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For accounting platforms

Context before review begins.

On accounting platforms, transactions end up in review and matching steps. TXNORA enriches them with merchant, category and labels beforehand, so your users start with context rather than a raw line.

Request trial accessSee before and after

The starting point

Unclear lines end up in review.

People matching receipts and transactions often see nothing but the transaction description. “REWE SAGT DANKE 1834” adds a phrase and a number to the merchant, and “PAYPAL *ADOBE” names the payment provider first. Before a transaction can be matched, someone has to work out what it is.

Without a consistent merchant name, the same merchant is hard to group, and rules based on raw text have to cover many spellings.

Raw descriptions as they arrive

  • PAYPAL *ADOBE – PAYPAL: Payment provider; ADOBE: Merchant

  • REWE SAGT DANKE 1834 – REWE: Merchant; SAGT DANKE: Extra text; 1834: Number

  • AMZN MKTP DE*X4H88291 – AMZN MKTP DE: Abbreviations; X4H88291: Reference

Example data. The breakdown explains the raw data and is not API output.

What structured context changes

Into review with context.

Three ways structured context supports your review workflow.

  1. Group merchants

    Different raw descriptions of the same merchant can be grouped under one normalized name, for example for rules or batch reviews.

  2. Category as a starting point

    A consistent category gives your users a starting point for matching. The decision stays in your workflow.

  3. Review where it matters

    With the confidence value, you can control which transactions move on and which go to a manual check.

Before and after

Your review queue, before and after context.

Three typical transactions as they arrive in a review list: first as raw text, then with merchant, category, labels and confidence.

Incoming, before review

Three example transactions

  1. Raw

    PAYPAL *ADOBE

    Structured

    Merchant: AdobeCategory: Software

    Amount: −59.49 EUR

  2. Raw

    REWE SAGT DANKE 1834

    Structured

    Merchant: REWECategory: Groceries

    Amount: −42.17 EUR

  3. Raw

    AMZN MKTP DE*X4H88291

    Structured

    Merchant: AmazonCategory: Retail

    Amount: −129.90 EUR

Example data from three typical transactions.

The confidence values are examples, not measured accuracy.

Relevant fields

What your review workflow needs.

For matching and review, category and confidence matter most. The transaction ID links each result to your record.

  • Transaction ID

    transaction_id

    Links the response to the original record.

  • Merchant

    merchant.name

    Groups the same merchant across different raw texts.

  • Category

    category.id · category.name

    A starting point for matching in review.

  • Confidence

    confidence

    Helps decide what needs a manual check.

POST /v1/transactions/classifyExample response
{  "transaction_id": "txn_demo_001",  "merchant": {    "name": "Adobe"  },  "category": {    "id": "software",    "name": "Software"  },  "labels": [    "SOFTWARE",    "DIGITAL_SERVICE"  ],  "confidence": 0.984}

Relevant for this use case

Simplified example.

More use cases

Other products, the same foundation.

  • 01

    Fintechs

    Make transaction feeds easier for people to understand.

    PAYPAL *ADOBEbecomesMerchantAdobe

  • 03

    Expense tools

    Bring more consistency to spending categories and review queues.

    PAYPAL *ADOBEbecomesLabelsSOFTWARE · DIGITAL_SERVICE

  • 04

    Analytics products

    Work with structured transaction data in your own reporting experience.

    AMZN MKTP DE*X4H88291becomesMerchantAmazon

Test TXNORA with your product.

With free trial access, you see which fields matter for your use case. After your request, you receive access to the API, the developer documentation and our pricing.

Request trial accessAll use cases