LLM observability explains what happened inside a model call. AI profit analytics explains whether the customer, feature, or acquisition source attached to those calls earns more than it costs. Most production AI products eventually need both—but they solve different decisions.
Use LLM observability to debug model behavior
Traces, spans, prompt versions, response quality, latency, tool calls, errors, and evals help engineering teams understand why a request behaved as it did. This is the right layer for debugging agents, comparing prompts, inspecting retrieval, and improving response quality.
Use AI profit analytics to debug the business
Payments, refunds, processor fees, account identity, feature usage, model cost, and unallocated evidence answer a different question: which customers and features create contribution profit? A trace can show that a call cost $0.04; it cannot prove that the customer paid or that the account is profitable.
The data model that connects them
Trace or model call → stable user/account ID → payment customer → observed revenue − fully priced AI cost.
Keep prompt text optional and private. For economics, the necessary fields are provider, model, token categories, status, latency, feature, prompt version, user/account IDs, and request time. Revenue still comes from the payment provider—not the LLM trace.
Which one should you install first?
| Your immediate question | Start with |
|---|---|
| Why is this response wrong or slow? | LLM observability |
| Which prompt or model version performs better? | LLM observability plus evals |
| Which customers cost more than they pay? | AI profit analytics |
| Which acquisition source brings profitable AI users? | AI profit analytics plus analytics attribution |
| Can we lower cost without hurting quality? | Both: observability for quality, profit analytics for economics |
Where Grow or Die stops
Grow or Die is not a full trace explorer, prompt playground, or eval platform. It wraps server-side model clients to observe usage and business context, then joins that cost to traffic and revenue. If you need complete trace inspection, use a dedicated LLM observability product alongside it.