Cyara Ships Agentic CX Trust Platform, Scores 100% of AI Agent Calls

Cyara has launched the Agentic CX Trust Platform, a rebuild of its core technology that scores 100% of live AI agent conversations for quality and compliance and turns every production failure into a test the agent must pass before its next release. The company positions itself as an "AI trust company for customer experience," and the pitch is blunt: the hard part isn't the agents, it's trusting them with your customers.

At the center sits AI Trust Observability (a vendor-neutral monitoring layer that judges whether conversations went right, not just whether they happened). Today, the vendor that builds an AI agent usually supplies the analytics that say it works — a model Cyara compares to trusting financial reporting from the party being audited. An agent can pass every pre-launch test, then break policy on a live call that still logs as a success.

"Enterprises are being asked to trust AI agents on the word of the companies that built them," said Sushil Kumar, Chief Executive Officer at Cyara. "We would never accept that for financial reporting, and we shouldn't accept it for a system that authenticates customers and makes commitments in a brand's name. Independent scoring turns an AI deployment from an act of faith into something a business can defend."

Why does proof matter more than capability?

Every enterprise now sits somewhere on the path from human-led to AI-led service. Where earlier bots followed scripts, today's AI agents reason, decide, and act on their own — looking up accounts, changing orders, and issuing refunds in a brand's name. One wrong answer can cost a customer relationship; one policy violation can create regulatory exposure.

The consequence: without a way to prove agent behavior, most enterprises limit AI to simple requests and keep high-value journeys like billing and authentication off-limits. Cyara's read is that the barrier is not capability. It's proof.

What does AI Trust Observability actually do?

The layer works across any vendor's agents, including homegrown ones. Its working parts:

• 100% scored, not sampled. Every production conversation is evaluated against the same standard.
• Regulation-linked scorecards. Trust criteria and hard-stop rules are tunable per journey, with versioned packs covering the EU AI Act, HIPAA, PCI DSS, and GDPR.
• Compliance gates kept apart from quality scores. A fluent, friendly call that breaks policy still fails.
• Evidence, not just a score. Every verdict traces to the exact conversation turn, with reasoning and timestamp — audit-ready on request.
• You know first. A violation reaches the right person the moment it happens, before it hits the escalation queue or a regulator.
• Production becomes the next test. Every material failure becomes a regression test the agent must clear before it ships again.

"When agentic AI fails, most teams fix the incident but leave the test gap that let it through, so the failure returns with the next release, often logged as a success," said Amitha Pulijala, Chief Product Officer at Cyara. "A failure may happen once. It should never happen twice."

Cyara invites enterprises to request a demo at cyara.com to see the scoring run on their own production conversations.

How does the platform cover the whole customer journey?

Customers don't experience an AI agent in isolation. They experience a journey that runs through carriers, IVR (interactive voice response menus), digital channels, AI agents, and handoffs to people — and failures hide in the seams. The platform covers the full agent lifecycle across three connected functions:

• Test — proof before launch. Real-world agent testing with real personas, audio, and model versions; end-to-end journey testing from carrier to human handoff; load testing at true peak volume.
• Monitor — detect outages before customers do. End-to-end journey monitoring from carrier to AI agents and other channels to human handoff, across 420+ carriers in 145+ countries.
• Observe — measure live quality and compliance. AI Trust Observability scores every AI conversation, while human agent observability covers the desktop, network, and call quality behind every human-handled call, wherever agents work.

A production-to-test loop ties it together: what breaks in production becomes the next pre-launch test. Enterprises can start where they are — human-led, hybrid, or AI-led — with no rip-and-replace.

"Successful teams treat AI agents as live systems that need discipline before, during, and after deployment," said Ian Jacobs, VP and Lead Analyst at Opus Research. "They don't wait for customers to find the edge cases. They build CX assurance into the operating model."

Cyara has not disclosed pricing. The takeaway is simple: independent scoring of every AI conversation is the company's answer to earning the right to move billing and authentication to AI.