Your AI’s been working overtime. But have you actually tested what it’s doing?
AI isn’t magic — it’s math, models, and (a lot of) uncertainty. We make sure yours doesn’t just “work”… but works well, reliably, and safely.
Garbage in? Better not — get garbage out.
We test:
• Valid vs invalid data
• Edge cases (zeroes, extremes, weird Unicode stuff)
• Injection attempts (prompt injection, SQL, code)
You wouldn’t release a calculator that’s right 60% of the time — so why let your AI off the hook?
We:
• Compare predicted vs expected results
• Measure accuracy, precision, recall, or BLEU/F1 scores, depending on model type
• Benchmark model performance across test setsWe don’t want 100% perfection.
But we do want 98%+ confidence that your AI won’t embarrass you.
Does your model know when it does something wrong?
We test:
• How it handles low-confidence outputs
• Whether it flags uncertain cases instead of bluffing
• If fallback logic is in place (especially for high-risk decisions)
No one likes an overconfident AI.
We verify your AI plays nice with:
• Frontends (apps, web, dashboards)
• Backends (databases, APIs)
• Orchestration tools (pipelines, workflows)
An AI that gives the right answer to the wrong system is still broken.
We check for:
• Data leaks
• Confidential information exposure
• Prompt injection risks
• Compliance issues (GDPR, HIPAA)
AI can “accidentally” reveal things. We make sure it doesn’t.
We simulate bad actors, confused users, and messy real-world input.
Why?
Because the real world is chaotic, and your AI needs to be tougher than it looks.
Will your AI break under pressure?
We measure:
• Response times under normal and peak loads
• System resource usage
• Graceful fallback under strain
If it can’t handle traffic, it’s not ready for production.
AI thinks a scam is “probably fine”
Chatbot prescribes cheese
“Hires” the most biased answer
Cites Harry Potter in court
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