Rank #1 of 5 in Expense Management
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See what an agent can do with Ramp before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; commands tagged live-capable can re-run against the real endpoint from our edge, right now (▶ run live — the exact same request, live and recorded lines always labeled); the live MCP handshake runs real requests from our edge, right now — including, where the server allows it, one real read-only tool call (bring your own key for auth-gated servers); sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).
$curl -s https://api.ramp.com/developer/v1/transactions # the documented Developer API, keyless → access-token errorrecorded session — replayed, not liveVerified integrations
Connections to other tracked products — hover a chip for the verbatim evidence quote behind it.
By theme — the product's score on each story themeBy theme
Accounting close — stories about accounting close in this arenaAccounting closeevidence →
Stories about accounting close in this arena
Agenticness — how well agents can access and operate the productAgenticnessevidence →
How well agents can access and operate the product
Ai automation — stories about ai automation in this arenaAi automationevidence →
Stories about ai automation in this arena
Automation depth — how much of the product can run unattendedAutomation depthevidence →
How much of the product can run unattended
Bills ap — stories about bills ap in this arenaBills apevidence →
Stories about bills ap in this arena
Cards controls — stories about cards controls in this arenaCards controlsevidence →
Stories about cards controls in this arena
Expense data access — stories about expense data access in this arenaExpense data accessevidence →
Stories about expense data access in this arena
Openness — open source, data portability, and self-hosting storiesOpennessevidence →
Open source, data portability, and self-hosting stories
Policy approvals — stories about policy approvals in this arenaPolicy approvalsevidence →
Stories about policy approvals in this arena
Privacy posture — data-handling and privacy storiesPrivacy postureevidence →
Data-handling and privacy stories
Receipts capture — stories about receipts capture in this arenaReceipts captureevidence →
Stories about receipts capture in this arena
Reimbursements — stories about reimbursements in this arenaReimbursementsevidence →
Stories about reimbursements in this arena
Spend visibility — stories about spend visibility in this arenaSpend visibilityevidence →
Stories about spend visibility in this arena
Travel — stories about travel in this arenaTravelevidence →
Stories about travel in this arena
Story verdicts — every judged story with its evidenceStory verdicts
Follow the green: where the map greys out is where Ramp stops today. ✓ full · ~ partial · ! disputed · — none · n/a not applicable.
Accounting close — stories about accounting close in this arenaAccounting close
Stories about accounting close in this arena
Transactions sync to QuickBooks, NetSuite, or Xero with GL account, class, and department mappings I control
~6/10
Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
✓8/10
Run multiple legal entities and currencies in one account with consolidated reporting and per-entity books
~5/10
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
API surface
Drive the product through a documented public API
✓9/10
unlocks → Official SDKs · Versioning policy · API sandbox
Subscribe to events via webhooks
✓8/10
Build against official SDKs
—0/10
Issue scoped/least-privilege API credentials for an agent
✓8/10
Connect an agent via an official MCP server
✓9/10
Download a machine-readable API spec (OpenAPI or equivalent)
~3/10
unlocks → Interactive API docs · Official SDKs
Rely on versioned APIs with a documented deprecation policy
—–
Test against a sandbox environment without touching production data
—–
Explore an interactive API reference with runnable examples
—0/10
Docs for agents
Point an agent at llms.txt or agent-oriented docs
✓9/10
Agentic features
Delegate tasks to a built-in AI assistant inside the product
~5/10
Operate the product with natural-language commands
✓8/10
Plug MCP servers into this product so it can use their tools
n/an/a
Get AI-generated insights and suggestions from my data inside the product
✓7/10
Set up automations that run autonomously in the background
~5/10
Ai automation — stories about ai automation in this arenaAi automation
Stories about ai automation in this arena
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
Bills ap — stories about bills ap in this arenaBills ap
Stories about bills ap in this arena
Cards controls — stories about cards controls in this arenaCards controls
Stories about cards controls in this arena
Restrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of sale
✓8/10
Issue physical and virtual corporate cards to the team in minutes, each with its own spend limit
✓8/10
Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared credit
✓8/10
Expense data access — stories about expense data access in this arenaExpense data access
Stories about expense data access in this arena
An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for review
~6/10
Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokens
✓8/10
Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public API
~3/10
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
