Data & AI Auditing
AI doesn't crash — it degrades quietly.
A data pipeline slowly shifts. A model's accuracy slips after a retrain. An LLM application starts returning confident, fluent, completely wrong answers after a prompt tweak. Most teams find out the same way: a customer complaint, a regulator's question, or a metric that drifted three months ago. By then, the cost is already paid. We offer independent evaluation of your data, models, and LLM applications — so you can ship with evidence instead of hope.
Two Audits, One Independent View of Your AI Stack
For the data pipelines and classical ML models powering your analytics and decisions.
- Data drift — Is production data still what your models were trained on?
- Overfitting & generalization — Will the model hold up on unseen inputs?
- Feature importance — What is the model actually basing decisions on?
- Decision explainability — Can you show a regulator or auditor why a specific outcome happened?
For the generative AI features you've already shipped — or are about to.
Testing an LLM-powered product isn't like testing traditional software. The same prompt can work Monday and fail Wednesday after a model update. There's no stack trace when it goes wrong.
- Component isolation — Are individual LLM calls and retrieval steps reliable on their own?
- Pipeline integration — Is the model using retrieved context, or answering from memory?
- Evaluation rubrics — Scoring for faithfulness, relevance, and groundedness.
- Regression suite — A golden dataset so every model or prompt change is measured, not guessed.
- Red teaming — Prompt injection, jailbreaks, scope creep, data leakage.
- Production observability — Continuous evaluation on live traffic with drift and cost monitoring.
Related Work
View all case studies →Bot Detection via Behavioral Fingerprinting
Insurance / Financial Services
Auditing raw application event data uncovered two distinct bot timing profiles and identified exactly which form fields were being targeted — giving the dev team concrete patterns to block.
Agent Performance Behavioral Analytics
Insurance / Financial Services
Deep behavioral analysis revealed that agents with the highest quote volume were not the top sales converters — a finding that changed how the business hired and trained.
Who we work with
We partner with teams in regulated, data-sensitive, and customer-facing industries where getting AI wrong has a real cost — Financial Services, Healthcare, Insurance, and Computer Hardware.
Whether you're preparing for a regulator, chasing a silent quality drop, or want a second set of eyes before you ship — a Saigon A.I. audit gives you the evidence to move forward with confidence.
Book an audit conversation