AXME MESH
Set budget limits on every agent — and stop runaway spend before it hits your bill
One misconfigured agent can spend $500 overnight. Without per-agent cost attribution, you get a surprise bill and no way to trace which agent caused it.
AXME Mesh tracks token spend, API call costs, and compute per agent.
See spend before the invoice
LLM agents burn tokens on retries, runaway loops, and verbose tool chains. Without per-agent attribution, finance sees one OpenAI line item — engineering guesses which feature caused it.
AXME Mesh attributes token spend, third-party API cost, and compute to each agent and team. Soft alerts warn before limits; hard caps stop runaway agents automatically.
CAPABILITIES
How it works.
Token attribution
LLM spend per agent and team.
API call costs
Third-party usage tracked.
Compute
Runtime cost allocation.
DEEP DIVE
Production patterns.
Hard caps
Stop agent at limit.
Soft alerts
Notify before breach.
Fleet dashboards
Trends and forecasts.
Surprise bill → attributed spend
One OpenAI line item
# finance: which agent spent $500? # engineering: shrugs
Mesh attribution
mesh.cost.by_agent("support-bot")
# cap + alert at 80%Caps, alerts, and attribution
Soft alerts notify owners at 80% of budget so they can tune prompts or limits. Hard caps stop the agent at the threshold — pairing with kill switch for immediate effect. Historical trends show which agents grew spend week over week.
Combine with policy-enforcement so budget rules are not optional — and with fleet visibility to correlate spend spikes with error rates or new deployments.
Common questions
- What costs are tracked?
- Token usage from LLM providers, metered API calls, and allocated compute for agent runtimes — exact meters depend on integration configuration.
- Can I set fleet-wide and per-agent caps?
- Yes — hierarchy from organization → team → agent with inheritance and overrides.
- Does cost control work without Mesh?
- Cloud executes intents; Mesh provides attribution and caps. Production fleets typically use both.
Related reading
Deeper dives from the AXME blog.
Your AI Agent Spent $500 Overnight and Nobody Noticed
AI agents call LLMs. LLMs cost money per token. Nobody tracks it per agent. One runaway loop and your OpenAI bill is a disaster.
Read post →Your AI Agent Made 10,000 API Calls in an Hour. Here's How to Stop That.
One runaway retry loop. 10,000 API calls. $130 in LLM costs. No rate limit fired because you never built one. Here's how to add centralized rate and cost limiting to AI agents.
Read post →
Related
Related links
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