Red teaming and adversarial testing providers
56 published entries state red teaming and adversarial testing on their AI testing pages. Between them they name 9 AI product types.
This service covers red teaming of models and applications: jailbreaks and attempts to elicit harmful output.
red teaming: Deliberate attempts to make a system produce harmful or unintended output.Showing 56 of 56. Default order: coverage score, then name. How the score works.
| Rank | Company type | AI products (as stated) | Services | Verified | |||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | DeviQA | Pure-play QA company | Poland, Warsaw | LLM applicationsAI agentsRecommender and ranking systemsPredictive ML modelsComputer visionVoice AI | 8 | 2010 | 16 | 2026-11-09 | |
| 2 | Abstracta | Pure-play QA company | United States, Jacksonville | LLM applicationsAI agentsPredictive ML models | 10 | 2008 | 15 | 2026-11-09 | |
| 2 | ImpactQA | Pure-play QA company | United States | LLM applicationsAI agentsComputer visionVoice AIRecommender and ranking systems | 9 | 15 | 2026-11-09 | ||
| 4 | BetterQA | Pure-play QA company | Romania, Cluj-Napoca | LLM applicationsAI agentsVoice AI | 9 | 2018 | 14 | 2026-11-09 | |
| 4 | QATestLab | Pure-play QA company | Cyprus | LLM applicationsAI agentsPredictive ML models | 10 | 14 | 2026-11-09 | ||
| 4 | TestingXperts | Pure-play QA company | United States | LLM applicationsAI agentsVoice AI | 10 | 14 | 2026-11-09 | ||
| 4 | Testlio | Crowdtesting platform | United States, Austin | LLM applicationsAI agentsPredictive ML modelsRecommender and ranking systems | 8 | 2012 | 14 | 2026-11-09 | |
| 4 | Testriq | Pure-play QA company | India, Mira-Bhayandar | LLM applicationsAI agentsPredictive ML models | 9 | 2010 | 14 | 2026-11-09 | |
| 10 | ITRex Group | IT services firm with a QA practice | United States, Sacramento | LLM applicationsAI agentsComputer visionPredictive ML modelsRecommender and ranking systems | 6 | 2009 | 13 | 2026-11-09 | |
| 11 | Fulminous Software | IT services firm with a QA practice | India, Jaipur | Voice AIAI agentsAutonomous and embedded AI | 7 | 2019 | 12 | 2026-11-09 | |
| 11 | QualityAI (formerly Qualitest) | Pure-play QA company | United States, Santa Clara | LLM applicationsAI agentsPredictive ML modelsRecommender and ranking systems | 7 | 12 | 2026-11-09 | ||
| 11 | SunTec India | Data and evaluation vendor | India, New Delhi | LLM applicationsDocument AIPredictive ML models | 7 | 1999 | 12 | 2026-11-09 | |
| 14 | Lionbridge | Data and evaluation vendor | United States, Waltham | LLM applicationsVoice AIComputer visionRecommender and ranking systems | 5 | 1996 | 11 | 2026-11-09 | |
| 14 | QA Madness | Pure-play QA company | Poland, Warsaw | LLM applicationsAI agentsRecommender and ranking systems | 7 | 11 | 2026-11-09 | ||
| 14 | QAwerk | Pure-play QA company | Ukraine, Kyiv | LLM applicationsAI agents | 7 | 2015 | 11 | 2026-11-09 | |
| 14 | Testrig Technologies | Pure-play QA company | United States, Dallas | Predictive ML models | 8 | 2015 | 11 | 2026-11-09 | |
| 18 | Indium Software | IT services firm with a QA practice | United States, Cupertino | AI agentsLLM applicationsRecommender and ranking systems | 6 | 10 | 2026-11-09 | ||
| 18 | Kualitatem | Pure-play QA company | United States, New York | Predictive ML models | 7 | 2010 | 10 | 2026-11-09 | |
| 18 | Shaip | Data and evaluation vendor | United States, New York | LLM applicationsAI agentsVoice AI | 6 | 10 | 2026-11-09 | ||
| 18 | Sparkout Tech | IT services firm with a QA practice | India, Coimbatore | Predictive ML models | 7 | 2017 | 10 | 2026-11-09 | |
