Carrot Labs
SuperPenguin is AI spend intelligence that attributes every AI dollar by customer, feature, team, and merged pull request.
If your AI spend crosses several providers and you genuinely cannot say which customer or feature caused it, SuperPenguin answers that question harder than provider dashboards can. Coding ROI is the part most cost tools miss - pricing merged pull requests across Cursor, Claude Code and Codex gives engineering leadership a number they can take into a headcount conversation. The catch: attribution only appears once someone instruments calls or installs the Mac app, and Free caps PR attribution at
Verified 12m ago · liveness 80/100 · cite: rightaichoice.com/tools/carrot-labs
- Engineering leaders who need AI spend tied to merged pull requests, not seat counts
- Finance teams reconciling multi-provider AI invoices and chasing billing errors
- Product managers measuring what a specific customer or feature costs to serve
- Platform teams wanting cost-per-customer attribution without moving traffic to a gateway
- Teams shopping for an LLM gateway or proxy — SuperPenguin routes no traffic
- Anyone who needs prompt-level debugging; content capture is opt-in, sampled, and text-only
- Solo builders with one provider and a low bill, where the native dashboard is enough
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Skip SuperPenguin if you want a gateway or proxy that routes and rate-limits traffic, or if prompt-level debugging is the goal — SuperPenguin sits outside the request path and stores cost metadata only by default.
Managed spend is capped by plan, so a month that pushes past $2K (Free), $5K (Growth) or $20K (Pro) means moving up a tier rather than paying an overage rate.
At $30/mo for up to $5K managed spend and $200/mo for up to $20K, SuperPenguin costs roughly 0.6% of the AI spend it watches at the Pro ceiling. That undercuts per-seat observability suites when a finance team wants broad dashboard access, but it isn't aimed at a solo builder on one provider, where the native dashboard is free. Above $20K monthly AI spend you're on a custom deal.
In short
Carrot Labs — SuperPenguin is AI spend intelligence that attributes every AI dollar by customer, feature, team, and merged pull request. Best for Engineering leaders who need AI spend tied to merged pull requests, not seat counts, Finance teams reconciling multi-provider AI invoices and chasing billing errors, Product managers measuring what a specific customer or feature costs to serve. Free to start; paid plans from $30/mo.
What's new in Carrot Labs
Checked 5 days agoAcross the latest 5 updates: 4 feature updates and 1 changelog entry.
v0.29.0 — Compare AI coding costs across people and teams, with easier organization setup
Adds an AI coding cost comparison by person and team with a toggle between actual cost and usage value plus CSV download, and lets you import organization structure and reporting lines from a CSV or pasted spreadsheet cells.
v0.28.0 — Track agent workflows and Cohere usage, with clearer live spending and team setup
Tracks model usage across agent workflows and attributes each run to its customer, team and feature; adds Cohere chat, embeddings and reranking including supported AWS Bedrock calls; API Usage gains live spending charts.
v0.27.0 — Easier-to-read PR attribution and more accurate model pricing
PR attribution now shows how many requests are on record per pull request and the value of each, replaces anonymous IDs with teammate names, and corrects pricing for Gemini models used through AWS Bedrock and more Cursor model names.
v0.26.0 — Setup is easier to finish, and coding spend is easier to understand
A refreshed setup flow makes it easier to connect tools, invite teammates and choose a plan, with a 14-day trial for eligible paid plans; also fixes OpenRouter spend reporting for cached tokens and usage with your own provider keys.
v0.24.0 — Connect coding tools even when the emails do not match
Lets you link Cursor, Claude Code and Codex to SuperPenguin when those accounts use a different email than your login, keeps API setup steps in the onboarding checklist, and adds AI help next to setup tasks.
What people actually say about Carrot Labs — is it worth it?