Policy approvals — stories about policy approvals in this arenaPolicy approvals
Stories about policy approvals in this arena
Build multi-step approval chains — manager, budget owner, finance — with delegation and escalation when approvers sit on requests
~4/10
Every expense carries a full audit trail — edits, approvals, policy checks — that survives an external audit
~4/10
Codify our expense policy — limits by category, role, and context — so in-policy expenses auto-approve and only exceptions reach a human
✓8/10
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
Receipts capture — stories about receipts capture in this arenaReceipts capture
Stories about receipts capture in this arena
Log mileage with map-based distance and claim per-diem rates without building the expense by hand
✓7/10
Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transaction
~5/10
Receipts match to card transactions automatically — with e-receipts pulled from integrations — and I get nudged only when one is genuinely missing
~6/10
Reimbursements — stories about reimbursements in this arenaReimbursements
Stories about reimbursements in this arena
Spend visibility — stories about spend visibility in this arenaSpend visibility
Stories about spend visibility in this arena
Travel — stories about travel in this arenaTravel
Stories about travel in this arena
Sorted by importance (agentic first) (high → low) · 53/53 stories · click a row’s chevron for the rationale and evidence
Connect an agent via an official MCP server G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 9/10 | Tprobed | |
Drive the product through a documented public API G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | full | 9/10 | Tprobed | |
Delegate tasks to a built-in AI assistant inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | partial | 5/10 | Tprobed | |
Plug MCP servers into this product so it can use their tools G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 3 | n/a | 0/10 | ||
Point an agent at llms.txt or agent-oriented docs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 9/10 | Tprobed | |
Issue scoped/least-privilege API credentials for an agent G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Tprobed | |
Operate the product with natural-language commands G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Tprobed | |
Subscribe to events via webhooks G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Cclaimed | |
Use an official CLI G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 8/10 | Tprobed | |
Get AI-generated insights and suggestions from my data inside the product G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | full | 7/10 | Tprobed | |
Run the product headlessly / in CI for automation G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 6/10 | Tprobed | |
Set up automations that run autonomously in the background G Agentic features | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 5/10 | Tprobed | |
Download a machine-readable API spec (OpenAPI or equivalent) G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 3/10 | Tprobed | |
Build against official SDKs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | 0/10 | ||
Explore an interactive API reference with runnable examples G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | 0/10 | ||
Rely on versioned APIs with a documented deprecation policy G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | untested | none yet | |
Test against a sandbox environment without touching production data G Api quality | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 1 | none | untested | none yet | |
Codify our expense policy — limits by category, role, and context — so in-policy expenses auto-approve and only exceptions reach a human C Policy engine | finance lead | Policy approvals — stories about policy approvals in this arenaPolicy approvals | 3 | full | 8/10 | Cclaimed | |
Define rules that trigger actions automatically on events G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 3 | full | 8/10 | Cclaimed | |
Issue physical and virtual corporate cards to the team in minutes, each with its own spend limit C Card issuance | founder | Cards controls — stories about cards controls in this arenaCards controls | 3 | full | 8/10 | Cclaimed | |
Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokens C Api access | developer | Expense data access — stories about expense data access in this arenaExpense data access | 3 | full | 8/10 | Tprobed | |
Restrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of sale C Card controls | finance lead | Cards controls — stories about cards controls in this arenaCards controls | 3 | full | 8/10 | Cclaimed | |
See company spend in real time — by team, category, and merchant — the day it happens, not when statements land C Dashboards | founder | Spend visibility — stories about spend visibility in this arenaSpend visibility | 3 | full | 8/10 | Cclaimed | |
Submit an out-of-pocket expense and get reimbursed by direct deposit in days, tracked from submission to payout C Domestic | employee | Reimbursements — stories about reimbursements in this arenaReimbursements | 3 | full | 7/10 | Cclaimed | |
An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for review C Agent access | ai-native user | Expense data access — stories about expense data access in this arenaExpense data access | 3 | partial | 6/10 | Tprobed | |
