Surface multilingual safety gaps and language-specific risks before your users do.
Into23 runs structured adversarial testing across APAC and global languages using native-speaker testers with deep cultural fluency. We specialise in the multilingual dimension of AI safety testing — the gap that English-only programs consistently miss.
Pricing is scoped individually based on language coverage, prompt volume, attack taxonomy, and reporting requirements. Contact us for a custom quote.
We craft adversarial prompts that exploit linguistic nuances, regional slang, dialect variation, and culturally specific framings — attack vectors that automated translation and English-only testing cannot replicate.
Testing runs across priority APAC languages so you can see whether safety controls hold outside English and across local writing styles, including low-resource languages where safety training data is thinner.
Native-speaking testers identify harmful phrasing, local sensitivities, religious and political content risks, and market-specific failure modes that generic testing teams often miss.
Findings are grouped by risk, reproducibility, and likely business impact so product, safety, and compliance teams can act quickly. Each issue is documented with prompts, outputs, and severity notes.
We present results in a format that helps product and safety teams prioritise what to fix before launch. Findings include practical notes on reproducibility and suggested mitigation priorities.
Structured testing reports and documented methodology can form one component of a broader compliance dossier, supporting frameworks such as the EU AI Act, NIST AI RMF, and ISO 42001.
We align on model type, user journeys, languages, safety policies, and the failure modes that matter commercially and operationally.
Our team executes adversarial prompt sets across agreed languages, markets, and scenario families.
Each issue is documented with prompts, outputs, severity, and practical notes on reproducibility.
We present the results in a format product, safety, and leadership teams can use to decide what to fix before launch.
Into23 positions AI red teaming for scoped programs where multilingual testing, native-speaker reviewers, and executive-ready reporting are required. Current delivery is best suited to strategic engagements and partnership-led projects.
Standard testing typically runs in English and misses language-specific safety gaps, culturally sensitive failure modes, and risks that only appear in other languages. Native-speaker testers find issues that translated test sets cannot — including code-switching attacks that succeed significantly more often than English-only attacks.
Enterprise AI teams preparing for product launches, regulated deployments, or customer assurance reviews. Also AI companies that need to demonstrate multilingual safety testing across APAC markets to enterprise buyers.
Into23 specialises in the multilingual and cultural dimension of adversarial testing. We do not provide prompt injection or agent attacks (which require developer-level technical infrastructure), multimodal red teaming, automated red tooling, or end-to-end compliance consulting. For those needs we can recommend appropriate specialist partners.
Get a custom quote for your AI red teaming project. Our team typically responds within 24 hours.