toolspool

Compare tools

Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Google Antigravity logo
Google Antigravity
✓ verifiedFree

Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.

22M visits/mo18K saves
HEROZ logo
HEROZ
✓ verifiedPaid

A Japanese AI firm that grew from shogi-AI research into industry ML solutions and a generative-AI platform, HEROZ ASK.

1.9M 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
27K visits/mo
LangWatch logo
LangWatch
✓ verifiedFreemium

Platform to test, evaluate and observe LLM and voice AI agents, with prompt management and red-teaming for production.

23K visits/mo6.4K saves
Pricing

No public pricing

No public pricing

No public pricing

No public pricing

Developer: €0 (50k events/mo)
Growth: €29/core-seat/mo (+ €5 per 100k events)
Core features
  • Agent-first IDE experience
  • Autonomous planning and code execution
  • Integrated editor, terminal and browser control
  • Powered by Google's Gemini models
  • High-level developer supervision
  • Deep-learning and machine-learning core technology
  • HEROZ ASK generative-AI platform
  • BtoB and BtoC AI solutions
  • BLOOMWORKS product
  • Industry AI deployment case studies
  • 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
  • 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
  • Scenario-based agent testing
  • LLM evaluation and quality scoring
  • Observability for cost and latency
  • Prompt management with GitHub sync
  • Voice AI simulation
  • LLM red-teaming and governance
Use cases
  • Building apps with AI agents
  • Automating multi-step coding tasks
  • Prototyping and iterating on software
  • Assisting developers on complex work
  • Deploying generative AI in enterprises
  • Applying ML to industry-specific problems
  • AI-driven business transformation (DX)
  • 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
  • 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.
  • Catch agent issues before production
  • Evaluate and monitor LLM quality
  • Test voice AI agents at scale
Visit
More in LLM Ops Observability