We scanned public community sources for Carrot Labs on Aug 31, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Our own analysis of that scan says the posts were off-subject. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Carrot Labs? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Per-request AI cost attribution in dollars via Python and TypeScript SDKs
- Tag each call with customer, feature, team, environment, or prompt version
- Define custom cost dimensions with no cardinality caps
- One View: every provider bill rolled into a single total
- Coding ROI: cost per merged GitHub pull request across Cursor, Claude Code, and Codex
- PR attribution showing request counts and value per pull request
- AI coding cost comparison by person and team, exportable as CSV
- Organization structure and reporting lines import from CSV or pasted spreadsheet
- Free Mac app showing live agent spend in the menu bar
- Agent workflow tracking: attribute each run to customer, team, and feature
- Cohere chat, embeddings, and reranking tracking, including AWS Bedrock calls
- Spend alerts to Slack, Discord, or email within minutes of a breach
- Daily thresholds, spike detection versus yesterday, and monthly budget caps
- End-of-month spend forecast and invoice reconciliation
- Custom model pricing for provider service tiers and regional Bedrock or Azure rates
About Carrot Labs
SuperPenguin, built by Carrot Labs, attacks a specific finance problem: your AI providers each bill you on their own project and API-key structure, so nobody can tell you which customer or feature caused the total. Connect provider admin keys and One View rolls OpenAI, Anthropic, Gemini, Cursor, Fireworks AI, AWS Bedrock, Azure, Deepgram, ElevenLabs, Together AI, Modal, OpenRouter, Vercel AI Gateway, LiteLLM and Cohere into one figure. The vendor's own illustration makes the gap concrete: on a $22,478 bill, only $15,658 maps to a named customer. Three entry points keep setup short. The Python or TypeScript SDK prices each request in dollars and tags it with customer id, feature, team, environment or prompt version, with no cardinality cap on the dimensions you invent. Connect GitHub and have engineers install the free Mac app, which syncs the per-session detail Cursor, Claude Code and Codex keep locally; Coding ROI then prices each merged pull request and rolls spend up by repository. The v0.29.0 release on October 12, 2026 added a per-person and per-team AI coding cost comparison with CSV export and organization-structure import from a spreadsheet. v0.28.0 on October 6, 2026 brought agent workflow attribution and Cohere tracking including calls routed through AWS Bedrock. Alerts fire in Slack, Discord or email minutes after a breach - daily thresholds, a spike detector against yesterday, monthly caps. Pro and Enterprise add end-of-month forecast and invoice reconciliation that flags hidden charges and billing errors. Growth and up unlock 90-day backfill and custom model pricing for provider service tiers and regional Bedrock or Azure rates. Architecturally it is not a proxy. Calls go straight to the provider and telemetry ships after the response returns; Carrot Labs puts overhead under 10ms non-streaming and under 5ms to first token on streams. Only cost metadata is stored by default, with prompt capture opt-in on Pro. Pricing scales on managed AI spend, not
Behind the Verdict
We'd reach for SuperPenguin the moment a second AI provider lands on the card statement and finance starts asking which customer ate the margin. Provider dashboards stop at their own wall, by their own project and API keys. SuperPenguin's whole reason to exist is stitching those walls together and slicing the total by dimensions you name yourself. The design choice that matters most: it is not in your request path. No proxy, no gateway migration, no re-plumbing your stack. Telemetry ships after the response returns, which Carrot Labs measures at under 10ms non-streaming and under 5ms to first token when streaming. Platform teams who refuse to put a middleman in front of production traffic get attribution without that trade. Coding ROI is where it earns its keep for engineering leadership. Cursor, Claude Code and Codex all keep per-session detail locally, so the free Mac app is genuinely load-bearing - connect GitHub, have engineers install it, and merged pull requests get a dollar figure. The v0.29.0 person-and-team comparison with CSV export makes that usable in a budget meeting rather than a curiosity. Where it bites: attribution is a homework problem. Skip the SDK tags or the Mac app and per-customer numbers stay blank. And plan limits are real - Free covers 3 merged PRs total, Growth caps PR attribution at the latest 20 merged PRs this month, so a team merging daily will be pushed to Pro at $200/mo fast. The closest alternative depends on what you actually need. If you want a gateway that routes and meters traffic, look at LiteLLM or OpenRouter - SuperPenguin sits alongside them, not instead of them. If you want prompt-level debugging or an observability platform, this is not it: content capture is opt-in, sampled and text-only. Pass if you run one provider on
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Real-world workflow fit
Concrete scenarios for the personas Carrot Labs actually fits — and what changes day-one when you adopt it.