| 23 | AppSierra | IT services firm with a QA practice | India, Noida | LLM applicationsAI agentsPredictive ML models | 5 | 9 | 2026-11-09 | ||
| 23 | Chetu | IT services firm with a QA practice | United States, Sunrise | Predictive ML models | 6 | 2000 | 9 | 2026-11-09 | |
| 23 | QASource | Pure-play QA company | United States, Pleasanton | LLM applicationsAI agents | 5 | 2002 | 9 | 2026-11-09 | |
| 29 | AIDX Tech | AI assurance and audit specialist | Singapore, Singapore | LLM applicationsAI agentsVoice AIComputer vision | 4 | 8 | 2026-11-09 | ||
| 29 | Applause | Crowdtesting platform | United States | LLM applicationsAI agentsVoice AI | 4 | 8 | 2026-11-09 | ||
| 34 | Centific | Data and evaluation vendor | United States, Redmond | AI agentsComputer vision | 4 | 7 | 2026-11-09 | ||
| 34 | Macgence | Data and evaluation vendor | India, Noida | Predictive ML models | 5 | 7 | 2026-11-09 | ||
| 34 | Qualitrix | Pure-play QA company | India, Bengaluru | Predictive ML models | 5 | 7 | 2026-11-09 | ||
| 40 | Fairly AI | AI assurance and audit specialist | Canada, Kitchener | LLM applicationsPredictive ML modelsAI agents | 3 | 6 | 2026-11-09 | ||
| 40 | Innodata | Data and evaluation vendor | United States, Ridgefield Park | LLM applicationsGenerative media | 4 | 6 | 2026-11-09 | ||
| 40 | Kainos | IT services firm with a QA practice | United Kingdom, Belfast | LLM applications | 3 | 1001-5000 | 6 | 2026-11-09 | |
| 40 | Qualysec | Security firm with AI testing | India, Bhubaneswar | LLM applicationsAI agents | 3 | 6 | 2026-11-09 | ||
| 40 | ScienceSoft | IT services firm with a QA practice | United States, McKinney | LLM applicationsAI agents | 2 | 1989 | 6 | 2026-11-09 | |
| 40 | Software Secured | Security firm with AI testing | Canada, Ottawa | LLM applicationsAI agents | 3 | 6 | 2026-11-09 | ||
| 40 | TaskUs | Data and evaluation vendor | United States, New Braunfels | AI agentsAutonomous and embedded AI | 3 | 5001+ | 6 | 2026-11-09 | |
| 50 | Artifice Security | Security firm with AI testing | United States, Denver | LLM applicationsAI agents | 2 | 2019 | 5 | 2026-11-09 | |
| 50 | Bishop Fox | Security firm with AI testing | United States, Tempe | LLM applicationsAI agents | 2 | 5 | 2026-11-09 | ||
| 50 | Bridewell | Security firm with AI testing | United Kingdom, Reading | LLM applications | 2 | 2013 | 5 | 2026-11-09 | |
| 50 | DeepStrike | Security firm with AI testing | United States | LLM applications | 2 | 2016 | 5 | 2026-11-09 | |
| 50 | HackerOne | Security firm with AI testing | United States, San Francisco | LLM applicationsAI agents | 3 | 5 | 2026-11-09 | ||
| 50 | Knovel Engineering | IT services firm with a QA practice | Singapore, Singapore | LLM applications | 4 | 5 | 2026-11-09 | ||
| 50 | Praetorian | Security firm with AI testing | United States, Austin | LLM applicationsAI agents | 3 | 5 | 2026-11-09 | ||
| 50 | Redbot Security | Security firm with AI testing | United States, Denver | LLM applicationsAI agents | 2 | 5 | 2026-11-09 | ||
| 61 | 7ASecurity | Security firm with AI testing | Ireland, Dublin | LLM applicationsAI agents | 2 | 4 | 2026-11-09 | ||
| 61 | Accenture | IT services firm with a QA practice | Ireland, Dublin | AI agents | 2 | 5001+ | 4 | 2026-11-09 | |
| 61 | IBM | IT services firm with a QA practice | United States, Armonk | LLM applications | 2 | 1911 | 4 | 2026-11-09 | |
| 61 | Nexigen | IT services firm with a QA practice | United States, Newport | LLM applicationsAI agents | 2 | 4 | 2026-11-09 | ||
