The crash test for AI agents.

Mantia is a pre-deployment testing platform for customer-facing AI agents.

Mantia, playing a first-time buyer

What’s your best rate? I need the absolute best.

Bank’s chatbot

Our best rate today is 4.75%.

Finding · Pricing integrity

High

The bank promises 5.00% on every mortgage, so 4.75% is the wrong rate.

Illustrative example. Product preview with sample data. EazyBank is a fictional bank.

AI agents are going live. Proving they’re ready is the hard part.

That’s why we built Mantia: a platform that simulates realistic conversations with your agent and pushes it to its limits, so you can fix what’s broken or release with confidence.

Meet Mantia.

You define ready. We find out whether your agent is.

Mantia’s overview for EazyBank: one agent scores 92 and is not ready to release, the other scores 99 and is ready to release, with a score for each domain below.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.

01Connect

Connect and configure your agent.

  1. Connect your agent, so we can talk to it.

  2. Select your goals, so we test what’s important.

  3. Share your knowledge base, so we know what’s true.

Setting up a new agent in Mantia: choose how Mantia reaches it, by API or another channel, then give its endpoint URL and how Mantia gets access.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.
Mantia recommends goals for the new agent from what it does, what it must never do, its channel, and its documents, above a list of goals under Truthfulness, such as Pricing integrity.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.
Setting up a new agent in Mantia: the reference documents it is tested against, grouped as product catalogue, fees and charges, policies, and knowledge base, each one selected.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.

02Simulate

Unscripted conversations that adapt as they go.

We talk to your agent as everyday customers, confused users, and attackers.

A test of one agent in progress: discovery and mapping are done, simulation and evaluation are running, with the conversations run so far, the goals decided and a live score of 94, and each goal marked passed, failed, simulating, or queued.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.

03Prove

Proof you can act on.

  1. See how your agent performed, and whether it clears the bar you set for release.

  2. Trace every finding to the conversation behind it, so you know what to fix.

The result for one agent: a Mantia score of 92, below the pass line, and the verdict: not ready to release, because the score is below its threshold of 95.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.
A Pricing integrity finding, quoting what the agent said: the number on its own is 5.25%. It fails because the goal says any mortgage rate other than 5.00% is unsupported. Severity medium.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.

An assessment report for your team.

In development: a two-page summary for your board, and a pack that maps the evidence to your obligations.

Report templates in the product preview: an assessment report, a two-page board summary, a pack that maps testing evidence to obligations, and a fix check comparison.
Product preview with sample data, which may include features in development. EazyBank is a fictional bank.

Ready has no single measure. It’s the whole experience.

  • Experience

    Does it deliver the experience you built it for?

  • Truthfulness

    Is everything it says correct?

  • Conduct

    Does it treat people the way your best people would?

  • Safety

    Could anything it says harm anyone?

  • Data & Privacy

    Does it guard what it knows about people, and about you?

  • Security

    Can anyone make it do what it shouldn’t?

We test what your agent has to get right before it goes live, against the goals you confirm.

This is all we do, and we do it brilliantly.

  1. We verify independently.

    We don’t sell agents, or the platforms they run on. No stake in the answer, just one question: is your AI agent ready for the real world?

  2. We test the whole agent.

    Whole conversations that adapt as people do, across every goal you confirm. We hunt for the failures nobody wrote down, before a customer finds them.

  3. We are specialists.

    We study one thing: how AI agents fail. Every assessment draws on over 150 goals and growing, over a hundred techniques.

  4. We do the heavy lifting.

    Testing has always been slow and a drag on your team. We set it up, run it and report it.

Nothing installed, nothing to unwind. Your testing partner, release after release.

Jesse Lucas, Founder & CEO

“Teams either launch with risks they can’t see, or wait and fall behind.”

For five years, I put chatbots, conversational AI, and AI agents in front of customers in seven markets across Europe and Asia. I felt this problem on every release, so I built Mantia.

Jesse Lucas, Founder & CEO

Questions worth asking

How is this different from evals?

Evals are useful, but your team writes and maintains them, and they typically score single answers to the cases you thought of. Mantia is plug and play: we design the tests, play your customers and attackers in whole conversations that adapt as they go, and judge each one against the goals you confirmed.

Why can’t we do this ourselves?

Our platform is ready to go today, with specialist techniques and experience built in, so you don’t start from scratch. And testing your own agent means marking your own work. We have no stake in your build, so we look for the failures you haven’t thought of.

We have a very specific use case. Can you test it?

Yes. Our catalogue covers the general tests, from security and safety to bias. Everything else is bespoke: you define what ready looks like for your agent, and we build the goals around it.

How do you connect to our chatbot or AI agent?

Through its API. We need the endpoint, one example request, and a key you issue and can revoke at any time.

When do we use Mantia?

Before launch, then before any release that changes your agent’s model, capabilities, or prompts. We can also come in earlier, while your agent is still being built, and fit the assessment around where you are.

How long does an assessment take?

It depends on the scope. Once we have what we need and you’ve confirmed the goals, we can turn an assessment around in as little as 24 hours.

What models do you use?

A mix, from different providers. Once we’ve seen your set-up and know which models your agent runs on, we recommend the models for your assessment, and you agree them in writing. Every model we use is tested on our own benchmark, against conversations whose right answer we already know, so we can show it’s fit for the job.

Cars are crash-tested to find their weak points. AI agents need the same.

We push yours to its limits, so you know when it’s ready.