Hi HN, I built Orbit to solve a visibility gap in AI cost management.
Provider dashboards show aggregate API spend, but don't answer which product feature is driving it. When your bill spikes, you're left guessing whether it's the chatbot, document processor, or an agent workflow running inefficiently.
Orbit attributes every LLM call to a specific feature, task, or customer. You wrap your existing AI client with our SDK, tag calls with metadata, and get real-time dashboards showing cost, latency, and error rates broken down by feature.
Key capabilities:
Per-feature cost and performance attribution
Agentic workflow tracking (group multi-step LLM calls by task or customer)
Support for OpenAI, Anthropic, and Gemini
SDKs for Node.js and Python
One-line integration, no API key access required
Free tier available.
Why I'm showing this now: I’m looking for 5-10 "Design Partners" to break the SDK and tell me what’s missing. I'm especially interested in teams building complex agents who feel they've lost control of their token spend.
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Show HN: Orbit – Track "zombie loops" and cost-per-feature in AI agents · HackerTrans
Provider dashboards show aggregate API spend, but don't answer which product feature is driving it. When your bill spikes, you're left guessing whether it's the chatbot, document processor, or an agent workflow running inefficiently.
Orbit attributes every LLM call to a specific feature, task, or customer. You wrap your existing AI client with our SDK, tag calls with metadata, and get real-time dashboards showing cost, latency, and error rates broken down by feature.
Key capabilities:
Per-feature cost and performance attribution Agentic workflow tracking (group multi-step LLM calls by task or customer) Support for OpenAI, Anthropic, and Gemini SDKs for Node.js and Python One-line integration, no API key access required Free tier available.
Why I'm showing this now: I’m looking for 5-10 "Design Partners" to break the SDK and tell me what’s missing. I'm especially interested in teams building complex agents who feel they've lost control of their token spend.