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Stripe
10 posts about Stripe. Every summary links to the original.
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Stripe Data Pipeline now syncs real-time Stripe data to Lakebase Postgres
Stripe Data Pipeline now supports real-time sync to Postgres, with Databricks Lakebase as a supported destination. Stripe streams real-time API data into Lakebase and manages the sync end to end, eliminating the need for custom integrations with APIs or webhooks that require handlers, retry logic, and reconciliation processes for missed or out-of-order events. One Stripe account can feed two Databricks destinations: Unity Catalog for analytics and AI workloads, and Lakebase for applications. With real-time sync, payment, customer, subscription, refund, and payout data updates arrive in Lakebase within seconds, enabling applications to control product and feature access based on subscription status, keep billing and account details up to date without calling the Stripe API on every page load, and provide real-time financial visibility with dashboards showing daily sales volume, refunds, and payouts as they happen. The feature is available in public preview and free to get started.
Sync real-time Stripe data to Supabase with Stripe Data Pipeline
Stripe’s Data Pipeline now adds Postgres as a destination, enabling developers to sync Stripe data directly into their Supabase project without maintaining webhooks or working around API rate limits. Setup occurs entirely in the Stripe Dashboard: under Reporting, Data management, users select Data Pipeline, choose Postgres and Supabase, and authorize the connection. Stripe backfills historical records and continuously syncs charges, refunds, disputes, customers, subscriptions, and invoices into a dedicated stripe_sdp schema in the user’s Postgres database. A dedicated stripe_sdp role with scoped permissions, JWT direct connections using short-lived tokens, and enforced SSL ensure the database password is never exposed to Stripe. Developers can then query the synced tables with standard SQL, join them with application data, and implement features like MRR calculations, churn analysis, or subscription-based feature gating without extra API calls.
Run recurring jobs on Stripe without a cron server
Stripe Workflows now supports recurring schedule triggers, enabling automated tasks like notifying teams about past-due subscriptions without external cron servers. Users set schedules in the Dashboard, and Stripe runs the workflow at each scheduled time, following the local clock and handling daylight saving time. A walkthrough lists past-due subscriptions, uses a metadata key condition to skip already-notified ones, and sends Slack notifications via the installed Slack app. The workflow handles pagination; if an action fails, the loop stops and remaining items are picked up on the next run, with details showing which step failed. This eliminates the need for a separate server, secret key storage, and daylight saving time logic, putting calendar-based operations under the finance team’s control.
Making it easier to build on Intercom - The Intercom Blog
Intercom announced platform updates to make it easier for developers to build integrations and automate workflows, reflecting its commitment to supporting unexpected business use cases. The Acquire API now provides full API and webhooks support for logged-out users (Contacts), including creating, converting, and merging Contacts and Users. The Conversations API has been expanded to support initiating, replying, opening, closing, assigning conversations, and sending attachments. Intercom now maintains official client libraries for Ruby, Node.js, PHP, Java, and Go, with community-contributed clients for Haskell, Python, and Perl, downloaded approximately 300,000 times. Additional improvements also include a Stripe integration for syncing user data and live events, a fully asynchronous Bulk API for large operations, a WordPress plugin, and OAuth support initially in the Salesforce integration, while third-party apps like AskNicely, Gini, and Talkdesk have built on the platform for NPS tracking, reports, and phone call management.
Creating a whitelabeled connected account dashboard with embedded components
This tutorial explains how to build a whitelabeled connected account dashboard using Stripe Connect embedded components, eliminating the need to manually implement pagination, permissions, and state management. The example uses FurEver, a pet grooming SaaS platform, and integrates the ConnectPayments, ConnectPayouts, and ConnectNotificationBanner components for payments, refunds, dispute management, balance and payout views, and account enablement alerts. The server-side requires creating an account session with enabled components, while the frontend initializes ConnectComponentsProvider with the fetched client secret and publishable key. Platform user roles can be enforced by setting features such as refund_management based on admin status in the account session, automatically adjusting component behavior. The dashboard’s appearance matches the platform using the appearance API with variables for colors, fonts, and locale, and it receives automatic updates for new payment methods and compliance.
