Your AI Talks to More Customers Than Your Whole Contact Center, and Every Word Is on the Record

Conversational AI governance means one runtime assurance layer across every chat, voice, and service desk agent that touches PII, consent, and brand exposure, aligned to the EU AI Act, NIST AI RMF, GDPR, and TCPA. Disseqt tests, protects, and proves your customer experience AI.

See solutions for customer experience

If you need to govern a specific surface, jump to the solutions in this vertical: IT service desk agents, customer-facing chatbots, and voice channels.

The problem for customer experience AI

Conversational AI scaled faster than any other enterprise use case, and it talks directly to the customer.

A chatbot answers product and account questions. A voice agent handles inbound calls. A service desk agent resets access and reads from internal systems. Each one holds a live conversation, which means each one can leak PII, hallucinate a policy, mishandle consent, take an injected instruction, or say something that damages the brand, all in the moment, in front of the customer.

The regulators that apply are the ones built around data and consent. The EU AI Act sets transparency obligations for AI that interacts with people and binds higher-risk uses to Article 9 and Article 72. GDPR and UK GDPR govern the personal data flowing through every conversation. In the US, TCPA governs consent for voice and SMS outreach, and state biometric laws such as BIPA apply to voice agents that process voiceprints. The NIST AI RMF is the framework many enterprises adopt to organise all of it.

The defining feature of CX AI is that there is no second chance. A bad underwriting decision can be reviewed before it lands. A bad response in a live conversation has already reached the customer. Governance for CX has to act in the runtime path, not after the fact.

The Disseqt answer, mapped to the three pillars

A CX leader running chat, voice, and service desk agents does not need three governance tools that do not talk to each other. They need one runtime assurance layer across every conversational surface. Disseqt is the only unified AI assurance platform covering testing, monitoring, policy, audit, and compliance in one place.

The three pillars are the AI Assurance Lifecycle. For CX, the weight sits on runtime enforcement.

Protect and Enforce

In conversation, the runtime is everything. Protect and Enforce applies guardrails on every output, enforces policy on every agent decision, runs per-span input validation on the prompt path to catch injection, scores toxicity on live conversations, detects drift away from the intended topic, and adds explainability.

That is what stops a chatbot leaking PII, a voice agent breaking consent rules, or a service desk agent acting on an injected instruction, in the moment, before the customer sees it. It is the difference between a governed agent and Agentic Theatre, an agent that looks helpful while quietly mishandling data.

Test and Detect

Before a chat, voice, or service desk agent goes live, Test and Detect runs it against an adversarial envelope. Sixty-five ML-based validators across four families (base, RAG, agentic, MCP), 84 jailbreak techniques including single and multi-turn attacks, a Live Vulnerability Database, and cross-LLM benchmarking.

Multi-turn matters here, because conversational attacks build over several messages. Find the jailbreak and the data-leakage path in private, before someone finds them in public.

Prove and Comply

Prove and Comply turns every conversation control into evidence. Tamper-evident audit trails, compliance dashboards, and mapping to the EU AI Act (Article 9, Article 72, high-risk focus), GDPR, and ISO/IEC 42001. Enterprise auditability is built in: SOC 2, SSO and SCIM, RBAC.

When a data protection regulator or an internal review asks how a conversation was handled, the answer is a reconstructable record.

Why ML validators matter in customer experience

A conversation moves at human speed, and a check that slows it down breaks the experience.

Disseqt validates with ML-based validators, not LLM-as-judge. That cuts the cost of validation to a level that makes continuous, real-time checking viable: around 99% less water, around 98% less CO2, and sub-50ms inline latency.

Sub-50ms means a policy, PII, and toxicity check can sit inline on every message without the customer feeling the delay. That is what lets enforcement run on every conversation at contact-center scale, rather than on a reviewed sample after the fact.

Where this fits in the AI Assurance Lifecycle

Customer experience is one view of the wider discipline of AI governance, framed for the CX, contact center, and service leaders accountable for what an agent says.

The work spans the full lifecycle: Test and Detect before launch, Protect and Enforce at runtime, and Prove and Comply for the evidence. It connects to broader AI risk management for risk teams, and to AI compliance for the regulatory mapping. The view of where assurance sits in the stack is the assurance layer.

Solutions in this vertical

Disseqt covers each conversational surface CX teams run today. Each has its own deep-dive page.

IT service desk agents. Service desk agents reset access and read internal systems, which exposes them to data leakage and instructions that overstep their scope. See AI assurance for IT service desk.

Customer-facing chatbots. Chatbots answer at volume in the open, where hallucination, jailbreaks, and off-brand responses are the live risk. See AI assurance for agentic customer-facing chatbots.

Voice channels. Voice agents handle calls under consent and biometric rules, where TCPA and state biometric law apply on top of the conversation risk. See AI assurance for voice channels.

Regulatory scope

This hub covers the regulators that bind conversational AI:

• EU AI Act. Transparency obligations apply to AI that interacts with people, with Article 9 and Article 72 obligations for higher-risk conversational uses.

• NIST AI RMF. The voluntary framework many enterprises adopt to organise conversational AI governance.

• GDPR and UK GDPR. Govern the personal data flowing through every customer conversation.

• TCPA. Governs consent for voice and SMS outreach in the US.

• US state biometric laws (BIPA and equivalents). Apply to voice agents that process voiceprints and other biometric data.

Who this is for

This hub is for the people accountable for what a conversational agent says to a customer.

Heads of customer experience, contact center, and digital service who own the channels. Heads of AI governance and chief risk officers who own the institutional answer. Data protection and compliance leads working across GDPR, TCPA, and biometric law. Engineering teams shipping chat, voice, and service desk agents into production.

It is also for the global systems integrators and IT consulting partners standing up CX AI programmes that their clients will audit.