AI observability and evaluation platform for ML models, LLM apps, and agents
Aporia
AI control platform combining ML observability with real-time guardrails for GenAI
What Aporia does
Aporia is an AI control and observability platform that helps organizations monitor, secure, and govern machine learning models and generative AI applications in production. The company built its reputation on ML observability, giving data science and ML teams tooling to detect drift, model degradation, bias, and data-integrity problems at scale, and later added a Guardrails product that intercepts LLM inputs and outputs in real time to block hallucinations, prompt injections, PII and data leakage, and inappropriate content. A distinctive technical element is its Direct Data Connectors approach, which lets Aporia analyze training and inference data without duplicating or sampling it, so sensitive data can stay inside the customer's environment—an important property for regulated buyers. Aporia holds SOC 2 Type II certification and supports GDPR and HIPAA-aligned deployments, including an EU data region. In December 2024 Aporia was acquired by observability company Coralogix (a deal reported around $50M), and as of mid-2026 its technology is being integrated into Coralogix's broader AI observability offering, with Aporia's founders helping lead a dedicated AI research effort. It targets ML, data science, platform, and security teams in regulated industries.
Key capabilities
- ML model monitoring (drift, degradation, bias, data integrity)
- 20+ pre-configured GenAI guardrails
- Real-time hallucination and prompt-injection mitigation
- PII/data-leakage detection
- Direct Data Connectors (no data duplication)
- Customizable monitoring policies and alerts
- Explainability and root-cause analysis
- Customizable dashboards
Best for
ML and platform teams in regulated industries needing production ML monitoring plus real-time GenAI guardrails, now within the Coralogix observability ecosystem
Limitations
Now part of Coralogix, so the standalone product roadmap and branding are being absorbed into a larger platform, which may affect independent adoption; public list of named customers is limited, and buyers should confirm current packaging post-acquisition.
Framework coverage
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