Try itExperimental
See what an agent can do with Navan 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 -sL https://developer.navan.com/llms.txt | head -4recorded session — replayed, not liveVerified integrations
No integration evidence found in our corpus for this product yet — that means none was found, never that it doesn’t integrate.
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 Navan 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
—–
Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
~7/10
Run multiple legal entities and currencies in one account with consolidated reporting and per-entity books
—–
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
✓8/10
unlocks → Webhooks · Machine-readable spec · Versioning policy · API sandbox · Official CLI · Full data export
Subscribe to events via webhooks
—0/10
Build against official SDKs
~5/10
Issue scoped/least-privilege API credentials for an agent
~3/10
unlocks → Autonomous automations
Connect an agent via an official MCP server
✓8/10
Download a machine-readable API spec (OpenAPI or equivalent)
—0/10
Rely on versioned APIs with a documented deprecation policy
—0/10
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
✓7/10
unlocks → MCP client
Operate the product with natural-language commands
✓7/10
unlocks → Autonomous automations
Plug MCP servers into this product so it can use their tools
—0/10
Get AI-generated insights and suggestions from my data inside the product
✓8/10
Set up automations that run autonomously in the background
—0/10
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
—0/10
Issue physical and virtual corporate cards to the team in minutes, each with its own spend limit
—0/10
Create single-vendor virtual cards for SaaS subscriptions and procurement so one compromised vendor never exposes shared credit
—0/10
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
~5/10
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
—0/10
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
~2/10
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
~5/10
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
—–
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
—0/10
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 | 8/10 | 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 | 8/10 | 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 | full | 7/10 | Cclaimed | |
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 | none | 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 | |
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 | 8/10 | Cclaimed | |
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 | 7/10 | Tprobed | |
Build against official SDKs G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | partial | 5/10 | 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 | 5/10 | Cclaimed | |
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 | partial | 3/10 | 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 | 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 | 0/10 | ||
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 | none | 0/10 | ||
Subscribe to events via webhooks G Agent access | ai-native user | Agenticness — how well agents can access and operate the productAgenticness | 2 | none | 0/10 | ||
Use an official CLI G Agent access | 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 | |
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 | 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 | 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 | 5/10 | Cclaimed | |
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 | partial | 5/10 | 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 | |
Define rules that trigger actions automatically on events G | ai-native user | Automation depth — how much of the product can run unattendedAutomation depth | 3 | partial | 4/10 | 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 | partial | 3/10 | 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 | none | 0/10 | ||
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 | none | 0/10 | ||
Export all of my data in open formats and leave G | ai-native user | Openness — open source, data portability, and self-hosting storiesOpenness | 3 | none | untested | none yet | |
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 | |
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 | none | untested | none yet | |
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 | 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 | partial | 7/10 | Cclaimed | |
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 | partial | 6/10 | Tprobed | |
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 | partial | 5/10 | 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 | 5/10 | Tprobed | |
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 | 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 | |
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 | 2/10 | 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 | none | 0/10 | ||
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 | none | 0/10 | ||
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 | none | 0/10 | ||
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 | none | 0/10 | ||
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 | |
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 | 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 | n/a | untested | none yet | |
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 | none | untested | none yet | |
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 | 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 | 6/10 | 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 42 stories with headroom
What would move Navan’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.
Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools
nonemoves agent-readyimpact 45
Missing: any documentation of Navan's AI features connecting to external MCP servers, any tool/plugin ecosystem for consuming outside MCP tools, and any hands-on confirmation of such client-side behavior.
Accounting close — stories about accounting close in this arenaTransactions sync to QuickBooks, NetSuite, or Xero with GL account, class, and department mappings I control
nonemoves PA Scoreimpact 30
The evidence pack contains no mention of QuickBooks, NetSuite, Xero, or any accounting-system sync, nor GL account/class/department mapping controls — it only covers Navan's API/MCP for expense querying, travel booking, and rewards.
