The other side of the table should be hard.

Why we built Sparring

Most organisations spend heavily on communication training and almost nothing on practice. People watch a video, read a framework, maybe role-play once with a colleague who is too kind to push back — and then face a furious customer or a defensive report with no rehearsal. The result is predictable: the same costly conversations go wrong, in the same ways, every quarter.

We started from a simple observation. The reason practice doesn't happen is that the other side is never realistic. Colleagues are polite. Chatbots agree with everything. Nobody tells you, with proof, exactly where you lost the room.

So we built counterparts that behave like people: they have a stance you can see and a motive you can't, they apply pressure, and they move only when something genuinely earns it. Then we built a judge that is not allowed to say anything it cannot quote from the transcript.

Then the agents arrived

In 2025 our customers started putting AI agents in front of their own customers — support bots, sales assistants, HR helpdesks. They asked us a question we couldn't ignore: "Can your counterparts test our bot?"

They could. The same adversarial counterparts that train a human agent will try to extract a discount from a sales bot, bypass a support bot's identity check, or inject instructions into an HR assistant. The same evidence-based judge scores the result. That became Sparring Arena: red-teaming and regression testing for conversational agents, with a pass/fail gate for CI.

Today one engine serves both markets, and that is the point. A company can ask, for the first time, how its people and its agents handle the same conversation — and see the answer quoted back.

What we believe

• Evidence or nothing. A judgment without a quote is an opinion. Our verifier deletes it.
• Practice is not assessment. Scores exist to help people improve. Using them for employment decisions is prohibited in our terms, and learners are told what managers can see.
• Method over prompts. Every scenario cites published sources — negotiation, de-escalation, feedback, security — and every skill maps to a competency model. We teach the why.
• Honest numbers. The figures on this site are measured on our own product before every release, and we publish the method.