Services | Reins AI

Custom Evaluation Suite

Targeted evaluation infrastructure tailored to your use case, success criteria, and implementation.

We triangulate across key metrics to ensure you know your application is working as intended.

Our methods work with the data you're already collecting. No manual annotation, no curated datasets, just signal extraction from real-world use.

Built to plug into your current tools and workflows. We support integrations with GCP, Azure, Databricks, Jupyter, Arize, and more.

Continuous, contextual monitoring designed to surface issues before they impact users or regulators.

We monitor your models for output changes, performance shifts, and suitability breakdowns, without needing access to ground truth.

We help you track model behavior across users, cohorts, and edge cases, revealing where performance diverges most.

Get concise updates that flag risk, summarize trends, and support fast technical or strategic decision-making.

Actionable strategies to improve AI performance through targeted changes, not just retraining.

We identify why your model is underperforming: pinpointing inputs, logic gaps, or usage patterns that lead to failure.

We simulate potential interventions (prompt tweaks, logic changes, or additional training) before you invest engineering time.

We provide a clear sequence of options, from quick wins to strategic overhauls, based on your system’s current behavior.

Targeted data expansion to improve model performance, coverage, and robustness without manual labeling.

We create synthetic examples tailored to your domain, edge cases, and performance gaps, grounded in real usage, not generic templates.

We surface underrepresented patterns and failure cases, ensuring your model sees more of what it needs to succeed.

Every augmented example is tied to specific evaluation goals, so you don’t just get more data, you get better insight.