Understanding Every Conversation
What is your AI actually doing? What are your customers telling you?
The problem
Your most important signals are hidden in conversations.
Every day your customers tell you what they need, what frustrates them and where your business is falling short. And increasingly, AI Agents are having those conversations on your behalf. Most organisations still have limited visibility into either.
Structured data
Transactions, dashboards, KPIs.
Unstructured conversations
Calls, chats, emails, tickets.
Humans and AI Agents
Part of the conversation is no longer human.
Your AI is talking to customers. Who is watching what it does?
Your vendor can tell you how its system is designed to work. Not how the Agent actually behaves in real conversations.
Thousands of conversations. Limited visibility.
The context is in the conversation. Analysing a fraction of them by hand is not enough.
The answer
One conversation layer. Two blind spots.
Companies need to know what people are saying. They also need to know what their AI is saying and doing. Lexic makes both visible.
You don't really know what your AI is doing.
You don't really know what your customers are telling you.
Independence
The company that built your AI should not be your only source of truth about how it behaves.
Lexic Compass audits agents from any vendor, and does not build the agents it audits. Flash Preview, full audit or continuous assurance are depths of the same offer — not different products.
Every Compass audit closes with a single Trust Score from 0 to 100. The four pillars below are its weighted components, not four separate scores.
Trust Score — 0 to 100
Integrity & Safety
Adversarial probes for prompt injection, jailbreaks and data leakage, run independently of the agent's vendor.
Regulatory Trust
Disclosure, traceability and evidence a compliance team can defend to a regulator or a board.
Operational Reliability
Task success, hallucination rate and failure handling against your defined agent contract.
Experience Trust
Tone, consistency and real escalation to a human when the customer needs one.
Integrity & Safety
30%Adversarial probes for prompt injection, jailbreaks and data leakage, run independently of the agent's vendor.
Regulatory Trust
30%Disclosure, traceability and evidence a compliance team can defend to a regulator or a board.
Operational Reliability
20%Task success, hallucination rate and failure handling against your defined agent contract.
Experience Trust
20%Tone, consistency and real escalation to a human when the customer needs one.
People must be told they are interacting with an AI system — clearly, in time, and verifiably. And you must be able to evidence it.
100% of the agents we audited failed to disclose as AI when a user asked directly.
They disclose when the script says so. Not when the customer asks.
Executives of these companies are already decoding conversations














The evidence
We audit AI agents already talking to customers. This is what we keep finding.
did not disclose as AI when a user asked directly
They disclose when the script says so. Not when the customer asks.
average Trust Score across audited agents
clears the audit without conditions
fail escalation to a human
Across nearly 50 independent audits of AI agents in production.
How it works
From conversation to intelligence to control.
Capture
Calls, chats, emails, tickets and AI Agent conversations.
Understand
Continuous analysis that surfaces meaningful signals.
Monitor
Behaviour, patterns, failures and emerging risks.
Act
The evidence teams need to improve and to control.
Frequently asked questions
Can our AI vendor audit its own agent?
How do you audit an AI agent that is already in production?
What does EU AI Act Article 50 require from a customer-facing AI agent?
Is a Lexic Compass audit a certification?
How fast do we get the first result?
What is Lexic Pulse?
How does Lexic Pulse compare to Gong or Observe.AI?
Next step
Every conversation leaves evidence. Are you listening?
Understand what your customers are telling you. Know what your AI is actually doing.
From The Signal
All research