Fiddler AI vs Deepchecks
Both compete in Observability & Monitoring. Fiddler AI positions itself as “Enterprise AI observability, security, and governance control plane for models and agents”, while Deepchecksleads with “Open-source-led testing, evaluation and monitoring for ML models and LLM applications”. The table below compares what each publishes.
Where Fiddler AI pulls ahead
Publishes support for EU AI Act, NIST AI RMF, which Deepchecks does not. Regulated enterprises needing a single platform for ML, LLM, and agent observability with strong explainability and governance/audit capabilities.
Where Deepchecks pulls ahead
Publishes support for SOC 2, which Fiddler AI does not. Data science and ML engineering teams wanting code-first, open-source-backed validation of models and LLM apps, with an enterprise upgrade path for production monitoring.
Both map to GDPR, HIPAA, so framework coverage alone will not separate them — the decision usually comes down to who operates the tool and how it fits your existing stack.
| Positioning | Enterprise AI observability, security, and governance control plane for models and agents | Open-source-led testing, evaluation and monitoring for ML models and LLM applications |
|---|---|---|
| Category | Observability & Monitoring | Observability & Monitoring |
| Frameworks | EU AI Act, NIST AI RMF, GDPR, HIPAA | SOC 2, GDPR, HIPAA |
| 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 | 2021 |
| Headquarters | Palo Alto, California, USA | Tel Aviv, Israel |
| Ownership | Private, independent; venture-backed | Independent |
| 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. | $14M seed led by Alpha Wave Ventures |
| Pricing | Enterprise subscription; custom pricing via sales/demo (no public self-serve tiers) | Free open-source core; commercial enterprise LLM Evaluation platform (pricing not public) |
| Key capabilities |
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| Integrations | Amazon SageMaker, Google Cloud Vertex AI, NVIDIA NIM, NVIDIA NeMo Guardrails, Databricks, Datadog | OpenAI, Anthropic Claude, Amazon Bedrock, LangChain, CrewAI, NVIDIA, AWS SageMaker, Datadog |
| Notable customers | Brex, BigaBid | None published |
| Best for | Regulated enterprises needing a single platform for ML, LLM, and agent observability with strong explainability and governance/audit capabilities. | Data science and ML engineering teams wanting code-first, open-source-backed validation of models and LLM apps, with an enterprise upgrade path for production monitoring. |
| 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. | Oriented toward technical ML/engineering users rather than non-technical GRC or legal teams, and its regulatory-framework mapping is lighter than dedicated AI-governance and compliance platforms. |
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 Deepchecks if data science and ML engineering teams wanting code-first, open-source-backed validation of models and LLM apps, with an enterprise upgrade path for production monitoring.
Neither is a substitute for a governance program. Whichever you pick, you still need people who can define the policies the tool enforces.
AI Governance Tool Selection Kit
A vendor-comparison worksheet plus EU AI Act, NIST AI RMF and ISO/IEC 42001 requirement checklists — so you can shortlist tools against the obligations that actually apply to you.
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