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ICA AI Announces Pre-Launch of +Trusted™, AI-Native Infrastructure That Makes UCaaS AI Profitable at Scale

Written by Amy Ralls | Jan 22, 2026 5:01:18 PM

Patented platform enables caller verification, relationship memory, and up to 85–90% reduction in AI inference costs

BOCA RATON, FL - January 2026 - ICA AI, Inc. today announced the pre-launch introduction of +Trusted™, an AI-native infrastructure platform designed specifically for UCaaS providers. The platform addresses a fundamental challenge facing the communications industry: AI features that improve user experience but erode margins as usage grows.

Unlike conventional AI systems—where every interaction incurs recurring inference costs—+Trusted introduces a reusable intelligence model that allows AI capabilities to become more efficient and more profitable over time.

“The AI industry has a structural economics problem,” said Ray Sheppard, Founder and Visionary of ICA AI. “Most AI systems get more expensive the more successful they become. We built +Trusted to invert that curve—so intelligence compounds, costs fall, and AI becomes sustainable at scale.”

Built for UCaaS Economics

+Trusted is purpose-built for UCaaS environments, where high-volume, repetitive communication has made traditional AI deployments prohibitively expensive. The platform combines caller verification, relationship-aware personalization, and patented cost-optimization architecture into a single AI-native infrastructure layer.

At the core of +Trusted is a patented Semantic Library architecture that allows the system to recognize previously handled intents and execute them deterministically—without invoking large language models (LLMs). New intents are learned once, added to the library, and reused across the network.

As a result, LLM usage typically declines from near-total reliance at launch to single-digit percentages within the first year of deployment, enabling AI services that improve margins rather than compress them.

Four Integrated Capabilities

+Trusted delivers four tightly integrated capabilities designed to work together:

· Security: Patented relationship-based caller verification blocks unknown or fraudulent callers at the network level—before reaching users and before incurring AI cost.

· Personalization: Permanent relationship memory allows AI to recognize callers and context without storing transcripts, delivering a more natural and trusted experience.

· Affordability: Lower operating costs allow UCaaS providers to offer enterprise-grade AI capabilities to organizations of every size, including SMBs.

· Profitability: Reusable intelligence dramatically reduces inference costs over time, enabling sustainable AI economics.

Protected by Infrastructure Patents

The +Trusted platform is protected by five granted U.S. patents covering foundational AI communication infrastructure, including AI agent architecture, adaptive hybrid reinforcement learning, dynamic relationship fingerprinting, real-time AI screening, and reputation-based trust scoring.

“These patents protect the architecture itself, not surface-level features,” said Tim Annis, Director of Licensing at ICA AI. “Replicating this model would require competitors to redesign their systems from the ground up.”

Industry Review

+Trusted is being presented for industry review at the Delray Beach Communication Alliance Convention on January 21, 2026.

Pre-Launch Availability

+Trusted is currently available in pre-launch through selective licensing and partner engagements with UCaaS providers. The platform integrates with existing infrastructure and supports incremental deployment. General availability will follow after completion of the pre-launch review period.

About ICA AI, Inc.

ICA AI, Inc. develops AI-native infrastructure for the communications industry. Its +Trusted™ platform enables UCaaS providers to deliver secure, personalized, and economically sustainable AI services at scale. ICA AI holds five U.S. patents covering foundational advances in AI communication systems and is headquartered in Boca Raton, Florida.