Stripe’s Payment Method Factory: Orchestrating agents for repeated, custom integrations
Stripe offers over 125 different payment methods globally, each requiring integrations that previously took up to six months because teams started from scratch. They hypothesized that reusable prompts with hardening could reduce effort, and a bake-off showed vanilla Claude Code took 20 days versus 4 days with their prompts. The resulting factory has created three new payment method integrations and migrated ten existing ones to a modern stack, reducing timelines from six months to two to six weeks. The factory also uses code-based orchestration, continuous knowledge loops where agents suggest prompt improvements, and agents testing their own code against sandbox environments. The factory’s approach has since been extended to Stripe’s tax and verification teams for building their own connectors.
How Stripe is designing Checkout for AI agents
Stripe implemented WebMCP on its Checkout UIs, which processes around 0.45% of global GDP, to optimize the buying experience for AI agents. Previously, agents relied on slow browser automation, consuming an average of 1.8 million tokens and 38.83 tool calls per transaction, taking over 2.5 minutes. WebMCP exposes MCP tools from the client side, allowing agents to execute actions like get_order_summary or fill_payment_form instead of interpreting the DOM. The implementation uses progressive tool disclosure, revealing only relevant tools; in evaluations across six models, agents using WebMCP consumed 42% fewer tokens, made 38% fewer tool calls, and completed checkout 39% faster. Stripe reused existing UI state and forms via imperative and declarative APIs, avoiding a separate agent-only code path and keeping human and agent experiences aligned.
Building custom financial reconciliation workflows with Stripe
The post examines how enterprises can replace SFTP-based financial reconciliation with Stripe’s reporting APIs. Stripe’s Reports API v2 and Query Run API provide SQL-based report customization, consistent schemas, API-key permissioning, audit trails, and event-driven completion notifications instead of fixed files and polling schedules. Using fictional retailer Galtee, the examples run payout queries across multiple Stripe accounts with an Organization secret key, joining transfers with balance_transactions and using a succeeded webhook to trigger retrieval. Further queries join charges to add presentment amounts and exchange rates, then use aggregation and a common table expression to itemize IC+ fees; the conclusion is that this supports an on-demand pipeline that evolves with business requirements.
What if Stripe could work the way your business does
Stripe’s default financial infrastructure covers common payment, subscription, invoicing, and money-movement needs, but businesses may require custom rules, data models, or operational views. Rather than placing every customization behind webhooks and a separately managed server, Stripe extensibility moves logic, data, and user interface capabilities into Stripe through Scripts, Workflows, Custom Objects, and UI extensions. Scripts handle individual decisions such as TypeScript-based proration, while Workflows orchestrate event-driven or manually initiated sequences involving Stripe APIs, third-party integrations, and custom actions. Custom Objects add typed fields, validation, and relationships for concepts such as Rocket Rides’ Vehicles and Rentals, and UI extensions expose that information and business actions in the Dashboard. In the example, an End Rental action updates status, triggers inspection, and marks a vehicle available, connecting the three dimensions without requiring a separate operational system.
Stripe data now available on Databricks via Databricks Marketplace
Stripe Data Pipeline is now available on Databricks Marketplace through Delta Sharing, allowing payment and business data to be analyzed in a Databricks workspace without ETL. Stripe data—including transaction records, customer histories, subscriptions, refunds, and payouts—remains in Stripe’s infrastructure and is queried directly through Unity Catalog, where it can be joined with other tables. The approach replaces polling integrations and custom jobs, avoiding per-call charges, connector licensing fees, data duplication, and maintenance code while providing row- and column-level access controls, audit trails, and compliance features. The shared data is positioned for AI-native uses such as continuous transaction monitoring, churn scoring, LLM-powered retention workflows, Genie queries, and finance analytics apps. Getting started involves visiting the Stripe Data Pipeline listing on Databricks Marketplace.
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