Connect each provider's admin key so One View pulls OpenAI, Anthropic, Gemini and Bedrock into one total, then reconcile that total against the invoices that arrive at month end.
Outcome: Hidden charges and billing errors get flagged against the invoice, and the team argues over one number instead of four dashboards.
Connect GitHub, email the free Mac app to engineers so Cursor, Claude Code and Codex session detail syncs, then open Coding ROI to price merged pull requests by repository.
Outcome: Each merged PR carries a dollar figure, and v0.29.0's people-and-teams view exports as CSV for the headcount and tooling conversation.
Wrap the provider client with the Python SDK and pass customer id and feature in the metadata on each call, then set a daily alert threshold to Slack.
Outcome: Feature-level ROI becomes a real number, and a runaway loop pages the team in minutes rather than surfacing on next month's invoice.
Use Cases
- Track monthly AI spend across OpenAI, Anthropic, Gemini, Bedrock, and Cursor in one dashboard total.
- Attribute each API call to a specific customer and feature to measure feature-level ROI in dollars.
- Reconcile tracked spend against provider invoices to catch billing errors and hidden charges.
- Set daily thresholds, spike detection, or monthly budget caps with Slack, Discord, or email alerts.
- Measure cost per merged pull request by linking Cursor, Claude Code, and Codex usage with GitHub PRs.
- Compare AI coding costs across individual engineers and teams, then export the comparison as CSV.
- Attribute agent workflow runs to the customer, team, and feature that triggered them.
- Let Claude Code, Cursor, or ChatGPT query organization spend through an OAuth-authenticated MCP connection.
Models Under the Hood
as of 2026-10-18
Limitations
- Attribution depends on instrumentation: per-customer, per-feature, and per-PR costs only appear once provider clients are wrapped with the Python or TypeScript SDK and tagged with metadata.
- Coding ROI per merged pull request requires GitHub plus the free Mac app, and Mac-app seats for Coding ROI are capped at 1 (Free), 3 (Growth), or 5 (Pro) before Enterprise.
- Managed spend is capped by tier — Free at $2K, Growth at $5K, and Pro at $20K per month — and 90-day historical backfill, custom model pricing, and end-of-month forecast are reserved for Growth and above.
- PR attribution on Growth covers only the latest 20 merged PRs in the month (UTC), against 3 merged PRs total on Free.
- The product is a cost-attribution and reporting layer; prompt-level debugging is out of scope, as content capture is opt-in, sampled, and text-only with images and audio stripped.
as of 2026-10-13
Verification history
We have re-verified Carrot Labs 10 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
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Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Carrot Labs tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
One engineer or a solo builder with a couple of providers and under $2K monthly AI spend who wants to see whether attribution fits before paying.
What this tier adds
Free entry point: $0/mo, up to $2K managed spend, 1 workspace member, Coding ROI for 1 person, and 3 merged PRs of attribution total with no monthly reset.
Growth
$30/mo
Ideal for
A small team shipping AI with roughly $2K-$5K in monthly provider spend that needs alerts and a comparison point against last month.
What this tier adds
Adds $5K managed spend, 3 workspace members, Coding ROI for 3 people, the latest 20 merged PRs this month, Slack/email/Discord alerts, 90-day backfill and custom model pricing.
Pro
$200/mo
Ideal for
A production team at $5K-$20K monthly AI spend where unlimited PR attribution and a month-end forecast are the deciding factors.
