Eigenn

Transaction Intelligence

Transactions are where finance questions start. Eigenn turns each transaction into a record the founder, bookkeeper, and CFO can inspect, explain, categorize, and tie back to customers, invoices, documents, and scenarios.

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transaction queue

94%

12 needs context | Every transaction explains the category, match, and decision trail.

Stripe payout$8,420matched
AWS services$1,944needs owner
Acme payment$12,100reconciled
Payroll debit$18,700forecasted

Review quality

94%

1Merchant enriched
2Invoice match found
3Founder question attached

Live

Bank and payment activity stays current

Explainable

AI categorization shows its reasoning

Reviewable

Questions and fixes stay on the transaction

Transactions lose meaning when context lives elsewhere

A transaction line can hide a customer issue, a margin problem, a vendor surprise, or a runway assumption. If context is in Slack or email, the books stay clean but the decision stays fuzzy.

Opaque

Transactions lack the business reason behind them

Repeated

Bookkeepers ask the same context questions every month

Detached

Scenario assumptions drift from the source records

How transaction queue works

A transaction line can hide a customer issue, a margin problem, a vendor surprise, or a runway assumption. If context is in Slack or email, the books stay clean but the decision stays fuzzy.

01

Sync and enrich activity

Bring bank, payment, and invoice activity into a transaction record with merchant, customer, category, and match context.

02

Explain the categorization

Use AI assist for suggestions while showing the reasoning and keeping overrides visible.

03

Keep the question on the record

Comments, mentions, files, and decisions stay attached to the transaction so the next review has evidence.

Transaction records your team can reason from

Make transaction review useful for bookkeeping, forecasting, customer work, and operator decisions.

Bank sync

Pull live bank and payment activity into the workspace without waiting for a monthly export.

AI categorization

Suggest categories and matches with reasoning that a human can accept, fix, or reject.

Reconciliation matching

Tie payments, invoices, customers, and bank activity together before they become cleanup work.

Context requests

Ask the founder about a transaction directly on the record instead of in a side channel.

Scenario inputs

Use cleaned transaction data as an input to cash, expense, and runway models.

Audit trail

Show who changed a category, added context, or approved a match.

Where this shows up in the week

01

Bookkeeper question queue

Ask precise context questions and keep the answers available for future reviews.

02

Expense surge review

Find which transactions drive an expense increase before changing the forecast.

03

Customer and invoice matching

Match payments to records so cash reporting and customer context stay aligned.

Transaction context
“The transaction record became the place where the question, answer, category, and forecast impact all live.”

Bookkeeper

Fractional finance practice

“AI suggestions are useful because the team can see the reason and override it before it affects reporting.”

Controller

B2B SaaS team

“We stopped asking the same transaction questions every close because the answer stays on the record.”

Finance lead

Agency group

“Expense scenarios are more trusted when they trace back to the transactions behind the trend.”

Founder

Services company

Turn transaction cleanup into finance context

Categorize, explain, match, and review transactions where decisions happen.

See Your RunwayBook a Demo

No credit card required. Start with one finance review and expand from there.

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