Transactions sync to QuickBooks, NetSuite, or Xero with GL account, class, and department mappings I control C Accounting sync | finance lead | Accounting close — stories about accounting close in this arenaAccounting close | 3 | partial | 6/10 | Cclaimed | |
Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transaction C Receipt capture | employee | Receipts capture — stories about receipts capture in this arenaReceipts capture | 3 | partial | 5/10 | Cclaimed | |
Export all of my data in open formats and leave G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | partial | 3/10 | Tprobed | |
Prevent my data from being used to train AI models G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 3 | none | untested | none yet | |
Self-host the core product G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | n/a | untested | none yet | |
AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraud C Ai coding | ai-native user | Ai automation — stories about ai automation in this arenaAi automation | 2 | full | 8/10 | Cclaimed | |
Allocate budgets to teams and projects and have card limits and approvals actually enforce them C Budgets | finance lead | Spend visibility — stories about spend visibility in this arenaSpend visibility | 2 | full | 8/10 | Cclaimed | |
Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared credit C Virtual cards | finance lead | Cards controls — stories about cards controls in this arenaCards controls | 2 | full | 8/10 | Cclaimed | |
Reimburse employees abroad in their local currency without running a separate international payments process C International | finance lead | Reimbursements — stories about reimbursements in this arenaReimbursements | 2 | full | 8/10 | Cclaimed | |
Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig C Close | finance lead | Accounting close — stories about accounting close in this arenaAccounting close | 2 | full | 8/10 | Cclaimed | |
An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happens C Ai policy | ai-native user | Ai automation — stories about ai automation in this arenaAi automation | 2 | full | 7/10 | Tprobed | |
Book flights and hotels in-platform with travel policy applied at booking time, not expensed and argued about later C Booking | employee | Travel — stories about travel in this arenaTravel | 2 | full | 7/10 | Cclaimed | |
Log mileage with map-based distance and claim per-diem rates without building the expense by hand C Mileage perdiem | employee | Receipts capture — stories about receipts capture in this arenaReceipts capture | 2 | full | 7/10 | Cclaimed | |
Do everything through the API that I can do in the UI G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | partial | 6/10 | Tprobed | |
Receipts match to card transactions automatically — with e-receipts pulled from integrations — and I get nudged only when one is genuinely missing C Receipt matching | employee | Receipts capture — stories about receipts capture in this arenaReceipts capture | 2 | partial | 6/10 | Cclaimed | |
Run accounts payable in the same platform — capture invoices, route approvals, and pay vendors by ACH, check, or wire C Bill pay | finance lead | Bills ap — stories about bills ap in this arenaBills ap | 2 | partial | 6/10 | Cclaimed | |
Run multiple legal entities and currencies in one account with consolidated reporting and per-entity books C Multi entity | finance lead | Accounting close — stories about accounting close in this arenaAccounting close | 2 | partial | 5/10 | Cclaimed | |
Build multi-step approval chains — manager, budget owner, finance — with delegation and escalation when approvers sit on requests C Approvals | finance lead | Policy approvals — stories about policy approvals in this arenaPolicy approvals | 2 | partial | 4/10 | Cclaimed | |
Every expense carries a full audit trail — edits, approvals, policy checks — that survives an external audit C Audit trail | finance lead | Policy approvals — stories about policy approvals in this arenaPolicy approvals | 2 | partial | 4/10 | Cclaimed | |
Perform bulk operations across many items at once G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | partial | 4/10 | Cclaimed | |
Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public API C Card api | developer | Expense data access — stories about expense data access in this arenaExpense data access | 2 | partial | 3/10 | Tprobed | |
Choose where my data is stored (region/residency) G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Control data retention and deletion G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Opt out of telemetry and usage tracking G | ai-native user | Privacy posture — data-handling and privacy storiesPrivacy posture | 2 | none | untested | none yet | |
Read the product's source under an open license G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 2 | none | untested | none yet | |
Schedule recurring jobs or workflows G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 2 | none | untested | none yet | |
A trip's expenses — bookings, cards, receipts — collect themselves into one itinerary-linked report C Trip expenses | employee | Travel — stories about travel in this arenaTravel | 1 | partial | 5/10 | Cclaimed | |
Version, review, and roll back my automations G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 1 | none | untested | none yet |
Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 28 stories with headroom
What would move Ramp’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.
