Sync a Paysley merchant account into your own stack

Every payment a merchant takes through Paysley — virtual terminal, QR Scan & Pay, an SMS or email link, or a Bluetooth swipe, EMV and tap reader — settles into one cloud account that the mobile app mirrors. The phone is a window; the records live server-side. That is the part worth wiring into your own systems, and the work this page describes is building the client that reads it.

For Paysley the practical lead is ingestion: a small language client that signs in to a merchant's account, pulls the payment ledger and the request and customer records, and keeps them current. Below is what the account actually holds, the route we would take to reach it under the account holder's authorization, and what lands in your repository at the end.

What a Paysley account actually holds

The mobile app and the cloud desktop share one back end, so the merchant's data is the same object set regardless of which surface created it. These are the domains worth reading.

Getting at the data: the routes that fit

Authorized read of the merchant's cloud account

This is the route we would take. With the account holder's authorization, we map the token chain the app uses to reach the cloud platform and drive the same surfaces from a server-side client — payments, requests, customers, inventory. Coverage is broad, the records come back structured, and the read is stable enough to run on a schedule. Access is arranged with you during onboarding; we build against the test environment first and switch to live once the logic checks out.

Protocol analysis of the app traffic

For any surface that the account read does not expose cleanly, we capture and document the mobile app's calls under the merchant's authorization — the auth handshake, the bearer token lifecycle, the request and response shapes. Slower to stand up, but it reaches whatever the app itself can see. We use it to fill gaps, not as the whole spine.

Native export as a backfill

The platform's own history views give a one-off dump for seeding history before the live read takes over. Useful on day one; not something to depend on for freshness.

What lands in your repo

The deliverable is working code, not a slide deck. For Paysley that means, in order of what most teams use first:

• A runnable client in Python or Node.js that authenticates to the merchant account and reads payments, payment requests, customers and inventory — the methods you call, with paging and date filtering handled inside.
• Event-callback handlers that accept the platform's payment notifications and update your records as money arrives, instead of waiting for the next sweep.
• An automated test harness that exercises the read against the test environment with recorded fixtures, so a change on either side is caught early.
• A backfill-and-sync design: how the first full history load runs, how the incremental cursor advances, and how the two stay reconciled.
• An OpenAPI description of the surfaces we drive, and a short protocol and auth-flow write-up (the bearer-token chain, error codes, retry behavior) for the engineers who maintain it.
• Interface documentation and data-retention notes covering what we read, what we deliberately do not, and where each field comes from.

A payment-history pull, sketched

Illustrative, with field names confirmed during the build. A real client paginates to the end and persists a high-water mark; this trims that to show the shape.

# Paysley merchant account — read settled payments for a date window
import httpx

BASE = "https://live.paysley.io"          # py_live_ keys; test.paysley.io for py_test_
auth = {"Authorization": f"Bearer {access_key}"}

def settled_payments(start_date, end_date, page=1, limit=100):
    r = httpx.get(f"{BASE}/v2/payments", headers=auth,
                  params={"start_date": start_date, "end_date": end_date,
                          "page": page, "limit": limit})
    r.raise_for_status()
    body = r.json()
    for p in body["data"]:
        if p["status"] != "ACK":          # NOK means declined or failed
            continue
        yield {
            "id":       p["payment_id"],
            "ref":      p["reference_number"],
            "amount":   p["amount"],
            "currency": p["currency"],
        }
    # caller advances `page` until data runs dry, then stores the last end_date

Refunds run against a known payment id rather than the card, and recurring requests carry their own frequency — both are modeled in the client so neither distorts the ledger.

Build notes specific to Paysley

A few things about this platform shape the work, and we handle each as part of the build rather than handing them back to you.

• Test then live keys. Keys are environment-scoped — the py_test_ prefix on the test host, py_live_ on production. We validate the full read and reconciliation against the test environment before a single call touches real settlement.
• Card data stays out of scope. We read tokenized money records — payment id, reference, amount, status — and never pull or store the card number. Capture stays inside Paysley's EMV and hosted flow, so the integration we deliver does not pull your stack into cardholder-data scope.
• One shape across many channels. The same account receives money from the virtual terminal, QR, links and the Bluetooth reader. We normalize all of it to a single transaction record so downstream code does not fork per channel.
• Recurring versus one-off. Payment requests can repeat weekly, monthly, quarterly or yearly. We model the schedule so a recurring charge is tied to its series instead of being read as a brand-new sale each cycle.

