
Langfuse
Helicone AI
LangChain
Portkey
Braintrust
Braintrust.dev
Humanloop
Build and deploy LLM applications with confidence

Helicone AI
Langfuse
MarginDash
LLMCap
OpenAI
Corrath
Claude by Anthropic
Know your AI costs per customer, per feature, per tier. PerUnit attributes every dollar of AI provider spend to the customers and features driving it.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | langchain.com | perunit.ai |
| Pricing | — | |
| Platforms | — | |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of LangSmith yet.
Your AI bill is growing — but which customers, features, and pricing tiers are driving it? OpenAI, Anthropic, and Google dashboards show totals. Totals don't help you decide who to charge more, what to gate, or where to cut. PerUnit breaks down AI spend by customer, feature, and pricing tier so...
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
LangSmith is recommended for AI developers, machine learning engineers, and businesses aiming to build, test, and optimize applications based on language models. It is particularly useful for teams that require robust evaluation tools and a streamlined process for managing and deploying language-driven applications.
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
🦜🛠️ Getting started with LangSmith - Integrating with LANGCHAIN powered Web Applications & Chatbots
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing LangSmith and PerUnit.
PerUnit's answer:
PerUnit is built for AI unit economics, not just cost tracking. We break down AI spend by:
Customer — see which accounts drive costs Feature — see which AI features burn through tokens Pricing tier — free vs paid user breakdown We connect AI costs to revenue via Stripe. Provider dashboards show totals; observability tools show tokens. PerUnit shows who's driving costs and whether they're profitable. No data warehouse or pipelines — direct API sync to OpenAI, Anthropic, and Google.
PerUnit's answer:
PerUnit is built for product and pricing decisions, not observability. Competitors focus on tokens, latency, and traces. We focus on:
Cost per customer Cost per feature Cost per tier — connected to revenue If you need to know who to charge more, what to gate, or where to cut, PerUnit gives you that. No pipelines, no data engineering, no data warehouse.
PerUnit's answer:
Founders, product managers, and CFOs at companies building AI-powered products. Anyone who needs to answer:
Which customers cost the most? Are free users profitable? Should we gate AI behind paid plans? Teams that care about unit economics and margins, not just total spend.
PerUnit's answer:
We've shipped products with AI and watched margins disappear without knowing why. The AI bill was one number — we couldn't see which customers or features were driving it. Every product and pricing decision was a guess.
We built PerUnit so product teams can have the same clarity on AI costs that they have on revenue and headcount.
PerUnit's answer:
Frontend: Next.js, React, TypeScript, Tailwind CSS Integrations: OpenAI, Anthropic, Google APIs, Stripe Deployment: Vercel
PerUnit's answer:
PerUnit is in early access. We're onboarding a small group of teams who need clarity on their AI unit economics. Our early users are founders and PMs at companies building AI features — from early-stage to growth — who want cost attribution before scaling further.
Share your experience with using LangSmith and PerUnit. For example, how are they different and which one is better?
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