Privacy posture — data-handling and privacy storiesPrevent my data from being used to train AI models
nonemoves PA Scoreimpact 30
Missing: any privacy policy statement, opt-out mechanism, or documentation about AI training data usage.
Agenticness — how well agents can access and operate the productBuild against official SDKs
nonemoves agent-readyimpact 30
Missing: any documentation of official SDKs/client libraries in specific languages, package registry listings, or SDK-specific quickstart guides.
Agenticness — how well agents can access and operate the productExplore an interactive API reference with runnable examples
nonemoves API qualityimpact 30
Missing: any mention of an interactive console or runnable example feature in the docs.
Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy
nonemoves API qualityimpact 30
Missing: versioning scheme documentation, deprecation policy/notice process, changelog or migration guidance for breaking changes.
Agenticness — how well agents can access and operate the productDelegate tasks to a built-in AI assistant inside the product
partialq5/10moves Built-in AIimpact 22.5
Missing: evidence of an in-app chat/assistant UI natively embedded in Ramp (not via MCP to third-party LLMs), and independent confirmation of task delegation working end-to-end within the product.
Openness — open source, data portability, and self-hosting storiesExport all of my data in open formats and leave
partialq3/10moves PA Scoreimpact 21
Missing: explicit full data export/takeout functionality, confirmation of open-format (CSV/JSON) bulk export, evidence of exporting all data types (bills, cards, reimbursements) not just transactions.
Agenticness — how well agents can access and operate the productDownload a machine-readable API spec (OpenAPI or equivalent)
partialq3/10moves API qualityimpact 21
Missing: an explicit OpenAPI/Swagger spec document, a documented download endpoint, or third-party confirmation that the API schema is available in a standard machine-readable spec format.
Automation depth — how much of the product can run unattendedSchedule recurring jobs or workflows
nonemoves PA Scoreimpact 20
Ramp's automation is event-driven (webhooks) or rules-based (route requests, reminders, auto-rebooking) rather than a documented recurring-job/scheduler capability that an AI agent could invoke via API, MCP, or CLI.
Showing the top 8 of 28 — every none/partial verdict in the story verdicts table is headroom.
Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.
Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map14 surfaces · 40 covered stories
Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.
Llms guides docs24 stories
- Point an agent at llms.txt or agent-oriented docs
- Run the product headlessly / in CI for automation
- Connect an agent via an official MCP server
- Use an official CLI
- Drive the product through a documented public API
- Issue scoped/least-privilege API credentials for an agent
- Subscribe to events via webhooks
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- Operate the product with natural-language commands
- Download a machine-readable API spec (OpenAPI or equivalent)
- An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happens
- Perform bulk operations across many items at once
- Define rules that trigger actions automatically on events
- Restrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of sale
- Issue physical and virtual corporate cards to the team in minutes, each with its own spend limit
- Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared credit
- An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for review
- Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokens
- Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public API
- Do everything through the API that I can do in the UI
- Export all of my data in open formats and leave
- Allocate budgets to teams and projects and have card limits and approvals actually enforce them
- See company spend in real time — by team, category, and merchant — the day it happens, not when statements land
Expense management docs17 stories
- Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
- Get AI-generated insights and suggestions from my data inside the product
- AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraud
- An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happens
- Define rules that trigger actions automatically on events
- Restrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of sale
- Issue physical and virtual corporate cards to the team in minutes, each with its own spend limit
- Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared credit
- Build multi-step approval chains — manager, budget owner, finance — with delegation and escalation when approvers sit on requests
- Every expense carries a full audit trail — edits, approvals, policy checks — that survives an external audit
- Codify our expense policy — limits by category, role, and context — so in-policy expenses auto-approve and only exceptions reach a human
- Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transaction
- Receipts match to card transactions automatically — with e-receipts pulled from integrations — and I get nudged only when one is genuinely missing
- Submit an out-of-pocket expense and get reimbursed by direct deposit in days, tracked from submission to payout
- Allocate budgets to teams and projects and have card limits and approvals actually enforce them
- See company spend in real time — by team, category, and merchant — the day it happens, not when statements land
- A trip's expenses — bookings, cards, receipts — collect themselves into one itinerary-linked report
ramp.com16 stories
- Transactions sync to QuickBooks, NetSuite, or Xero with GL account, class, and department mappings I control
- Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
- Get AI-generated insights and suggestions from my data inside the product
- AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraud
- Define rules that trigger actions automatically on events
- Restrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of sale
- Issue physical and virtual corporate cards to the team in minutes, each with its own spend limit
- Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared credit
- An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for review
- Codify our expense policy — limits by category, role, and context — so in-policy expenses auto-approve and only exceptions reach a human
- Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transaction
- Receipts match to card transactions automatically — with e-receipts pulled from integrations — and I get nudged only when one is genuinely missing
- Submit an out-of-pocket expense and get reimbursed by direct deposit in days, tracked from submission to payout
- Allocate budgets to teams and projects and have card limits and approvals actually enforce them
- See company spend in real time — by team, category, and merchant — the day it happens, not when statements land
- A trip's expenses — bookings, cards, receipts — collect themselves into one itinerary-linked report
Hc docs14 stories
- Connect an agent via an official MCP server
- Drive the product through a documented public API
- Issue scoped/least-privilege API credentials for an agent
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Delegate tasks to a built-in AI assistant inside the product
- Operate the product with natural-language commands
- AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraud
- An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happens
- Perform bulk operations across many items at once
- An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for review
- Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public API
- Do everything through the API that I can do in the UI
- Receipts match to card transactions automatically — with e-receipts pulled from integrations — and I get nudged only when one is genuinely missing
Corporate cards docs13 stories
- An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happens
- Define rules that trigger actions automatically on events
- Restrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of sale
- Issue physical and virtual corporate cards to the team in minutes, each with its own spend limit
- Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared credit
- Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public API
- Build multi-step approval chains — manager, budget owner, finance — with delegation and escalation when approvers sit on requests
- Every expense carries a full audit trail — edits, approvals, policy checks — that survives an external audit
- Codify our expense policy — limits by category, role, and context — so in-policy expenses auto-approve and only exceptions reach a human
- Receipts match to card transactions automatically — with e-receipts pulled from integrations — and I get nudged only when one is genuinely missing
- Submit an out-of-pocket expense and get reimbursed by direct deposit in days, tracked from submission to payout
- Allocate budgets to teams and projects and have card limits and approvals actually enforce them
- See company spend in real time — by team, category, and merchant — the day it happens, not when statements land
llms.txt7 stories
- Point an agent at llms.txt or agent-oriented docs
- Drive the product through a documented public API
- Download a machine-readable API spec (OpenAPI or equivalent)
- Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokens
- Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public API
- Do everything through the API that I can do in the UI
- Export all of my data in open formats and leave
GitHub README6 stories
Intelligence docs5 stories
- Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
- Get AI-generated insights and suggestions from my data inside the product
- Delegate tasks to a built-in AI assistant inside the product
- AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraud
- An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for review
Procurement docs5 stories
- Get AI-generated insights and suggestions from my data inside the product
- Set up automations that run autonomously in the background
- Define rules that trigger actions automatically on events
- Run accounts payable in the same platform — capture invoices, route approvals, and pay vendors by ACH, check, or wire
- Build multi-step approval chains — manager, budget owner, finance — with delegation and escalation when approvers sit on requests
Bill pay docs4 stories
- AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraud
- Run accounts payable in the same platform — capture invoices, route approvals, and pay vendors by ACH, check, or wire
- Every expense carries a full audit trail — edits, approvals, policy checks — that survives an external audit
- Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transaction
Integrations docs4 stories
- Transactions sync to QuickBooks, NetSuite, or Xero with GL account, class, and department mappings I control
- Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
- Run accounts payable in the same platform — capture invoices, route approvals, and pay vendors by ACH, check, or wire
- Every expense carries a full audit trail — edits, approvals, policy checks — that survives an external audit
Reimbursements docs4 stories
- Run multiple legal entities and currencies in one account with consolidated reporting and per-entity books
- Log mileage with map-based distance and claim per-diem rates without building the expense by hand
- Submit an out-of-pocket expense and get reimbursed by direct deposit in days, tracked from submission to payout
- Reimburse employees abroad in their local currency without running a separate international payments process
Travel docs4 stories
- An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happens
- Log mileage with map-based distance and claim per-diem rates without building the expense by hand
- Book flights and hotels in-platform with travel policy applied at booking time, not expensed and argued about later
- A trip's expenses — bookings, cards, receipts — collect themselves into one itinerary-linked report
Probe proofs — replayable recordings from the probe harnessProbe proofs
Replayable recordings from our probe harness — see the Prove-It protocol to submit one.
