plans + payments
Revenue intelligence
Stripe customers, plans, renewals, revenue, and payment count in one margin view.
Grow fast without losing track of margins
Businesses are scaling faster than spreadsheets, dashboards, and weekly reviews can keep up. Traket connects revenue, AI usage, and vendor spend so teams can grow quickly without blindly leaking revenue or discovering weak margins too late.
Connect a source in minutes. No prompts or outputs are ever stored.
Connects with
StripeOpenAIPlaidUsage CSVServer SDK
$0 saved so far.
Expanding margin
Clean growth compounds
Revenue growth
Growth gets cleaner
Production spend
Growth slows with control
Gross margin, mo. 1261%
Why it matters
Businesses grow faster than their margin systems.
Growth can hide expensive details. A team may add customers, launch AI features, change plans, and stack new vendors before anyone has a clean answer for what each account costs to serve. Traket is built to make that answer visible from the beginning.
Revenue spreads out
New plans, usage, invoices, discounts, and customer segments appear before the margin model catches up.
Costs move underneath
AI usage, vendors, support volume, and transaction fees change while teams are still looking at top-line growth.
Decisions need owners
Traket turns messy source data into pricing, product, finance, and operations actions before losses become normal.
Developers
Implementation should feel like a setup task, not a rebuild.
Use the Traket SDK directly or let project skills wire the tracking into known provider calls. The goal is simple: capture live margin data without storing prompts, outputs, files, full provider responses, or secrets.
The project skill reads the instrumentation config, skips excluded files, and wires usage tracking where the app already calls providers.
1Pick the routes or jobs to instrument
2Run the Traket SDK skill
3Review the patch and ship
Privacy contract
No prompt or response capture.
Unit model
Tokens, requests, costs, and diagnostics.
Source priority
Live SDK rows outrank CSV history.
Attribution
Customer, feature, model, and environment.
Server SDK
Request-level metering
import { createMargins } from "@traket/sdk";
const margins = createMargins({
endpoint: process.env.TRAKET_ENDPOINT,
writeKey: process.env.TRAKET_WRITE_KEY!,
});
await margins.openai.track(
() => openai.responses.create({ model, input }),
{
externalCustomerId: customer.id,
feature: "support_reply",
promptType: "support",
},
);Platform
Use one module or wire the whole margin stack.
The product reads like a developer platform because margin work is systems work. Connect sources, normalize evidence, and keep decisions close to the rows behind them.
tokens + cost
AI usage economics
Live SDK metering and CSV backfills with source quality kept visible.
identity match
Attribution graph
Customer IDs, emails, workspaces, and Stripe identities resolved into one record.
Plaid evidence
Vendor spend
Vendor transaction evidence, renewal windows, and subscription cleanup signals.
no filler rows
Forecast gate
Readiness checks prevent forecasts from appearing before enough real history exists.
SDK-first
Developer setup
Server SDK docs and key management built for production instrumentation.
Margin signals
The places growth hides margin loss.
No vanity percentages here. Traket focuses on the evidence teams need to find leaks, assign owners, and keep revenue from drifting away as the business expands.
Revenue quality
Customer-level margin
Tie every usage event back to the customer, feature, and plan that created it.
Connect evidenceCreate action
Usage economics
AI cost drift
Spot AI features that look popular but quietly cost more than they return.
Connect evidenceCreate action
Margin risk
Pricing leaks
Find pricing, discount, and packaging gaps before they become normal.
Connect evidenceCreate action
Attribution
Identity resolution
Connect Stripe, app IDs, emails, and workspace metadata into one account view.
Connect evidenceCreate action
Spend control
Vendor creep
Track recurring tools and renewals that are easy to miss while the team grows.
Connect evidenceCreate action
Owner workflow
Action routing
Route the fix to pricing, product, finance, or operations with the evidence attached.
Connect evidenceCreate action
Architecture
Source rows to owner action
Stripe
primaryCustomers, plans, payments, renewals.
Server SDK
liveRequest IDs, model usage, duration, cost.
Usage CSV
historyOpenAI exports and historical backfills.
Plaid
evidenceBank and card transaction evidence.
Analysis
reviewReadiness, leak detection, and owner routing.
Start with the row you have
Build a margin system one source at a time.
Connect Stripe first, backfill AI history, then add the SDK when production usage is ready. Traket keeps the gaps visible while the system gets better.
OwnerNext action
pricingStarter tier AI COGS above targetowner review
productSupport feature high cached-token wasteinvestigate
financeFive vendors lack renewal evidencecollect proof
opsCSV-only rows need SDK migrationinstrument
FAQ
Questions teams ask before connecting.
Traket is built to be honest about data quality and careful with what it stores. Here is what that means in practice.
Does Traket store my prompts or model outputs?
No. The SDK and CSV imports never store prompts, messages, outputs, images, files, tool arguments, provider headers, API keys, or full provider responses. Traket keeps mapped units, costs, diagnostics, and allowlisted metadata only.
What do I need to connect to get started?
Connect Stripe first to bring in customers, plans, and revenue. Backfill historical AI spend from provider CSV exports, then add the server SDK when production usage is ready. Each source improves the picture without blocking the others.
How does Traket keep the numbers trustworthy?
Live SDK request-level data outranks CSV history, and every metric stays labeled by source quality. Traket gates forecasts behind readiness checks so you never see filler numbers before enough real history exists.
Can it attribute AI cost to individual customers?
Traket resolves Stripe identities, app customer IDs, emails, and workspace metadata into one account record, so usage events tie back to the customer, feature, and plan that created them.