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Revefi vs. Grafana

One platform for AI FinOps, AI Observability, Data FinOps and Data Observability

Revefi is a unified, agentic platform that cuts LLM cost, agent cost, and cloud data platform costs, keeps AI and data pipelines observable, and fixes issues autonomously.

Learn how Revefi excels against Grafana.

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Revefi vs Grafana comparison

How does Revefi compare?

Revefi is the only platform that unifies full-lifecycle AI FinOps, AI and agent observability, AI gateway routing across every major model provider, and FinOps for data and data observability, all in one agentic system.

Capability
1.
Full-lifecycle AI FinOps
2.
LLM observability
3.
Agent observability
4.
AI governance (hallucination & drift)
5.
AI budgeting
6.
Autonomous remediation
Revefi
✅
Automated (cost to the cent, per request)
✅
Automated
✅
Automated
⚠️
Partial
✅
Forecasted, tracked & enforced
✅
Autonomous, human-in-the-loop
Grafana
⚠️
Partial (real-time cost tracking and token analytics, no budgeting)
✅
Yes
✅
Yes
✅
Yes (hallucination, toxicity, bias evals)
❌
No
❌
No
Capability
1.
AI gateway (unified, policy-controlled access)
2.
Model routing & failover
3.
Frontier & hyperscaler model support
4.
Instrumentation required
Revefi
✅
Private preview
✅
Yes
✅
OpenAI, Anthropic, Google, Amazon Bedrock, Microsoft Azure OpenAI, Meta, Mistral
✅
API, SDK or OTel
Grafana
❌
No (integrates with third-party gateways such as LiteLLM, OpenRouter)
❌
No
✅
OpenAI, Anthropic, Google Gemini, Amazon Bedrock, Cohere
✅
OpenTelemetry, thin SDKs (auto-instrumentation for LangChain, LangGraph, OpenAI Agents)
Capability
1.
Data platform observability
2.
DataOps
3.
Data quality
4.
Data platforms supported
Revefi
✅
Automated
✅
Automated
✅
Automated
✅
Snowflake, Databricks, BigQuery, Redshift, Postgres, Trino
Grafana
❌
No (infra/account metrics only, no schema drift, freshness or volume-anomaly detection)
❌
No
❌
No
⚠️
Snowflake (infra metrics only)
Table note: Capability ratings reflect Revefi's product and Grafana's publicly available marketing and documentation as of September 2026.
Case Study

Fortune 200 Enterprise, Maximizing ROI of AI

A Fortune 200 enterprise spending nine figures annually on AI, using Revefi's automated monitoring, alerting, recommendations and one-click actions to turn that spend into measurable savings.

8x
Increase in AI spend in less than 4 months
25K+
Users and increasing
200M+
Requests monthly and increasing
10K+
AI services and increasing
9-figure annual AI spend illustration showing rising cost bars for LLM providers7-figure savings identified illustration showing stacks of cashResults in 3 weeks illustration showing a calendar with a completed milestone

Additional resources

Blog

AI Cost Observability: Building a Cost-Controlled AI Practice with FinOps

eBOOK

Agentic AI for Autonomous Database Administration

Report

Revefi has been recognized as a 2025 Gartner Cool Vendor

Bring observability to your
AI agents and LLMs.

See Revefi's AI Agent find your token
waste in 5 minutes.

Discover how our customers

  • Got results in 5 minutes
  • Reduced cloud data cost by 30-70%
  • Increased operational efficiency by 10x

Agentic AI

Automatic warehouse optimization

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