Helicone shows you what you spent on OpenAI. Preto tells you what to do about it — ranked recommendations, dollar estimates per finding, and budget enforcement at the proxy level. Same one-line integration.
No credit card. No SDK. Works with your existing OpenAI code.
Helicone is a well-built, mature tool. If you need LLM observability, prompt management, and request logging, it genuinely delivers. The teams that look for alternatives have already solved observability — now they need to actually reduce the bill.
Helicone shows total spend and per-request costs. But with 40+ API call sites in your codebase, you still don't know which feature to fix first. The dashboard tells you the total — it doesn't rank the culprits.
Great dashboards. No ranked action list. You still need an engineer to dig through logs and figure out what to change — hours of analysis to produce a guess. Preto produces the ranked list automatically, with estimated dollar impact per item.
Helicone notifies you. It doesn't stop runaway spend. When a misconfigured retry loop hits GPT-4 at 2am, Helicone sends an alert after the damage is done. Preto can hard-block requests before they reach OpenAI.
Built for observability and LLM debugging. Excellent at showing you what happened and how much it cost. Great for teams focused on quality, evals, and prompt management.
Built for LLM cost reduction. Tells you exactly what to change, estimates the savings before you act, and enforces spend limits at the proxy level.
| Feature | Helicone | Preto.ai |
|---|---|---|
| Proxy-based integration | ✓ | ✓ |
| Cost tracking per request | ✓ | ✓ |
| Request logging + latency | ✓ | ✓ |
| Prompt management | ✓ | ✗ not our focus |
| AI recommendations | ✗ | ✓ |
| Dollar savings estimates per finding | ✗ | ✓ |
| Savings dashboard | ✗ | ✓ |
| Budget enforcement (hard-block) | ✗ | ✓ |
| Spend alerts | Partial | ✓ |
| Open source | ✓ | Soon |
Helicone gives you a complete picture of your LLM traffic. Every request logged with cost, model, latency, and prompt. You can filter, search, and replay. For teams debugging LLM quality or managing prompts across environments, this is genuinely the right tool. The data is all there — it's just not analyzed for you.
Preto takes the same raw request data and runs it through five AI analysis rules to surface your highest-impact opportunities. Each finding comes with a dollar estimate — a projected monthly savings based on your actual traffic. You get a ranked to-do list, not a dashboard to interpret.
Helicone can show you this usage data. Preto surfaces the finding automatically, estimates the savings, and tracks when you implement it.
If you already use Helicone, you know the pattern — you changed base_url once to adopt it. Moving to Preto is the same operation. No migration wizard. No data export. Just a URL swap.
No data migration. No SDK to remove. No refactor required.
Book a 30-minute demo. We'll show you what your OpenAI spend looks like through Preto — and what we'd recommend cutting first.
Book a Demo →Or email gaurav@preto.ai
What they said after switching.
[Your quote from a team that switched from Helicone will go here.]
[Name], [Role] at [Company]
[Your quote from a team that switched from Helicone will go here.]
[Name], [Role] at [Company]
We're in private beta. Quotes coming soon — reach out if you want to be first.