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27K visits/mo
liteLLM logo
liteLLM
✓ verifiedFreemium

Open-source AI gateway giving dev teams unified access, fallbacks and spend tracking across 100+ LLMs.

703K visits/mo
Fiddler AI logo
Fiddler AI
✓ verifiedFreemium

Enterprise AI observability and security platform to monitor, evaluate, and govern agentic and ML systems with guardrails.

51K visits/mo
Weights & Biases logo
Weights & Biases
✓ verifiedFreemium

Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.

2.5M visits/mo
Helicone logo
Helicone
✓ verifiedFreemium

LLM observability platform and AI gateway that lets teams route, log, debug and analyze their model requests.

100K visits/mo
Pricing

No public pricing

Open Source: $0 (self-hosted, 100+ providers)

Free trial available

Free: $0 (real-time guardrails)
Developer: $0.002 per trace

No public pricing

Hobby: Free (10,000 requests/mo)
Pro: $79/mo (unlimited seats)
Team: $799/mo (SOC-2 & HIPAA)

Free trial available

Core features
  • Open-Source AI Gateway
  • Multi-LLM Management & Cost Optimization
  • Efficient and Secure LLMs Invocation
  • Unified API Signature for LLMs
  • Load Balancer for seamless switching between LLMs
  • Fine-Grained Traffic Control for LLMs
  • LLM Quota Management
  • Real-time LLM Traffic Monitoring
  • Caching Strategies for AI in Production
  • Flexible Prompt Management
  • Unified access to 100+ LLMs in OpenAI format
  • Cost/spend tracking per key, user and team
  • Budgets and rate limiting
  • Automatic provider fallbacks and retries
  • Virtual keys and team management
  • Logging and observability integrations
  • End-to-end agentic and ML observability
  • Real-time guardrails (hallucination, PII, jailbreak)
  • Continuous evaluations and custom judges
  • Root-cause analysis and decision lineage
  • AI governance, risk, and compliance controls
  • Flexible SaaS, VPC, or on-prem deployment
  • Experiment tracking and visualization for ML training runs
  • Model and artifact versioning and management
  • Hyperparameter optimization tooling
  • Collaborative dashboards and reports for ML teams
  • LLM application tracing and evaluation tooling
  • Request logging and LLM observability
  • AI gateway with routing and automatic fallbacks
  • Caching and rate limiting
  • Session, user and custom-property analytics
  • Prompts, playground and datasets for testing
  • Integrations with OpenAI, Anthropic, Azure and more
Use cases
  • Building API portals for secure sharing of internal APIs with partners.
  • Tracking API usage and driving API monetization.
  • Managing and securing API access in compliance with enterprise policies.
  • Connecting to multiple AI large models simultaneously.
  • Optimizing LLM costs and improving efficiency.
  • Protecting against LLM attacks and data leaks.
  • Giving developers governed access to many LLMs
  • Attributing and controlling LLM spend
  • Keeping apps running during provider outages
  • Monitoring production AI agents
  • Enforcing safety guardrails on LLM apps
  • Evaluating and debugging model behavior
  • Governance and compliance for enterprise AI
  • ML engineers tracking and comparing training experiments
  • Research teams versioning datasets and model checkpoints
  • Teams building and evaluating LLM-powered applications
  • Organizations collaborating on machine learning projects
  • Monitoring and debugging LLM apps
  • Analyzing model usage and cost
  • Caching responses to cut spend
  • Managing prompts and testing datasets
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