$curl -s https://api.ramp.com/developer/v1/transactions # the documented Developer API, keyless → access-token errorreproduced$ curl -s https://api.ramp.com/developer/v1/transactions # the documented Developer API, [redacted]less → access-[redacted] error
{"error_v2":{"additional_info":{},"message":"Access [redacted] with given access_[redacted] not found","error_code":"DEVELOPER_7002","notes":"","error_id":"0a12058a"},"error":{"message":"Access [redacted] with given
$curl -sI https://agents.ramp.com/install.sh | head -1 # the documented CLI install script, livereproduced$ curl -sI https://agents.ramp.com/install.sh | head -1 # the documented CLI install script, live HTTP/2 200
$curl -sL https://docs.ramp.com/llms.txt | head -4reproduced$ curl -sL https://docs.ramp.com/llms.txt | head -4 # Ramp Developer API Machine-readable index for Ramp's Developer API documentation.
$curl -s -X POST https://mcp.ramp.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # Ramp's production MCP server, keyless → token challengereproduced$ curl -s -X POST https://mcp.ramp.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # Ramp's production MCP server, [redacted]less → [redacted] challenge
{"detail":"No access [redacted] provided"}
Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence
6 of 21 testable claims verified · 0 contradicted → integrity 29/100
33 distinct capability claims found in Ramp’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.
6
Verified
15
Unverified
0
Contradicted
19
Undersold
Verified (9)
“Provides a Transactions API to retrieve transaction data via an access token”
Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokensfullproof ↗
“Uses OAuth 2.0 with scopes and multiple flows for granular, secure API access”
Issue scoped/least-privilege API credentials for an agentfullproof ↗
“Offers an official CLI to authenticate and manage expenses, bills, and travel from the terminal”
“Ramp MCP lets AI assistants like ChatGPT and Claude query data and take actions via natural language”
“Can grant an AI agent read access, action authority, and approved purchasing power via MCP or CLI”
Issue scoped/least-privilege API credentials for an agentfullproof ↗
“Every spend request gets an AI-generated recommended action based on policy, budget, and funds”
An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happensfullproof ↗
“Automatically sends reminders for missing receipts or requests repayments”
An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happensfullproof ↗
“Natural-language command finds transactions missing receipts/memos and drafts reminder messages”
Operate the product with natural-language commandsfullproof ↗
“Natural-language command can lock a lost card”
Operate the product with natural-language commandsfullproof ↗
Unverified (22)
“Supports webhooks for real-time event notifications”
“Issue physical and virtual corporate cards with real-time spend controls”
Issue physical and virtual corporate cards to the team in minutes, each with its own spend limitfullproof ↗
“Automatically captures receipt and pre-fills memo/category at the moment of card swipe”
Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transactionpartialproof ↗
“Can set submission requirements, spend limits, and block risky merchants/categories before spend occurs”
Restrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of salefullproof ↗
“Create custom virtual cards with fine-grained permissions for specific spend categories or teams”
Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared creditfullproof ↗
“Configurable approval notification workflows based on spend amount or role”
Build multi-step approval chains — manager, budget owner, finance — with delegation and escalation when approvers sit on requestspartialproof ↗
“Reimburses employees in 70+ countries and 40+ currencies within two days”
Reimburse employees abroad in their local currency without running a separate international payments processfullproof ↗
“Google Maps integration auto-calculates mileage for repayments”
Log mileage with map-based distance and claim per-diem rates without building the expense by handfullproof ↗
“OCR captures receipt line items with 99% accuracy”
Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transactionpartialproof ↗
“Performs two- and three-way line-item matching to catch discrepancies before submission”
Run accounts payable in the same platform — capture invoices, route approvals, and pay vendors by ACH, check, or wirepartialproof ↗
“Shows real-time policy compliance status for each travel booking option”
Book flights and hotels in-platform with travel policy applied at booking time, not expensed and argued about laterfullproof ↗
