AI-Native Revenue Intelligence

Understand Why
Revenue Changes —
and Fix It Faster

Revenue performance can shift without warning. Authorization rates dip. Declines increase. Fraud blocks good customers. Retries underperform. Billing logic impacts payments. Revenue moves — but it's not always clear why.

Natural Language Queries Full Payment Lifecycle LLM-Driven Analysis No SQL Required

Partner to Co-Design Request Early Access

revledger / query

→ Why did auth rates drop yesterday?

AI Analysis — Live

Authorization Rate ↓ 3.2%

Stripe (primary PSP) Degraded

Adyen (fallback) Normal

Revenue at Risk $18,400

            SQL generated · Full transparency
          

The Problem

Payment Data Is Fragmented

PSPs. Fraud tools. Retry engines. Billing systems. Internal reports. Each shows part of the picture. To understand what's driving revenue change, teams export data, reconcile dashboards, or rely on engineering.

PSP Dashboards Fraud Tools Retry Engines Billing Systems Internal Reports

The challenge isn't access to data. It's connecting it — fast enough to protect revenue.

~⅓

of transactions can be exposed to risk from declines, processing failures, or overly aggressive fraud controls — for companies without unified payment intelligence.

The Solution

One AI Layer Across Your Full Payment Lifecycle

RevLedger connects PSP and authorization data, fraud and risk signals, retry and recovery performance, and billing and subscription systems — all normalized into one AI-powered layer.

📊

PSP & Authorization DataMonitor authorization performance across providers in one unified view.
🛡️

Fraud & Risk SignalsDetect overly aggressive rules blocking good customers before they cost you revenue.
🔄

Retry & Recovery PerformanceSee whether retries are actually recovering payments — or just burning through attempts.
💳

Billing & Subscription SystemsSurface how billing logic and subscription events are affecting payment outcomes.
⚡

Instant Transparent AnalysisAsk in plain language. Get instant answers — with SQL visibility, no black box.

No black box No waiting on analysts No dashboard switching

Ask in plain language

› Why did authorization rates drop?

› Which declines are costing the most revenue?

› Are fraud rules too aggressive?

› Are retries actually recovering payments?

› Is one provider underperforming?

Generated SQL · Full transparency

SELECT provider, decline_reason,
  COUNT(*) AS tx_count,
  SUM(amount) AS revenue_lost
FROM transactions
WHERE date = CURRENT_DATE - 1
  AND status = 'declined'
GROUP BY 1, 2
ORDER BY revenue_lost DESC;

Who It's For

Built for Growing Payment Teams

One shared lifecycle view. Clear answers. Better revenue performance.

Founders

Understand Revenue Shifts

Understand revenue shifts without building a data team. Get immediate answers to the questions that affect your growth.

Payments & RevOps

Optimize Authorization Performance

Improve authorization performance and reduce avoidable declines. Stop reacting to revenue loss — start preventing it.

Engineering

Isolate Issues Instantly

Quickly isolate whether performance issues stem from providers or integrations — without pulling reports or writing queries.

Partner With Us

RevLedger Is Built With You