Fiddler AI vs Evidently AI
Both compete in Observability & Monitoring. Fiddler AI positions itself as “Enterprise AI observability, security, and governance control plane for models and agents”, while Evidently AIleads with “Open-source and cloud observability for evaluating, testing, and monitoring ML and LLM systems”. The table below compares what each publishes.
Where Fiddler AI pulls ahead
Publishes support for EU AI Act, NIST AI RMF, GDPR, HIPAA, which Evidently AI does not. Regulated enterprises needing a single platform for ML, LLM, and agent observability with strong explainability and governance/audit capabilities.
Where Evidently AI pulls ahead
Data science and MLOps teams wanting developer-first, code-native ML/LLM evaluation and monitoring with an open-source foundation
| Positioning | Enterprise AI observability, security, and governance control plane for models and agents | Open-source and cloud observability for evaluating, testing, and monitoring ML and LLM systems |
|---|---|---|
| Category | Observability & Monitoring | Observability & Monitoring |
| Frameworks | EU AI Act, NIST AI RMF, GDPR, HIPAA | None published |
| Deployment | SaaS, Cloud, On-prem, API | Open-source, SaaS, Cloud, On-prem, API |
| Built for | GRC, Compliance, Risk, Data Science / ML, Security | Data Science / ML |
| Founded | 2018 | 2020 |
| Headquarters | Palo Alto, California, USA | San Francisco, California, USA |
| Ownership | Private, independent; venture-backed | Private, independent; venture-backed (Y Combinator alum) |
| Funding | Approximately $100M total as of 2026; $30M Series C led by RPS Ventures (Jan 2026), following a $32M Series B (2021). Investors include Insight Partners, Lightspeed, Lux Capital, and Capgemini Ventures. | $15M Series A (Dec 2024, led by DN Capital, with Clear Ventures, Fellows Fund, Framework Ventures, Stephens); Y Combinator-backed |
| Pricing | Enterprise subscription; custom pricing via sales/demo (no public self-serve tiers) | Free open-source core (Apache 2.0); commercial Cloud and Enterprise tiers with undisclosed/contact-sales pricing |
| Key capabilities |
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| Integrations | Amazon SageMaker, Google Cloud Vertex AI, NVIDIA NIM, NVIDIA NeMo Guardrails, Databricks, Datadog | Python, GitHub, Databricks, MLflow, Airflow, Grafana |
| Notable customers | Brex, BigaBid | DeepL, Wise, Flo Health, PlushCare, Realtor.com, Plaid, Databricks |
| Best for | Regulated enterprises needing a single platform for ML, LLM, and agent observability with strong explainability and governance/audit capabilities. | Data science and MLOps teams wanting developer-first, code-native ML/LLM evaluation and monitoring with an open-source foundation |
| Limitations | Enterprise-focused with custom pricing and no transparent public tiers; the breadth across ML, LLM, and agents can mean a steeper setup and learning curve for smaller teams. | Positioned as an evaluation/observability toolkit rather than a full regulatory-compliance or GRC platform; no explicit mapping to named governance frameworks; commercial pricing is not public; governance features are monitoring-oriented rather than policy/attestation-oriented |
Which should you shortlist?
Choose Fiddler AI if regulated enterprises needing a single platform for ML, LLM, and agent observability with strong explainability and governance/audit capabilities.
Choose Evidently AI if data science and MLOps teams wanting developer-first, code-native ML/LLM evaluation and monitoring with an open-source foundation
Neither is a substitute for a governance program. Whichever you pick, you still need people who can define the policies the tool enforces.
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