Revenue Analytics CMI

The commercial margin operating system for industrial companies

Revenue Operations Manufacturing & ERP Business Intelligence www.revenueanalytics.com

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Founded

2005

Starting Price

Custom

About Revenue Analytics CMI

Revenue Analytics CMI (Commercial Margin Intelligence) is an agentic AI platform that finds where margin is leaking across price, customer, product, cost, and sales behavior for manufacturers, distributors, and the private equity firms that back them. It succeeds the vendor's Pricing-as-a-Service offering and pairs the software with embedded pricing and commercial experts who turn findings into field action.

Pros & Cons

Pros

Pairs software with an embedded team of pricing and commercial experts, so it works without an in-house pricing department
Built for messy industrial data: thousands of SKUs, fragmented ERP data, and decentralized sales pricing
Every finding is dollarized and tied to a specific rep, customer, or product
Vendor reports ROI in under three months and 300+ bps average margin improvement for PE portfolio companies
Strong data posture: tenant isolation, private AWS Bedrock processing, and no model training on customer data

Cons

No public pricing; sold as a custom annual subscription through a demo
Aimed at mid-market and enterprise industrials and PE portfolios, not small businesses
CMI reached general availability in June 2026, so the platform has a short public track record
Few independent user reviews on G2 or Capterra; results cited are vendor-reported

Key Features

Continuous margin visibility

Always-on analysis of every commercial transaction across price, customer, product, cost, and sales behavior, replacing quarterly margin reviews.

Agentic AI opportunities

AI agents surface unnecessary discounting, at-risk customers, win-back plays, and product mix imbalances, each with a dollar impact estimate, recommendation, and supporting evidence.

CMai conversational analyst

Ask plain-language questions such as which customers have declining margins and get data-backed answers with inline charts, sortable tables, and exports; context carries across sessions.

Five intelligence views

A prioritized Home view plus dedicated Sales Rep, Customer, Product, and Pricing views, each listing named opportunities with CSV export.

AI price guidance

Price corridors (floor, target, stretch) and real-time guardrails embedded in quoting and CRM tools to enforce pricing discipline in the field.

Cost-to-price compression alerts

Flags products where unit cost has outpaced unit price, customers priced below economic peers, and transaction-level pricing outliers.

Embedded expert team

Business strategists, commercial experts, data engineers, and PhD mathematicians work alongside customer teams from implementation onward.

ERP and CRM integrations

Connects to SAP, Microsoft Dynamics 365, Salesforce, and Epicor Prophet 21 to normalize messy industrial commercial data.

Isolated AWS deployment

Runs in a dedicated AWS environment with tenant-isolated data, AI processing through AWS Bedrock inside a private VPC, no model training on customer data, and SSO.