Stripe

Most mid-market companies already use Stripe. What they usually do not have is the layer of automation that turns Stripe from a payment processor into a revenue operations engine. That gap is where money quietly leaks: failed cards that never get retried smartly, churn signals that never reach the CRM, finance reports that live in three different spreadsheets, fraud rules nobody has touched since the integration went live.

What Stripe Does

Stripe is the payments and billing infrastructure layer for a large share of internet businesses. It started as card processing and now covers most of what a finance and revenue team needs to move money.

• Payments. Card processing, wallets, bank debits, and local payment methods across most countries, with one API and one settlement flow.
• Billing. Subscription management, usage-based billing, proration, trials, coupons, and revenue recognition built around recurring SaaS motions.
• Invoicing. One-off and recurring invoices with hosted payment pages, automatic reminders, and Stripe-managed tax handling.
• Connect. The platform layer for marketplaces and SaaS that pay out third parties, with KYC, account onboarding, and split payments handled.
• Tax. Automatic sales tax and VAT calculation, registration tracking, and filing in supported jurisdictions, so finance is not stitching together TaxJar plus spreadsheets.
• Radar. Machine-learning fraud detection running on Stripe's full network, with custom rules teams can tune to their dispute pattern.
• Sigma and Data Pipeline. SQL access to your Stripe data inside the dashboard, plus syncing the full dataset into Snowflake, Redshift, or BigQuery.

Stripe's AI

Stripe has been embedding machine learning into the core platform for years rather than bolting on a chatbot. Radar's fraud engine, Adaptive Acceptance for retrying declined charges against an issuer-specific model, Smart Disputes for chargeback evidence, and Optimised Checkout Suite for personalised payment method ordering all run on models trained across Stripe's network. The practical effect for an operator: authorisation rates tend to improve and disputes get cheaper without a single config change, but the real lift comes when you tune the rules and feedback loops around your own data.

Automations We Build with Stripe

Stripe is the spine. The automations are what determine whether you recover dunning revenue, catch churn early, and close the books on day three of the month instead of day eight. These are the plays we run for mid-market clients.

• Smart dunning. Card-decline reason routes the customer into a different retry cadence and email sequence. Hard declines go to account owners; soft declines stay automated. We typically use n8n or Temporal as the orchestration layer.
• Churn signals into CRM. Failed payments, plan downgrades, and unusual usage drops fire into HubSpot or Salesforce as deal-risk fields and CSM tasks, not silent webhook noise.
• Stripe to ledger sync. Charges, refunds, fees, and disputes mapped to the correct accounts in QuickBooks, Xero, or NetSuite with full audit trail. Finance stops manually exporting CSVs.
• Radar rule tuning. Custom rules built around your geography, ticket size, and dispute pattern, with a Slack review channel for the borderline 3DS decisions instead of auto-block.
• Revenue recognition automation. Invoices, prorations, and refunds flow into a clean ARR/MRR/NRR dashboard pulling from Sigma plus the CRM, refreshed daily.
• Connect onboarding flows. KYC, payout schedules, and platform fee logic for marketplaces and B2B SaaS that pay out third parties, with status events wired into ops dashboards.
• Customer self-service portal. Subscription upgrades, downgrades, payment method updates, and invoice history behind your auth, so support stops fielding billing tickets.

Why Teams Choose Stripe

• One API for the entire money movement stack. Payments, subscriptions, invoicing, payouts, tax, and fraud sit behind the same SDK instead of four separate vendors.
• Developer ergonomics that nobody else matches. The docs, the dashboard, the test mode, and the webhook tooling are the reason engineering teams stop fighting the integration on day one.
• Authorisation rates that lift with the network. Adaptive Acceptance and Optimised Checkout typically improve approval rates by a few percentage points, which on a real revenue base compounds into material money.
• Global coverage without a separate provider per region. 195+ countries, 135+ currencies, local payment methods from iDEAL to Pix supported in the same flow.
• Data access that finance and analytics can actually use. Sigma for in-dashboard SQL, Data Pipeline for warehouse sync, plus a public API that exposes essentially everything.

Stripe's headline rate in Europe starts at 1.5% + €0.25 for standard EEA cards, with international cards landing at 3.25% + €0.25, plus add-ons for Tax (from €80/month or 0.5% per transaction), Sigma (from €9/month annual), and Radar enhancements. Native integrations exist for essentially every CRM, accounting, and analytics tool that matters. HubSpot, Salesforce, QuickBooks, Xero, NetSuite, Snowflake, Segment, and several thousand more. That's the build we do: not the Stripe install, but the automation layer on top that turns it into a finance and revenue ops engine.