Preto sits between your app and your LLM provider. It finds which calls use the wrong model, which users are unprofitable, and exactly what to change — each recommendation with a projected dollar savings. The OpenAI dashboard shows you spend. Preto shows you waste.
10K requests free · No credit card · No SDK required · Or let the founder configure it for you
"I kept seeing teams waste 40–60% of their LLM spend on model choices they never revisited. A GPT-4 call that costs $0.06 could run on GPT-5 Mini for $0.002 — same quality. One URL change shouldn't be this hard to justify. So I built Preto to make the ROI obvious in under an hour."
You've been meaning to audit your LLM usage for weeks. You know GPT-4 is expensive. You suspect some calls don't need it. But with 40+ places in the codebase touching the API and zero per-feature breakdown, you don't know where to start.
So you send the Slack message: "Hey team, be mindful of LLM usage." Nothing changes. The CFO asks again.
Preto ends that loop.
No SDK to install. No agent to run. No refactor required. Swap your base URL and every request flows through Preto — logged, costed, and analyzed.
Swap your OpenAI base URL to proxy.preto.ai. One line. Your existing code keeps working exactly as before.
Every request is logged with cost, model, latency, and which feature triggered it. Async. Under 50ms overhead.
Within 24 hours, see exactly what to change — with projected monthly savings per recommendation. Implement the top one and track the money coming back.
Think CloudHealth for LLMs. We don't just show you costs. We tell you exactly how to cut them, and track the money you get back.
Every request logged with model, tokens, cost, and latency. Broken down by feature, by user, by environment. See which users are profitable and which ones are eating your margin. Know exactly where every dollar goes, not just the monthly total.
Five analysis rules run on every workspace automatically: (1) Model downgrade detection, (2) Duplicate prompt caching, (3) Cheaper embedding alternatives, (4) Prompt optimization, (5) Rate limit waste. Each finding includes a projected monthly savings figure, ranked by dollar impact. Works across OpenAI, Anthropic, NVIDIA, and TTS providers.
The metric your CFO actually wants: "Money saved this month: $4,234." Not another cost dashboard — a savings engine with measurable, attributable ROI you can show in a weekly standup.
Set hard spend limits per workspace. Get alerted before you hit them — or configure Preto to hard-block requests when the threshold is crossed. Never get a surprise $10K bill again. Infrastructure, not just alerts.
You're sending 2,300 requests/day to GPT-5 ($1.25/1M input) for tasks under 500 tokens. GPT-5 Mini ($0.25/1M) handles these at equivalent quality — 80% cheaper. This is your highest-impact optimization.
Preto generates recommendations like this within 24 hours of seeing your traffic. Works across OpenAI, Anthropic, and NVIDIA. Most teams implement their first one within a week.
Free up to 10K requests. No credit card required.
They show you what you spent.
We show you what to do about it.
| Helicone | Langfuse | Portkey | Datadog LLM | Preto.ai | |
|---|---|---|---|---|---|
| Cost Attribution (by feature/user) | ✓ | Manual tags | ✓ | Basic | ✓ |
| AI Savings Recommendations | ✗ | ✗ | ✗ | ✗ | ✓ |
| Savings Dashboard | ✗ | ✗ | ✗ | ✗ | ✓ |
| Budget Enforcement | ✓ | Alerts only | ✓ | ✗ | ✓ |
| TTS/Voice AI Support | ✗ | ✗ | ✗ | ✗ | ✓ |
| Keep Your Own API Keys | ✓ | ✓ | ✓ | ✓ | ✓ |
| 1-Line Integration | ✓ | ✗ | ✓ | ✗ | ✓ |
| Pricing (entry paid tier) | $20/seat/mo | $59/mo | ~$499/mo | $8/10K req | $99/mo |
Fair questions. Direct answers.
"If Preto goes down, does my app go down?"
Logging and cost analysis run asynchronously, completely off the critical path — if our logging layer or database has a problem, your requests keep flowing to your provider, unaffected. And if the proxy itself is ever unreachable, your requests fall straight through to your provider — you lose visibility for that window, never availability. If you're putting Preto in front of production, point one non-critical endpoint at it first, run it for a day, then expand. Questions about failover for your setup? Email gaurav@preto.ai — a straight answer, not a ticket.
"You're in the request path — what about my keys and data?"
Your API keys are encrypted at rest with AES-256 and used only to forward your requests to your own provider — you keep your keys and your provider relationship. By default Preto logs request content to power recommendations; you can switch prompt logging off per workspace at any time, and we'll store only metadata — model, tokens, cost, latency — never prompt or response text. Built-in PII masking can redact or hash sensitive data before it ever reaches the model. For full details on data retention and compliance status, email gaurav@preto.ai.
Pro pays for itself the first time you implement a recommendation.
base_url. No SDK to install, no agents to deploy, no architecture changes. Most teams complete integration in under 10 minutes. You'll see your first cost breakdown within minutes of your first request flowing through.
10K requests free. Setup takes 5 minutes.
No credit card. Free up to 10K requests. If Pro doesn't find 2x its cost in savings within 30 days, cancel free.
Want me to set it up for you? Reply to gaurav@preto.ai with your provider and I'll configure the proxy in 2 minutes.