Where teams plug this in

• Nightly settlement reconciliation: pull the day's accepted payments and match them against your general ledger.
• Live accounts receivable: on a payment-request callback, mark the matching invoice paid in your billing system.
• One report across every channel: merge terminal, QR, link and card-reader takings into a single revenue view.
• Catalog and customer sync: keep your CRM and stock counts aligned with the Paysley records.

Authorization, card data, and what governs the read

The dependable footing here is the merchant's own authorization over their account. They own the payment, customer and inventory records; the integration reads them on their instruction, under an NDA where the project calls for one, with access logged and the field set kept to what the use case needs. We do not read what we were not asked to.

Because card-present payments run through EMV and chip on the reader, the security line that matters most is PCI DSS, and we stay clear of it by design — tokenized references only, no primary account numbers crossing our code. On consumer data-rights law: the US CFPB Personal Financial Data Rights rule (12 CFR Part 1033) is not in force as of mid-2026, with enforcement enjoined and the rule back in agency reconsideration, and in any case it speaks to consumer accounts rather than a merchant's own transaction records. It is where the broader picture may go, not the basis we rely on. The basis is the account holder's consent.

Screens from the app

How this brief was put together

I worked from the app's own store listing and Paysley's user guide and platform documentation in June 2026, cross-checking the data surfaces named in the merchant app against the records the cloud platform exposes. Where a detail was not stated plainly, the page says so rather than guessing. Primary sources I opened:

• Paysley Merchant on Google Play — feature list and package id (com.paysley.merchant, per the listing).
• Paysley platform documentation — environments, bearer auth, payment and request objects.
• Paysley user guide — virtual terminal, Scan & Pay and managing payments.
• Paysley mobile POS — card-reader and in-person payment flow.

Engineering notes by OpenFinance Lab, June 2026.

Other merchant payment apps in the same orbit

Teams integrating Paysley often run, or compare against, other merchant payment back ends. Reading several through one normalized model is a common reason to start. Neutral context, no ranking:

• Square Point of Sale — in-person and online sales with a merchant ledger of payments, items and customers.
• Stripe Dashboard — charges, payouts and customer objects behind a developer-centric back end.
• Helcim — interchange-plus merchant accounts with invoicing, a virtual terminal and recurring billing.
• SumUp — reader-based card acceptance with a transaction and payout history per merchant.
• PayPal Zettle — point-of-sale takings, products and reporting tied to a PayPal merchant account.
• Clover — POS hardware and apps holding orders, payments and inventory.
• SpotOn — restaurant and retail POS with sales, customer and loyalty records.
• Lightspeed Retail — inventory-heavy POS with catalog, sales and customer data.

Questions integrators ask about Paysley

Do you poll Paysley for new payments, or react to events?

Both, and the mix depends on how fresh you need the data. The durable backbone is a paged read of the payment history filtered by date, with a stored high-water mark so each run continues where the last one stopped. On top of that we wire the platform's response callbacks for payment events so a sale shows up in your system within seconds rather than at the next sweep. The client we hand over keeps the two reconciled against each other.

Does reading payment data drag us into PCI cardholder-data scope?

It does not have to. We keep the read on tokenized references — payment_id, reference_number, amount, currency, status — and never request or persist the primary account number. Card capture stays inside Paysley's EMV and chip flow on the reader or hosted page. The integration we deliver handles money records, not card numbers, which keeps it out of cardholder-data scope.

We take payments through a Shopify store and in-person POS on Paysley — can one integration cover both?

Yes. Whether the money came in through a Shopify checkout, the virtual terminal, a QR Scan and Pay, an SMS or email link, or a Bluetooth card reader, it settles into the same merchant cloud account. We read that account once and normalize every channel to one transaction shape, so your reporting code does not branch per source.

Can you tell recurring payment requests apart from one-off charges?

Yes. A Paysley payment request carries a frequency — one-time, weekly, monthly, quarterly or yearly — and a payment type such as direct billing or pre-authorization. We model that schedule explicitly so a recurring charge is recognized as part of its series and not counted as a fresh sale each cycle, which keeps subscription and installment revenue clean in your ledger.

Working with us

You bring the account you need read and a description of what you want out of it; we arrange access, build the client, and hand it over. Source code lands in your repository from $300, billed only after delivery once it runs to your satisfaction — or, if you would rather host nothing, call our endpoints and pay per call with no upfront fee. A first Paysley integration, runnable client plus tests and interface docs, usually takes one to two weeks. Tell us the shape of the read you need and we will scope it: get in touch.