“Per diem automatically adjusts to trip location and duration and shows allowable spend”
Log mileage with map-based distance and claim per-diem rates without building the expense by handfullproof ↗
“Monitors hotel rates and automatically rebooks when price drops $50 or more”
Book flights and hotels in-platform with travel policy applied at booking time, not expensed and argued about laterfullproof ↗
“AI 'teammates' continuously flag fraud, code expenses, and enforce policy”
AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraudfullproof ↗
“AI parses uploaded contracts or screenshots to auto-fill request forms”
AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraudfullproof ↗
“Rules-based workflows automatically route requests to stakeholders by vendor, category, or amount”
Define rules that trigger actions automatically on eventsfullproof ↗
“Syncs transaction and reimbursement data to multiple entities in one step”
Run multiple legal entities and currencies in one account with consolidated reporting and per-entity bookspartialproof ↗
“Automated 3-way matching of purchase orders, receipts, and invoices”
Run accounts payable in the same platform — capture invoices, route approvals, and pay vendors by ACH, check, or wirepartialproof ↗
“Built-in reconciliation tool verifies balances between Ramp and accounting platform”
Transactions sync to QuickBooks, NetSuite, or Xero with GL account, class, and department mappings I controlpartialproof ↗
“End-to-end vendor bill processing that can start in NetSuite or Xero and complete via Ramp payments”
Run accounts payable in the same platform — capture invoices, route approvals, and pay vendors by ACH, check, or wirepartialproof ↗
“Instant per-vendor virtual cards give real-time visibility into SaaS spend without shared card numbers”
Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared creditfullproof ↗
“Receipts are auto-captured, coded to the correct GL account, and auto-approved within policy without filing an expense report”
Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology digfullproof ↗
Undersold (19)
Point an agent at llms.txt or agent-oriented docsfullproof ↗
Run the product headlessly / in CI for automationpartialproof ↗
Drive the product through a documented public APIfullproof ↗
Get AI-generated insights and suggestions from my data inside the productfullproof ↗
Set up automations that run autonomously in the backgroundpartialproof ↗
Delegate tasks to a built-in AI assistant inside the productpartialproof ↗
Download a machine-readable API spec (OpenAPI or equivalent)partialproof ↗
Perform bulk operations across many items at oncepartialproof ↗
An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for reviewpartialproof ↗
Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public APIpartialproof ↗
Do everything through the API that I can do in the UIpartialproof ↗
Export all of my data in open formats and leavepartialproof ↗
Every expense carries a full audit trail — edits, approvals, policy checks — that survives an external auditpartialproof ↗
Codify our expense policy — limits by category, role, and context — so in-policy expenses auto-approve and only exceptions reach a humanfullproof ↗
Receipts match to card transactions automatically — with e-receipts pulled from integrations — and I get nudged only when one is genuinely missingpartialproof ↗
Submit an out-of-pocket expense and get reimbursed by direct deposit in days, tracked from submission to payoutfullproof ↗
Allocate budgets to teams and projects and have card limits and approvals actually enforce themfullproof ↗
See company spend in real time — by team, category, and merchant — the day it happens, not when statements landfullproof ↗
A trip's expenses — bookings, cards, receipts — collect themselves into one itinerary-linked reportpartialproof ↗
Claims outside our story set (2)
Real capability claims found in Ramp’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.
“Offers Agent Cards designed for a single AI agent's checkout use”
source ↗“Lets users edit and submit expense entries via SMS, Slack, or Microsoft Teams”
source ↗
Business model
Free core plan is interchange-funded with unlimited cards; Ramp Plus adds AI-driven automation at $15/user/mo plus a platform fee; Enterprise is custom.
pricing ↗Score trend
How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.
Try Experimental
Run it in the microterminal →Recorded agent sessions — and a live MCP handshake where the vendor ships one.
Flag
⚑ Flag a verdictThink a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.
For agents
