LangSmith traces your LangChain runs. Preto tells you what to change to cut the bill — ranked recommendations, dollar estimates per finding, and budget enforcement at the proxy level. No SDK changes required.
No credit card. No SDK. Works with your existing LangChain code.
LangSmith is the standard tool for debugging and evaluating LangChain applications. If you're building agents and need step-level visibility, it's genuinely great. Teams that look for alternatives have already solved the debugging problem — now they need to actually reduce the LLM bill.
LangSmith requires the LangChain SDK to instrument your code. If you're not using LangChain — or want monitoring without a framework dependency — you need something that works at the HTTP layer instead. Preto is a proxy: one URL change, works with any OpenAI-compatible client.
LangSmith gives you granular execution traces. What it doesn't give you is a ranked list of "change this call to GPT-4o-mini and save $847/month." Preto analyzes traffic patterns automatically and surfaces the highest-dollar optimizations first — no trace spelunking required.
LangSmith is an observation tool. When spend spikes, it shows you the traces — it doesn't stop the spend. Preto enforces hard budget limits at the proxy level: when a threshold is hit, requests are blocked before they reach OpenAI. No runaway cost surprises.
Built for debugging and evaluating LangChain applications. Deep visibility into chains, agents, and tool calls. Requires LangChain SDK. Best for teams focused on quality and correctness.
Built for LLM cost reduction. Works as an HTTP proxy — no SDK required. Tells you what to change, estimates savings before you act, and enforces spend limits at the proxy level.
| Feature | LangSmith | Preto.ai |
|---|---|---|
| Proxy-based integration (no SDK) | ✗ | ✓ |
| Cost tracking per request | Partial | ✓ |
| Chain + agent tracing | ✓ | ✗ not our focus |
| LLM evaluation + evals | ✓ | ✗ |
| AI cost recommendations | ✗ | ✓ |
| Dollar savings estimates per finding | ✗ | ✓ |
| Savings dashboard | ✗ | ✓ |
| Budget enforcement (hard-block) | ✗ | ✓ |
| Works without LangChain SDK | ✗ | ✓ |
| Prompt management | ✓ | ✗ |
LangSmith is purpose-built for LangChain observability. Every step of your chain is traced — tool calls, retrieval steps, model calls, outputs. For teams building complex agents and needing to understand failure modes or improve quality, this trace data is invaluable. It's exactly the right tool for that job.
Preto works at the HTTP layer — every LLM API call flows through the proxy regardless of which framework made it. It analyzes your traffic patterns with five AI analysis rules and surfaces the highest-dollar optimization opportunities. Each finding includes a projected monthly savings figure so you can prioritize without guessing.
LangSmith would show you this chain's execution trace. Preto surfaces the cost finding automatically, estimates the savings, and tracks when you implement it.
Preto works at the HTTP layer. Your LangChain code doesn't change — just the base_url your OpenAI client points to. LangSmith can keep running alongside it if you want both.
No changes to your chains, agents, or tools. No SDK to remove. LangSmith keeps working if you still want traces.
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 using LangChain + Preto will go here.]
[Name], [Role] at [Company]
[Your quote from a team using LangChain + Preto will go here.]
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We're in private beta. Quotes coming soon — reach out if you want to be first.