Helicone
AI gateway + observability platform
- • Gateway proxy with caching
- • Request-level analytics and logging
- • Usage cost tracking
- • Rate limiting and access controls
helicone vs braintrust
Helicone vs Braintrust
Compare Helicone gateway observability with Braintrust evaluation-first monitoring for AI application workflows.
Last reviewed: 2026-03-03
Braintrust
LLM evaluation + experiment platform
- • Evaluation and scoring framework
- • Experiment tracking and comparison
- • Dataset management
- • Prompt playground and iteration
Feature and workflow comparison
| Capability | Helicone | Braintrust |
|---|---|---|
| Primary focus | AI gateway + observability | LLM evaluation + experiments |
| Request proxy / gateway | Core capability | Not a primary focus |
| Evaluation and scoring | Limited | Core capability |
| Experiment tracking | Basic | Deep comparison and iteration |
| Cost tracking | Built-in usage costs | Basic cost visibility |
| Dataset management | Request logs | Structured dataset workflows |
| Starting price | Free tier available | $249/mo (Pro) |
Where AI Cost Board fits
Helicone excels at gateway-level observability while Braintrust focuses on evaluation workflows. AI Cost Board fills the cost governance gap that neither tool prioritizes — budget alerts, project-level spend attribution, anomaly detection, and finance-aligned reporting.
FAQ
Should I choose Helicone or Braintrust?
They solve different problems. Helicone is for gateway observability and request monitoring. Braintrust is for evaluation and experiment tracking. Many teams use both for different workflow stages.
Which is more affordable?
Helicone offers a free tier for basic usage. Braintrust Pro starts at $249/month. AI Cost Board starts at $9.99/month for dedicated cost governance.
Can AI Cost Board replace either tool?
AI Cost Board is not a replacement for gateway or evaluation workflows. It is a complementary tool for cost governance, budget controls, and spend attribution that works alongside observability and evaluation tools.
What is the best stack for production AI?
A common production stack includes: (1) a gateway or proxy for routing, (2) an observability or evaluation tool for quality, and (3) a cost governance tool like AI Cost Board for financial controls.