Cards controls — stories about cards controls in this arenaRestrict cards by category, merchant, and amount — and the platform auto-locks or declines out-of-policy spend at the point of sale
nonemoves PA Scoreimpact 30
Missing: explicit documentation of category/merchant/amount-based card controls, missing for 10: evidence of real-time auto-lock or point-of-sale decline enforcement.
Cards controls — stories about cards controls in this arenaIssue physical and virtual corporate cards to the team in minutes, each with its own spend limit
nonemoves PA Scoreimpact 30
Missing: any documentation of card issuance workflow, virtual card creation, spend-limit configuration, or time-to-issue claims.
Openness — open source, data portability, and self-hosting storiesExport all of my data in open formats and leave
nonemoves PA Scoreimpact 30
Missing: bulk export functionality, open-format data dumps, documented data portability/exit process.
Privacy posture — data-handling and privacy storiesPrevent my data from being used to train AI models
nonemoves PA Scoreimpact 30
Missing: any explicit statement on AI/model training data usage, opt-out settings, or data retention/privacy commitments.
Agenticness — how well agents can access and operate the productSet up automations that run autonomously in the background
nonemoves Built-in AIimpact 30
Evidence shows Navan's AI features (MCP, Ava) are query/chat-based tools that answer questions or analyze spend on request, and Navan Edge explicitly states it 'will always ask for your explicit confirmation before booking, changing, or canceling any trip,' which is the opposite of autonomous background automation.
Agenticness — how well agents can access and operate the productUse an official CLI
nonemoves agent-readyimpact 30
The axis applies to this product kind (peer products hold positive or none verdicts on this story), so lack of evidence for an applicable capability is "none", never "na".
Showing the top 8 of 42 — 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 map8 surfaces · 26 covered stories
Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.
MCP docs17 stories
- Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
- Point an agent at llms.txt or agent-oriented docs
- 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
- Build against official SDKs
- Get AI-generated insights and suggestions from my data 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
- An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for review
- Do everything through the API that I can do in the UI
- 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
- 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
developer.navan.com16 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
- Drive the product through a documented public API
- Issue scoped/least-privilege API credentials for an agent
- Build against official SDKs
- Operate the product with natural-language commands
- 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
- 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
- Do everything through the API that I can do in the UI
- 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
- See company spend in real time — by team, category, and merchant — the day it happens, not when statements land
Pricing docs13 stories
- Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
- 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
- Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokens
- Do everything through the API that I can do in the UI
- 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
- 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
- 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
API reference10 stories
- Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology dig
- Run the product headlessly / in CI for automation
- Drive the product through a documented public API
- Build against official SDKs
- 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
- Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokens
- Do everything through the API that I can do in the UI
- 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
llms.txt4 stories
Blog docs4 stories
- Get AI-generated insights and suggestions from my data inside the product
- Delegate tasks to a built-in AI assistant inside the product
- Operate the product with natural-language commands
- An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happens
Product docs4 stories
Probe proofs — replayable recordings from the probe harnessProbe proofs
Replayable recordings from our probe harness — see the Prove-It protocol to submit one.
$curl -sL https://developer.navan.com/llms.txt | head -4reproduced$ curl -sL https://developer.navan.com/llms.txt | head -4 # Navan Developer Portal > Connect AI assistants to Navan travel and expense data via the Model Context Protocol (MCP), and integrate programmatically with the Navan Expense API.
$curl -s -X POST https://mcp.navan.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # Navan's hosted MCP server, keyless → Bearer challengereproduced$ curl -s -X POST https://mcp.navan.com/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>' # Navan's hosted MCP server, [redacted]less → Bearer challenge
{"jsonrpc":"2.0","id":0,"error":{"code":-32001,"message":"Missing Bearer [redacted]"}}
Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence
2 of 9 testable claims verified · 2 contradicted → integrity 0/100
19 distinct capability claims found in Navan’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.
