Most teams ship a model and move on. Nobody runs a systematic audit. We analyze your predictions against ground truth and return a complete health report — health score, drift analysis, failure modes, and a ranked action plan — in under 24 hours.
Data drifts. Pipelines shift. Edge cases accumulate. Most teams don't find out their model is broken until a business metric tanks — never before.
"We discovered our fraud model was missing 30% of cases. It had been drifting for two months. Nobody had an alert."— ML Engineering Lead, Series B fintech
Every audit covers the dimensions that matter in production — not just accuracy.
Overall health score /100, top 3 findings, and the single most important action to take this week.
Missing values, class imbalance, duplicate rows, and dataset size adequacy for reliable metric estimation.
Beyond accuracy: precision, recall, F1, AUC-ROC, average precision, and confusion matrix breakdown.
Temporal prediction drift (KS test), positive rate shifts, and distribution shape anomalies.
Subgroup performance gaps across categorical segments. F1 variance by group, regulatory risk flags.
Brier score, probability compression check, and global calibration bias analysis.
Feature-error correlations, false positive/negative breakdown, and systematic misclassification patterns.
Near-duplicate features, zero-variance columns, high-skew distributions, and redundancy detection.
Timestamp logging, probability exposure, monitoring gaps, and debugging data quality.
Every finding turns into a prioritized P0/P1/P2 action with effort estimate. Your team knows exactly what to fix next.
Export a CSV with y_true and y_pred columns. Add y_score for probability analysis, timestamp for drift detection, and any feature columns for deeper analysis.
Our engine runs 8 independent analyses across all sections. No source code needed. No infrastructure access required. Just predictions.
A structured JSON report (or premium PDF for paid tiers) with your health score, every finding, and a prioritized action plan ready to paste into your sprint board.
No retainer. No monthly subscription. Pay once per audit.
Money-back if we don't find 3 new improvements
A CSV file with at minimum two columns: y_true (ground truth) and y_pred (model predictions). No source code, no infrastructure access needed.
We sign an NDA before you send anything. Your data is used solely for the audit and deleted after delivery. Anonymize sensitive identifiers before sending.
Binary classification, multiclass, and regression models. Tabular data. Specialties: fraud detection, churn prediction, risk scoring, recommendation quality.
Yes. The full audit is available via REST API. See the API docs or try it interactively in the demo tool.
If the Full Audit doesn't surface at least 3 actionable improvements you didn't already know about, we refund you in full. No questions asked.
Yes. After the audit, we offer implementation sprints starting at $1,800 for 3 days of hands-on ML work. About 30% of audit clients take this option.
No sign-up, no credit card. Upload your CSV and get a real health score in seconds.
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