Micropayments
Budgets for machine payments
Set spending limits per request and per session for API, inference, and compute usage.
Industries
Compute & AI infra · Personal agents
Best for
Inference, APIs, service spend
Controls
Per-call caps, session budgets, velocity
Outcome
Machine-speed buying with hard limits
How per-call spend stays inside budget
Budget at request time
82% spent · $0.88 left
Per-call decisions
Every paid request is checked before the provider is paid. Low-cost calls keep flowing, while an oversized call or an exhausted session both stop without a human in the loop.
Case Study
Enchant: x402 and MPP in action
Enchant uses Conto to apply budgets and approvals to x402 and MPP payments. Try it free and get signup credits.
Visit Enchant at askenchant.comPrompt
User asks Enchant
A task can require a paid tool, data source, or model call.
Quote
Price appears first
The paid step shows its cost before anything runs.
Control
Conto checks policy
Budgets, per-call caps, and approvals are evaluated before spend.
Payment
x402 or MPP clears
Approved micropayments settle and update the user budget.
Payment flow
x402 and MPP micropayments
Spend layer
Conto budgets for every user
Control point
Policy before each paid request clears
Service-spend activity with budget context attached
Machine-speed payments carry the same approval and budget context as other company payment activity.
Payment request
Rules evaluated
Routed to review
1 of 4 rules needs a human before settlement.
Controls that bound automated service spend
Per-call, session, provider, and velocity policies stop runaway spend without forcing every low-cost request into manual review.
Per-call ceilings
Prevent a single API or inference request from blowing past the allowed unit economics for the task.
Session envelopes
Give each task or agent run a hard budget so many small calls cannot add up to an unlimited bill.
Provider-level policy
Restrict autonomous spend to the providers or service types you actually trust for the workflow.
Velocity monitoring
Catch broken loops or runaway retry behavior before the agent can hammer a paid endpoint continuously.
How per-call payments stay inside budget
Agents can buy APIs, inference, and compute on demand while Conto checks unit economics and task budgets before each paid request.
Step 1
The agent chooses a paid service
A compute or API workflow selects the service endpoint and proposes the call based on price, latency, or task fit.
Step 2
Conto checks call-level economics
Conto checks each request against your per-call limits, session budgets, and provider rules before the service is paid.
Step 3
Normal usage continues until budget is spent
Low-cost calls keep flowing. Expensive routes or exhausted budgets are blocked before the provider is paid.
Demo
No single call escapes the session budget
A buyer agent shops for inference call by call. Cheap ones clear, but the session budget caps the rest.
Conto products behind service-spend budgets
Runtime controls
Policy Engine
Define the rules for how agents spend, then evaluate every payment request before funds move. Conto keeps limits, categories, trust requirements, and approval rules in the transaction path.
Explore productWallet operations
Agent Wallets
Give each agent a wallet that can be governed by policy, monitored by finance, and connected to the payment workflows it owns.
Explore productFinancial visibility
Audit and Reconciliation
Attach agent, counterparty, policy, approval, and execution context to every transaction so finance can understand what happened without chasing separate systems.
Explore productMachine payments that stay in budget
Engineering teams can let agents buy services dynamically without accepting unbounded cost exposure.
The same control plane works for per-call infrastructure spend and more traditional payouts.
Every paid request records its provider, price, budget, and policy result.