2
Verified
5
Unverified
2
Contradicted
19
Undersold
Verified (2)
“Connect AI assistants (Claude, Cursor, ChatGPT, Codex, OpenClaw) to Navan data via an official MCP server”
“Query Navan spend and travel data using natural language through MCP”
Operate the product with natural-language commandsfullproof ↗
Unverified (12)
“API supports OAuth 2.0 client-credentials auth with retrieval/update endpoints across expenses, custom fields, receipts, and webhooks”
Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokensfullproof ↗
“Single API to retrieve and update card transactions, manual expenses, payroll, repayments, fees, adjustments, rebates, and disputes”
Pull transactions, expenses, and receipts through a documented REST API with OAuth and scoped tokensfullproof ↗
“Ask an AI assistant which transactions violate company policy (e.g. rideshare policy)”
An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happenspartialproof ↗
“Manage expenses and issue reimbursements to employees”
Submit an out-of-pocket expense and get reimbursed by direct deposit in days, tracked from submission to payoutpartialproof ↗
“Access global travel inventory with exclusive negotiated rates”
Book flights and hotels in-platform with travel policy applied at booking time, not expensed and argued about laterfullproof ↗
“Self-serve trip changes plus 24/7 human travel support agents”
Book flights and hotels in-platform with travel policy applied at booking time, not expensed and argued about laterfullproof ↗
“Shows a 'price to beat' smart target for hotel searches based on location, date, and demand, within policy”
Get AI-generated insights and suggestions from my data inside the productfullproof ↗
“Personalizes travel results using chat preferences, booking history, and connected loyalty programs”
Get AI-generated insights and suggestions from my data inside the productfullproof ↗
“Analyzes travel spend and generates suggestions to save money”
Get AI-generated insights and suggestions from my data inside the productfullproof ↗
“Summarizes travel spend by month and by category”
Get AI-generated insights and suggestions from my data inside the productfullproof ↗
“Compares travel spend against company policy”
An AI assistant enforces policy conversationally — chasing missing receipts, explaining declines, and answering "can I expense this?" before the spend happenspartialproof ↗
“Predicts future travel spend habits”
Get AI-generated insights and suggestions from my data inside the productfullproof ↗
Contradicted (2)
“API supports OAuth 2.0 client-credentials auth with retrieval/update endpoints across expenses, custom fields, receipts, and webhooks”
“View card management details — active/inactive status, number of cards per user, and other card info”
Issue and manage cards programmatically — create a card with a limit, lock it, update controls — via the public APInoneproof ↗
Undersold (19)
Spend is coded as it happens — merchant, category, memo, receipt — so month-end close is a review, not an archaeology digpartialproof ↗
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 ↗
Issue scoped/least-privilege API credentials for an agentpartialproof ↗
Delegate tasks to a built-in AI assistant inside the productfullproof ↗
AI codes and audits expenses for me — reading receipts, suggesting categories and memos, and catching duplicates or fraudpartialproof ↗
Perform bulk operations across many items at oncepartialproof ↗
Define rules that trigger actions automatically on eventspartialproof ↗
An agent can pull uncoded transactions via API or MCP, propose categorizations and policy flags, and push clean coding back for reviewpartialproof ↗
Do everything through the API that I can do in the UIpartialproof ↗
Build multi-step approval chains — manager, budget owner, finance — with delegation and escalation when approvers sit on requestspartialproof ↗
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 humanpartialproof ↗
Snap a photo or forward an email and the platform OCRs the receipt and files it against the right transactionpartialproof ↗
Allocate budgets to teams and projects and have card limits and approvals actually enforce thempartialproof ↗
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 (4)
Real capability claims found in Navan’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.
“Connect existing corporate or business credit cards to the platform”
source ↗“Earn Navan Rewards that can be applied to personal hotel stays booked on the platform”
source ↗“24/7 access to human travel agents via chat or phone”
source ↗“Always requires explicit user confirmation before booking, changing, or canceling a trip”
source ↗
Business model
Travel booking is free with unlimited trips; expense is free for the first 5 users then $15/user/mo; Navan Enterprise is custom — travel supplier commissions fund the free tier.
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
