We test for you
AI Security Testing as a ServiceWe handle scoping, manual and automated security and quality tests with Dreamleap, human review and prioritised findings with fix recommendations, re-testing and governance/release considerations.
AI security testing for chatbots and AI agents.
Test. Understand. Scale responsibly.
We assess the security and answer quality of your chatbots and AI agents, for you or alongside your team. If needed, we help your teams build lasting security-testing and red-teaming capability.
01 Test
02 Validate
03 Govern
Fix & Re-Test
Three ways to build AI security testing.
We test with you
Red Teaming & SparringWith your AI, engineering, risk or security teams, we challenge architecture, agent capabilities, data access, tool permissions, guardrails and attack scenarios. Your team understands risks and practical improvements.
We enable your team
Security Testing EnablementWe support tool setup, threat modelling and your own test cases. Your team learns to identify prompt, RAG and agent risks, assess findings and embed fixes and re-testing in governance and releases.
What we check in practice.
Test cases are tailored to your system and the agreed scope.
AI Security / Red Teaming
- Prompt injection, jailbreaks and manipulated tool calls
- Data and PII leakage; access to APIs and internal sources
- RAG poisoning, context manipulation and debug bypasses
- Bias, toxic, harmful or disallowed content
- Unwanted competitor mentions and unsafe outputs
- Cost and resource abuse
Answer Quality / Quality Evaluation
- Answer relevance to the question
- Faithfulness to knowledge sources and context
- Hallucinations, factual errors and unsupported claims
From scope to fixes and re-testing.
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Scope
Agree the system, data access, tools and risks.
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Test
Challenge it manually and/or automatically; have experts validate findings.
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Fix
Harden guardrails, permissions and workflows together.
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Re-Test
Verify improvements and document residual risks and release decisions.
Concrete findings and internal capability when needed.
What you receive
- Prioritised findings and risk assessment
- Reproducible test cases and fix recommendations
- Re-testing and management summary
- Governance and release considerations
What your team can do afterwards
Depending on the enablement scope: configure tools, create threat models and test cases, assess answer quality and attack surfaces, apply defensive measures, prioritise findings and carry out fixes and re-testing.
We test systems we build and understand.
Our own agentic and GenAI development connects testing with hands-on implementation.
Our AI Advisory connects this with your business context, including Microsoft Copilot and Claude for Companies. For specific requests, we can draw on our cybersecurity expert network.
Key questions before your first test.
Which AI systems do you test?
GenAI applications, RAG pipelines and AI agents with tool-calling and retrieval layers, including platform copilots and custom LLM solutions.
Do you need access to production data?
We prefer production-like sandboxes or masked data. If production access is necessary, scope, rate limits and logging are agreed in advance.
How do you combine automated testing and sparring?
Dreamleap supports quality and security tests. We review findings with your team, assess risks and discuss improvements. Human review remains part of the process.
Can you help resolve the findings?
Yes. We support fixes and hardening with your team, then verify improvements through re-testing.
Can we start with one chatbot or agent?
Yes. Scoping establishes your system, data handling and goal: testing by VOICETECHHUB, collaborative sparring or building internal testing capability.
Talk to us
Tell us about your chatbot or agent. Together, we decide whether to test for you, work with your team or build your internal testing capability.