What this tier adds
Adds $20K managed spend, 10 workspace members, Coding ROI for 5 people, unlimited PR attribution, end-of-month forecast, and opt-in prompt and outcome capture.
Enterprise
Custom
Ideal for
Organizations above $20K monthly managed spend, or teams needing unlimited workspace members and unlimited Coding ROI seats.
What this tier adds
Adds unlimited managed spend, unlimited workspace members, Coding ROI for unlimited people, and custom onboarding via sales over an Enterprise agreement.
Where the pricing makes sense
The company stage and team size where Carrot Labs's pricing actually pencils out — and where peers do it cheaper.
At $30/mo for up to $5K managed spend and $200/mo for up to $20K, SuperPenguin costs roughly 0.6% of the AI spend it watches at the Pro ceiling. That undercuts per-seat observability suites when a finance team wants broad dashboard access, but it isn't aimed at a solo builder on one provider, where the native dashboard is free. Above $20K monthly AI spend you're on a custom deal.
Setup time & first value
How long it actually takes to get something useful out of Carrot Labs — broken out by persona, not the marketing-page minute.
One View is the fastest path: connect a provider admin key and see a total in minutes. SDK attribution takes an hour or two of engineering time to wrap clients and pass tags, with the first attributed spend visible almost immediately. Coding ROI is the slowest, since it depends on GitHub access plus each engineer installing the Mac app and linking their Cursor, Claude Code or Codex account.
Switching to or from Carrot Labs
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From spreadsheets: import your organization structure and reporting lines from a CSV or pasted spreadsheet cells, then tag SDK calls with the same customer and team names.
- →From a provider dashboard: connect the provider's admin key to One View so the existing bill keeps flowing while you layer attribution on top.
- →From a gateway-only view: price traffic from OpenRouter, Vercel AI Gateway, or LiteLLM using each platform's own per-request charge rather than replacing the gateway.
- →From manual PR cost tracking: connect GitHub and install the Mac app so Coding ROI prices merged pull requests automatically instead of by hand.
- ↗To an LLM gateway or proxy: if you need routing, failover, or rate limiting in the request path, SuperPenguin was never in that path and a gateway takes its place.
- ↗To a full observability platform: if you need prompt-level traces rather than sampled opt-in capture, move to a tool built around request debugging.
- ↗To native provider dashboards: for a single-provider, low-spend setup, the provider's own dashboard may be sufficient and requires no instrumentation.
- ↗To spreadsheets: cost metadata can be pulled via the Agent API or CLI and exported, so you can rebuild reporting outside the product if you leave.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Carrot Labs”, and we withheld 6: 6 could not be judged, because “Carrot Labs” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Carrot Labs.
Official links
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Featured Head-to-Head Comparisons
Carrot Labs vs Bitsgap
If you're an engineering leader drowning in AI invoices and need per-customer cost breakdowns, Carrot Labs is your only answer. If you're a crypto beginner wanting automated trading bots with AI guidance, Bitsgap's 30-day demo and multi-exchange support make it a no-brainer. They solve completely different problems—choose based on whether you manage AI costs or crypto trades.
Carrot Labs vs Geologicai
If you're in critical minerals mining needing rapid, integrated core scanning and AI logging, GeologicAI is the only end-to-end platform that can deliver sub-48-hour turnaround and 400% project acceleration. For any organization spending on LLM APIs—especially those needing per-request attribution per customer, feature, or team—Carrot Labs' SuperPenguin (with its free tier up to $2K) is the cost intelligence solution. They serve completely different buyers; choose based on whether your problem is rocks or tokens.
Carrot Labs vs Screenplayiq
If you need to control AI spend across providers and teams with per-request granularity, Carrot Labs is essential. ScreenplayIQ is a niche script analysis tool for film professionals — great if you're a screenwriter, but irrelevant for most AI users. Pick based on your job: engineering leader → Carrot Labs; screenwriter/producer → ScreenplayIQ.
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Chattermill
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