Equitus KGNN Achieves DoD Tradewinds Awardable Status as Structured AI Infrastructure Demand Accelerates

Knowledge Graph Neural Network Platform Validated for Production Deployment Ahead of 2026 Enterprise AI Inflection Point

CLEARWATER, FL, UNITED STATES, December 17, 2025 /EINPresswire.com/ -- Equitus announced today that its Knowledge Graph Neural Network (KGNN) platform has achieved awardable status through the Department of Defense Tradewinds Solutions Marketplace, validating the platform as production-ready infrastructure as enterprises shift from experimental AI to structured, mission-critical deployment.

The recognition positions KGNN for accelerated government adoption while confirming its readiness for regulated industries facing mounting pressure for AI explainability, data governance, and operational reliability.

"The AI market is reaching an inflection point," said Mark Rigney, CEO at Equitus. "First-generation strategies focused on prediction and generation. The next phase requires structure, governance, reasoning, and provenance. Tradewinds validation confirms KGNN is ready to serve as foundational infrastructure for organizations that need AI they can trust, explain, and audit."

From Proof-of-Concept to Production Infrastructure

Tradewinds awardable status creates a direct pathway for government agencies to adopt KGNN without lengthy procurement cycles, materially shortening time-to-revenue across defense, intelligence, and federal civilian agencies. The assessment evaluated deployability, integration readiness, scalability, and mission impact, criteria that resonate equally across commercial enterprises requiring similar technical maturity.

KGNN addresses a persistent industry barrier: most knowledge graph implementations succeed as proofs-of-concept but fail at production scale due to manual construction and integration complexity.

"The knowledge graph market is littered with successful proofs-of-concept that never reached production," said Michael Avina, CTO. "The failure point isn't the technology, it's the deployment model. KGNN eliminates that barrier through autonomous operation. The platform maintains structure, updates semantics, and scales infrastructure without linear engineering investment. That's what separates production infrastructure from research projects."

Strategic Positioning for 2026

Multiple forces are converging to make 2026 a breakout year for structured AI infrastructure:

- AI governance regulations requiring explainability and auditability

- Accuracy demands exposing LLM limitations in mission-critical contexts

- Data sovereignty requirements driving on-premises AI deployment

- Integration complexity as enterprises unify hundreds of data sources

Equitus is positioned ahead of this shift. While competitors add reasoning capabilities retroactively, KGNN was purpose-built as autonomous infrastructure for structured AI.

Tradewinds status also strengthens the company's position for partnerships and strategic transactions, making KGNN visible and actionable to defense primes, system integrators, and enterprise AI vendors seeking structured reasoning capabilities.

"We're providing the infrastructure layer that makes AI trustworthy, explainable, and mission-ready," said Cedric Signori, CMO. "Going into 2026, enterprises that can't deploy governed, explainable AI will simply stop deploying AI, and lose the race to those who solved it first. Whether you're a government agency, regulated enterprise, commercial or platform vendor, that's the inflection point we're built for."

KGNN is optimized for on-premises and hybrid cloud deployment with support for IBM Power and Dell x86 architectures, integrating with existing data infrastructure without requiring wholesale system replacement.

Organizations interested in learning more can visit www.equitus.ai or contact info@equitus.us

About Equitus

Equitus develops AI-driven intelligence platforms that unify data, enable reasoning, and support decision-making in mission-critical environments. Its platforms, including Knowledge Graph Neural Network (KGNN) and Video Sentinel (EVS), are deployed across defense, public safety, and commercial enterprise sectors requiring high standards of accuracy, security, and operational reliability.

Cedric Signori
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