Your Production AI Is Failing in Ways You Can't See
We find the failure modes your team doesn't test for — hallucination, scope drift, prompt injection, silent model degradation — and deliver a severity-ranked findings report in 48 hours. Before your users find them for you.
SaaS Chatbot API · GPT-4o · 339 vectors run
Full HTML report · Payload + response evidence · Remediation guide
View real report →Services
What We Do
Two disciplines. Ten services. Complete quality coverage from your AI stack to your delivery pipeline.
AI Reliability
Reliability engineering for production AI systems
Six specialized engagements that close every quality, security, and observability gap in your AI stack — from pre-launch evals to compliance audits.
Know exactly where your AI stands before you ship.
- Evaluation suite definition document
- Baseline scorecard across all 6 quality dimensions
- PASS / PARTIAL / FAIL results per test case with evidence
Attack your AI before adversaries do.
- Full findings report: VULNERABLE / SUSPICIOUS / CLEAN per vector
- HTML export with payload + response evidence
- Severity matrix: CRITICAL / HIGH / MEDIUM / LOW
See exactly what your AI is doing in production.
- Langfuse instrumentation on your key LLM calls and agent steps
- Trace Analysis report: span timing, token usage, tool call paths, latency per layer
- Trace screenshots and exports as evidence
End-to-end testing for multi-agent orchestration.
- Agent graph documentation and orchestration map
- Tool use accuracy report per tool
- Handoff integrity analysis across agent boundaries
Compliance, audit trails, and policy enforcement for AI.
- Compliance gap analysis report
- Regulatory alignment checklist (HIPAA / GDPR / SOC 2 / EU AI Act)
- Audit trail architecture recommendations
Your CI/CD eval pipeline, built and handed to your team.
- Eval pipeline configured on your infrastructure
- CI/CD integration (GitHub Actions / GitLab CI / custom)
- Quality baseline with documented pass/fail thresholds
QA Engineering Practice
End-to-end quality coverage at every layer
Automation frameworks, structured testing, AI-accelerated QA, and CI/CD quality gates — everything your delivery pipeline needs to ship with confidence.
Automation frameworks built to scale with your team, not break under it.
- Test automation suite in Playwright / Cypress / Selenium
- API test layer covering critical REST endpoints
- CI/CD pipeline integration (GitHub Actions / GitLab CI)
AI in your QA loop — more coverage, same rigour, less manual effort.
- AI-generated test case suite mapped to your specs and requirements
- Coverage gap report with prioritised recommendations
- Defect triage process and AI tooling setup
Systematic coverage for what automated tests routinely miss.
- Test plan with scope, priorities, and coverage approach
- Test case suite across functional and edge case scenarios
- Full defect report with severity classification and evidence
Quality gates on every push — automated, enforced, non-negotiable.
- CI/CD quality gate configuration (GitHub Actions / GitLab CI)
- Automated test suite running and gating on every PR
- Coverage threshold enforcement with configurable thresholds
Client Outcomes
What Happens When You Test Before It Matters
The failure modes we test for — and the outcomes our methodology is built to deliver.
We found 4 critical vulnerabilities in a RAG-based clinical decision support system before it went live — including an indirect injection vector that would have allowed patient record manipulation. The client shipped clean, on schedule, with zero incidents in the first 90 days.
4
Critical findings caught pre-launch
48hr
Full assessment delivery
0
Production incidents post-launch
A payments AI was silently drifting on edge cases — compliance-adjacent queries were degrading week over week, invisible to the team. We caught a 12% performance regression before it reached customers, and the rollback was executed in 24 hours.
12%
Drift detected before customer impact
24hr
Rollback execution time
14 wks
Stable on baseline since
With an EU AI Act deadline approaching, the client had no systematic view of their compliance posture. Our 5-day gap analysis surfaced 8 compliance gaps and produced a prioritised remediation roadmap — they closed all critical gaps 4 weeks ahead of the deadline.
8
Compliance gaps identified
5 days
Full audit completion
4 wks
Ahead of regulatory deadline
How It Works
How Every Engagement Works
A structured four-step process — not ad hoc testing. Every engagement runs the same rigorous methodology, every time.
Scope
We review your AI stack, define the attack surface, and align on scope and success criteria. A 30-minute scoping call is all it takes to get started.
- Stack review
- Attack surface definition
- Scope agreement
- NDA signed before kick-off
Test
374 adversarial vectors fired across both layers — 90 AI-specific prompt injection vectors and 284 web-layer payloads — plus a 64-case quality eval baseline.
- AI layer — 90 injection vectors
- Web layer — 284 payloads
- Quality eval — 64 cases
- Severity classification per finding
Report
Every finding documented with the exact payload sent, response received, and a severity verdict. Delivered as a full HTML + PDF report within 48 hours.
- Payload + response evidence
- Severity matrix (CRITICAL to LOW)
- Prioritised remediation guide
- HTML + PDF — audit-ready
Verify
Your team remediates the findings. We re-run the full suite to confirm every issue is resolved — verification, not just discovery. Quarterly retests available after any model update.
- Remediation support
- Full retest after remediation
- Quarterly retests available
- Delta report vs. prior run
Client Results
In Their Words
“We test our own AI before anyone else's.”
FlyTraq is our own GPS-verified flyer distribution platform, powered by an AI copy generator. Before we validate our methodology on client systems, we run every test on ourselves — red-teaming FlyTraq's AI layer for prompt injection, hallucination, and scope drift. Building with the tools we sell means every edge case we find in FlyTraq gets fixed before it shows up in a client engagement.
Navid, Co-Founder, AxionTest
Dogfooding — FlyTraq AI Layer
“We wouldn't ship without it now.”
ReplyPulse sends AI-generated replies on behalf of our users — any quality issue is instantly visible to their contacts. Axiontest's eval baseline gave us a consistent quality benchmark across every release. We wouldn't ship without it now.
Founder, ReplyPulse
AI Auto Reply Bot
Free Scoping Call
Is Your Production AI System Reliable?
Book a free 30-minute scoping call. We'll review your stack, identify your highest-risk failure modes, and show you exactly what to fix first.