Deximes - Test your AI agents before your customers do!

Test your AI agents before customers do

We simulate your real customers & real-world interactions, secretly test your AI agents and uncover costly failures before they become customer complaints

AI agents` productivity isn’t translating into measurable and reliable business results?

Everyone expects AI agents to boost productivity — until reality kicks in.

Test your AI agents before your customers do. The problem isn’t output, it’s unpredictability: inconsistent responses, unclear behavior, and the downstream cost of confused users and negative customer reviews

50%

Misalignment vs KPI`s

Most untrained agents showed 30%–50% misalignment under real KPI pressure (A Benchmark for Evaluating Outcome-Driven Constraint Violations in Autonomous AI Agents, 2026)

80%

Risky behaviors from AI agents

The percentage of organizations say they have encountered risky behaviors from AI agents, including improper customers` data exposure (Autonomous AI agents Survey by McKinsey 2025)

10%

High misclassification rate

In customer support, more than 10% misclassification rate forces companies back to humans, reducing the expected savings from AI automation

Why is this happening?

On paper, your AI agents work.
In reality, they’re uncoordinated and unpredictable under pressure. Without proper stress-testing validation, monitoring and tune-up your AI agents become just expensive business experiments. Test your AI agents before customers do!

Do you test your AI agents behavior with your customers?

The problem isn’t productivity. It’s that no one knows how your AI agents behave with your customers when it actually matters. Instead of clarity, you’re dealing with unpredictable outputs and negative reviews

What started as automation is turning into operational overhead

Agents work in isolation, not as a cohesive system. Outputs are inconsistent and hard to trust. No clear visibility into what your agents are doing

On paper, your AI agents should work perfect

Edge cases, privacy issues, failures, and unpredictable behavior started creeping in. Now your team is constantly stepping in—fixing, retrying and supervising. Instead of replacing work, your agents created a new layer of it

How do we test your AI agents?

We are your mystery customers

We analyze your AI agents in 100% real life scenarios and situations to ensure they behave with your customers exactly as you expect it. Test your AI agents before customers do!

We test AI agents to avoid KPI cheating

AI agents can exploit KPIs — driving scores up while customer satisfaction declines. Our testing prioritizes behavioral metrics over vanity metrics to capture real customer impact

We simulate all kinds of “difficult” users

Modern AI agents are highly sensitive to changes in user behavior. Under impatient/erratic communication styles, agents` performance can drop by 32–46%

We use our proprietary aiStress-Matrix

Instead of running isolated experiments, we combine different stress factors and observe how your AI agents behave under compound pressure and how it affects your customers

We use human judgements only

In real stress conditions, human judgment remains the most reliable way to measure behavioral robustness. Our professional testers check realism, fidelity, consistency, and compositionality of your agents

Customer data privacy above all

Your consumers data should be processed and collected by AI agents properly. Avoid legal and reputational consequences — ensure consumer data stays within the European Economic Area or is securely safeguarded

By the way, just a few words about us. We are:

How do we tune up your AI agents after testing?

Your KPIs first

We push your agents beyond demo conditions and benchmarks to expose true production behavior. Through structured tune up, we ensure outputs remain consistent and predictable across variations and real-world business complexity

Proprietary approach

Our approach is designed to go far beyond static benchmarks. Rather than measuring performance in isolation, we stress systems in environments which replicate business reality to expose weaknesses that traditional evaluation methods often miss

Human validation only

AI agents performance is not only measured by automated metrics, but also tested in real human judgment under 100% realistic conditions. While automated testing can capture statistical reliability, human evaluators are essential for assessing quality in real-life scenarios

Adversarial defence

We don’t evaluate AI in safe conditions; we attack it with structured, evolving pressure designed to expose every weak point. From prompt injection to deceptive logic traps and multi-layered inputs, we simulate real-world attempts to distort, derail, and manipulate agent`s behavior

Supervised-tuning & human feedback

We don’t just evaluate—we correct, refine, and harden. Our expert reviewers provide precise tuning signals that directly reshape model behavior. The result is an AI system that doesn’t just perform—it stays consistent, controlled, and deployment-ready under real-world pressure

Privacy data safeguards

AI agents process personal data without limitation and user awareness. Users don’t realize what data is being stored or used beyond the response. The biggest issue is that LLMs policies are unclear, while GDPR expects strict, traceable, and purpose-bound data control — and bridging that gap is still hard for many systems

We can stress-test and precisely tune-up AI agents based on any LLM

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Stress-test AI your agents before they become support tickets

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May 26, 2026