The control plane
for AI agent spend

Agents request authority. Policies decide. Humans approve exceptions. Scoped cards execute. Everything is logged.

Agents spend money.
Nobody governs how.

The financial system assumes a human behind every transaction. AI agents bypass that assumption entirely.

01

Shared credentials, unlimited blast radius

Agents borrow a human's corporate card with zero vendor restrictions, zero budget scoping, and no way to trace charges back to specific agent tasks. One compromised agent exposes the entire card limit.

02

Platform lock-in

Ramp Agent Cards only work for Ramp customers. Stripe's primitives are merchant-side. Companies using multiple agent frameworks have no unified governance layer.

03

Finance teams are flying blind

47.6% of businesses use AI tools, but no spend management system differentiates agent-initiated transactions from human ones. Growing autonomous spend sits outside every approval workflow.

From intent to audit trail

An agent requests authority. Policy decides. Humans approve exceptions. The system issues scoped instruments and logs everything.

01

Request

Agent submits a Spend Intent: vendor, amount, task, and business reason.

02

Evaluate

Policy engine checks vendor approval, budget availability, and spend rules in real time.

03

Approve & Execute

Safe requests auto-approve. Borderline ones route to a human. A task-scoped virtual card is issued.

04

Audit

Complete chain: LLM reasoning, policy evaluation, approval decision, transaction, receipt, accounting sync.

Delegated authority,
not agent personhood

Controlled delegation with budgets, policies, and accountability. Not independent financial entities.

Platform

Cross-platform policy engine

Works with any card issuer, bank, or stablecoin rail. Not locked to Ramp, Stripe, or any single ecosystem. One policy layer governs them all.

Budgets

Budget hierarchies and scoping

Allocate per agent, per task, per vendor, per time window. Sub-budgets with automatic rollover and threshold alerts.

Provenance

Reasoning-to-receipt chain

Links the LLM reasoning chain directly to payment authorization. Critical for compliance, insurance underwriting, and dispute resolution.

Accounting

Accounting system integration

Syncs to QuickBooks Online and NetSuite. GL codes, cost centers, and approval metadata flow directly into your books.

Wire any agent framework
in an afternoon

Open-source MCP server, REST API, and CLI. Works with OpenAI Agents SDK, Claude MCP, LangChain, CrewAI, and any MCP-compatible framework.

REST APICLIMCP ServerTypeScriptPython

request_spend — Submit a Spend Intent with vendor, amount, task, and reason

get_budget_remaining — Check available budget before committing

get_policy_explanation — Understand why a request was approved or denied

lock_card — Instantly revoke a compromised card in under 200ms

# Install $ npm install @imprest/mcp-server # Request spend authority $ imprest request-spend \ --vendor "OpenAI" \ --amount 500.00 \ --task "eval-pipeline-v3" ✓ auto-approved (within software budget) ✓ card issued **** 7291, 24h, vendor-locked ✓ audit logged intent → approval → card

The governance layer for
a $1.7 trillion market

Every major payment network is building agentic commerce infrastructure. The policy and compliance layer above all of them remains unclaimed.

$1.7T
Embedded finance market by 2030, growing from $135B today as agents become primary transactors.
Juniper Research, McKinsey
400K+
AI agents with active purchasing power. 140M transactions processed in the last nine months.
Circle, March 2026
44%
Of finance teams will deploy AI agents for procurement and expense management in 2026.
Wolters Kluwer

Ready to govern
agent spend?

We are onboarding design partners for Q2 2026. Paid pilots with dedicated integration support.

Backed by 199 Biotechnologies

Open source
MCP Server ready
View integration docs