous and mission-critical systems.
Governance Gap - AI decisions must be observable, traceable, and accountable.
Lifecycle Gap - AI must be maintainable, certifiable, and sustainable throughout long operational lifecycles.
Initiative sets common engineering foundation that participating organizations agree essential for deploying AI into systems where failure isn't option. To close gaps, participants endorsing shared set of engineering principles: Determinism by Design, Observability by Default, Integration Across the Stack, Runtime Governance, Security by Design, Lifecycle-Ready Engineering, Deployment as First-Class Concern, Ecosystem Collaboration.
Beyond endorsing manifesto, founding participants will collaborate on educational resources for broader industry: deployment best practices, technical guidance, deployment-readiness frameworks, reference architectures, joint whitepapers, deployment blueprints, operational case studies and lessons learned from operational deployments. Goal is to help organizations move faster from AI innovation to trusted operational capability.
"Industry has spent last decade learning how to build increasingly capable AI models. Next decade will be defined by ability to deploy those models into systems that must be trusted, governed, and sustained over years of operation," said Tim Reed, CEO of Lynx. "Closing AI deployment gap requires collaboration across entire ecosystem, and that's exactly what initiative intended to foster."
"In safety-critical and mission-critical environments, trust must be engineered, not assumed. Dependable AI is not optional," said Joao Galego, head of AI at Critical Software. "Every decision must be predictable, verifiable, and accountable, and every part of ecosystem must be held to same standard."
"No single company closes AI deployment gap alone. Organizations building AI today are all running into same wall models that perform brilliantly in lab and then have to survive years in field, under real constraints, with real consequences if something breaks," said Emily Long, co-founder and CEO of Edera.
Initiative open to organizations across AI ecosystem, such as silicon providers, platform and operating system vendors, AI framework developers, cybersecurity companies, system integrators, OEMs and end users who share commitment to advancing deployable AI.
About Lynx
Lynx delivers safe, secure, and modular software platform for edge computing in aerospace, defense, industrial, and autonomous mission-critical systems. Purpose-built for real-time, mixed-criticality environments, Lynx enables CPU- and GPU-based workloads, including AI, to coexist without interference on single mission computer. Its MOSA-aligned architecture reduces certification scope, accelerates deployment, sustains systems across 10- to 30-year lifecycles.