| 61 | Toloka | Data and evaluation vendor | Netherlands | LLM applicationsAI agents | 2 | 4 | 2026-11-09 | ||
| 61 | Vaadata | Security firm with AI testing | France, Lyon | LLM applicationsAI agents | 2 | 4 | 2026-11-09 | ||
| 61 | Welo Data | Data and evaluation vendor | United States | LLM applications | 3 | 4 | 2026-11-09 | ||
| 61 | WorkNest | United Kingdom, London | LLM applicationsAI agents | 2 | 4 | 2026-11-09 | |||
| 74 | Anvil Secure | Security firm with AI testing | United States, Seattle | LLM applications | 2 | 3 | 2026-11-09 | ||
| 74 | CrowdStrike | Security firm with AI testing | United States, Austin | LLM applications | 2 | 3 | 2026-11-09 | ||
| 74 | Dionach | Security firm with AI testing | United Kingdom, Oxford | LLM applications | 2 | 3 | 2026-11-09 | ||
| 74 | NetSPI | Security firm with AI testing | United States, Minneapolis | LLM applications | 2 | 3 | 2026-11-09 | ||
| 74 | SISA | Security firm with AI testing | India, Bengaluru | AI agents | 1 | 3 | 2026-11-09 |
Product types covered by vendors stating this service
Count of entries on this page that state each product type.
| Product type | Red teaming and adversarial testing |
|---|---|
| LLM applications | 45 |
| AI agents | 37 |
| Voice AI | 9 |
| Computer vision | 6 |
| Predictive ML models | 16 |
| Recommender and ranking systems | 8 |
| Generative media | 1 |
| Document AI | 1 |
| Autonomous and embedded AI | 2 |
Scope and standards referenced
Jailbreaks, harmful output elicitation, OWASP Top 10 for LLM Applications, MITRE ATLAS.
- OWASP Top 10 for LLM Applications: list of the main security risks in LLM applications
- MITRE ATLAS: knowledge base of adversary tactics against AI systems
The directory lists which vendors state this service. It does not test whether a vendor applies these standards.
Related
Product types
Other services
Guides
Questions
What is AI red teaming?
AI red teaming is a deliberate attempt to make a model or AI application produce harmful, unsafe or unintended output. Testers use jailbreaks, manipulative prompts and misuse scenarios. 56 published entries state red teaming and adversarial testing.
What is the purpose of red teaming an AI system?
Red teaming finds failure modes before users or attackers do, so they can be fixed or guarded. The findings also feed regression tests and the risk documentation that regulation and internal policy ask for.
How does AI red teaming differ from AI penetration testing?
Red teaming targets the model's behaviour, such as harmful content and policy bypass. Penetration testing targets the system around the model: tools, data access, integrations and prompt injection that triggers actions. 33 published entries state both.
What risks does an AI red team assessment look for?
Typical risks are jailbreaks, harmful or illegal content, leakage of system prompts or private data, biased output, misinformation and unsafe actions by agents. Reports often map findings to the OWASP Top 10 for LLM Applications or MITRE ATLAS.
Which AI systems should be red teamed: models, applications or agents?
All three, at different depths. Model red teaming tests behaviour; application red teaming adds the system prompt, retrieval and user interface; agent red teaming adds tools and permissions, where a successful attack can cause actions.
What is the difference between automated red teaming tools and human-led red teaming services?
Tools run large sets of known attack prompts quickly and repeatably. Human-led services design new attacks for the specific product and judge subtle failures. This directory lists services; tool-only vendors are on the not-published page.