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use case

AI agent spend monitor pilot — 30 days to find the runaway calls

A fixed-scope pilot for teams shipping OpenAI, Anthropic, Bedrock, or coding-agent workflows who need cost, latency, and budget alerts before the provider invoice arrives.

AI agent spend monitor pilot

Instrument one production agent in 10 minutes. Run it for 30 days. Leave with a clear answer: which agents, prompts, routes, models, and customers are driving cost and failures?

Who this is for

  • AI SaaS teams with real OpenAI, Anthropic, Bedrock, or OpenRouter spend.
  • Engineering teams using Claude Code, Cursor, Codex, or other coding agents heavily.
  • Agencies building agent workflows for multiple customers.
  • Platform teams adding LLM calls to an existing SaaS product.

What we install

One of three paths:

  1. @sutrace/llm wrapper around an existing OpenAI or Anthropic client.
  2. Sutrace LLM proxy for teams that want provider-compatible base URLs.
  3. @sutrace/agent-cli for local coding-agent telemetry.

The first signal should appear in the Agents dashboard within 60 seconds of the first call.

What you get in week one

  • Spend by project, agent, model, and route.
  • Input/output token totals.
  • p50/p95 latency.
  • Error rate and failed calls.
  • Per-run, daily, monthly, agent, and model-call budget alerts.
  • Recent call table with provider, model, status, tokens, cost, and latency.

Sutrace does not need prompt or completion text for this pilot. The first version records metadata and usage, not customer content.

Pilot terms

  • Duration: 30 days.
  • Setup: one 30-minute install call.
  • Scope: one workspace, one to three agents, up to 100k events.
  • Price: free for the first 10 founder-led pilots; $500 fixed after that.
  • Exit: keep using the free tier or convert to Starter/Team.

Success criteria

The pilot is successful if, by day 14:

  • The team can identify the top 3 cost drivers.
  • At least one useful budget alert has fired or been tested.
  • The dashboard answers a question the provider invoice cannot answer.
  • Setup took under 10 minutes of code changes after credentials were ready.

Install snippet

import OpenAI from "openai";
import { wrapOpenAI } from "@sutrace/llm";

const openai = wrapOpenAI(new OpenAI({ apiKey: process.env.OPENAI_API_KEY }), {
  apiKey: process.env.SUTRACE_API_KEY,
  project: "support-agent",
  agent: "refund-router",
  route: "/tickets/summarise",
  budget: { perRunUsd: 1, dailyUsd: 20, monthlyUsd: 500 },
});

Smoke test:

npx @sutrace/llm test --api-key "$SUTRACE_API_KEY"

What we need from you

  • One engineer for 30 minutes.
  • A non-production or production agent path with visible usage.
  • A Sutrace API key from /connect.
  • Agreement that Sutrace can use anonymized learnings, not your customer data.

Book the pilot

Email akshay@akshaysarode.com with:

  • Company:
  • Agent/framework:
  • Provider/model:
  • Monthly LLM spend estimate:
  • What you want to catch first: