Turn raw transactions into categories your users understand
Openaggr classifies every bank transaction and surfaces cashflow insight in milliseconds, the intelligence layer a finance app needs but should not build itself.
From raw string to structured insight
Every bank transaction arrives as a messy string. Openaggr normalizes, classifies, and enriches it in a single API call.
The numbers behind the enrichment pipeline
1,200 categories, organized for real users, not accountants.
The taxonomy is designed for the spending breakdowns users actually read, not for reconciliation ledgers. Every category includes a color token, an icon identifier, and subcategory depth ready for your UI layer.
30-day cashflow forecast, per category
The /cashflow endpoint builds a 30-day forward projection from enriched transaction history. Each category gets its own spending curve. Recurring charges are separated from discretionary spend so your projected balance feature stays accurate when a subscription renews mid-month.
From the engineers who integrated it
"We had burned three sprints building and re-training a category model that still mislabeled half the gig economy merchants. Openaggr was integrated in a day. The color token system mapped straight into our spending breakdown UI with no intermediate layer."
"We maintained a regex ruleset for recurring charge detection that needed manual updates every quarter. Openaggr's API handles 14 pattern types automatically, including the irregular utility and insurance charges our regex never caught. Latency is well inside our ingestion SLA."
Start enriching transactions in under an hour
Free tier. No credit card. Production keys in 5 minutes.