Your transaction feed is 30% wrong. We fix it in 200ms.

Spendaq is a real-time reclassification and cash-flow forecasting API for SMB banking apps. Drop it into your open banking pipeline — accurate categories and forecasts ship in days, not months.

spendaq — live reclassification feed
09:41:07.142
DEBIT_MISC Office Supplies
142ms
09:41:08.240
PAYMENT_OTHER Software Subscription
98ms
09:41:09.427
UNCATEGORIZED Business Travel
187ms
09:41:10.081
TXN_UNKNOWN Utilities
113ms
09:41:11.352
MISC_DEBIT Professional Services
156ms
<200ms Median reclassification latency
94%+ Categorization accuracy on open banking feeds
Charlotte, NC In the heart of US banking infrastructure

Open banking APIs deliver data. Not accuracy.

Plaid, Tink, Truelayer — they connect bank accounts and deliver transaction streams. But miscategorization rates of 20–35% are industry-normal. That garbage goes straight into your cash-flow dashboards.

One API call. Accurate categories. Forecast-ready.

Spendaq sits between your open banking data feed and your SMB dashboard. POST a transaction batch, receive corrected categories + a 90-day cash-flow forecast signal in under 200ms.

See how it works
Abstract architectural diagram showing three layers: Open Banking APIs, Spendaq Engine, Banking App Dashboard

Built for banking product teams

Real-time reclassification

Batch or streaming. Corrects miscategorized transactions from any open banking feed in under 200ms.

Cash-flow forecast API

90-day rolling forecast signal derived from corrected transaction history. Embed directly in your SMB dashboard.

Feed-agnostic integration

Works with Plaid, Tink, MX, Truelayer, and raw bank CSV exports. No re-engineering your data pipeline.

Bank-grade data handling

All transaction data processed in isolated compute. Zero retention after classification. SOC 2 controls in progress.

Integrate in a sprint

01

Connect your feed

POST your transaction stream — raw Plaid, MX, or any open banking format.

02

Spendaq reclassifies

ML engine corrects categories in <200ms. Confidence scores included.

03

Serve accurate data

Corrected categories + 90-day forecast signal stream back to your app.

See the full integration guide

What banking teams are saying

"We dropped Spendaq into our Plaid pipeline in under a week. Cash-flow accuracy went from embarrassing to something we can actually show enterprise SMBs."

Marcus Reyes

Head of Product, Kestrel Banking

"The <200ms latency is real. Our customers get live category corrections in the feed — no nightly batch, no data lag."

Priya Sehgal

Lead Engineer, Ironbay Neobank

Ready to fix your transaction feed?