Who We Are
Turn pricing, demand, inventory, and portfolio signals into faster actions, measured outcomes, and learning that compounds.
Revenue Intelligence DeployCo · AI Agents for Revenue & Commercial Ops
THE PROBLEM
Pricing, portfolio, and promotion decisions are made episodically — a consulting engagement, a strategy document, an implementation plan. Then the market moves. Competitors reprice. Consumer behavior shifts. Demand patterns change. By the time the erosion shows in your numbers, you're six months behind and back in a consulting cycle.
Revenue leakage isn't a one-time event. It's continuous — and most companies discover it far too late.
The Decision Loop
Signals become a diagnosis. A diagnosis becomes a recommendation. Humans decide. Outcomes are measured. The next recommendation gets smarter.
1 · Signal
Commercial pressure detected
Signals are moving out of sync.
2 · Diagnose
Revenue gap identified
Signals become a specific, quantified diagnosis.
3 · Recommend
Mitigation options prepared
Current signals combine with similar past decisions.
4 · Decide
Human judgment applied
Humans approve, modify, or override — and the rationale is captured.
5 · Act
Commercial move executed
The decision enters the operating workflow.
6 · Measure
Business impact tracked
Outcomes are measured against baseline.
7 · Remember
Learning becomes reusable
The next similar decision starts with better context.
Decision Memory
↻ Next similar event → better recommendation
Where It Applies
Find the category that matches how your team makes decisions today.
For businesses where demand, capacity, and pricing move together.
Examples
Best fit
For teams balancing commercial demand against operational constraints.
Examples
Best fit
For teams managing products, packs, channels, media, and portfolio performance.
Examples
Best fit
WHAT OUR DIAGNOSTICS FIND
We don't audit from the outside. We run the diagnostic inside your commercial data and show you exactly where revenue is leaking.
PRIVATE AVIATION
10%+
premium revenue uplift
A membership-based private aviation company with pricing that rarely changed — leaving peak demand undermonetized and slow periods unfilled.
Diagnostic finding
Revenue gaps across four simultaneous commercial levers:
CONSUMER GOODS — $3B COMPANY
8%
revenue uplift across the portfolio
A $3B consumer goods company making portfolio, pricing, and content decisions disconnected from real purchase behavior and competitive market dynamics.
Diagnostic finding
Revenue gaps across five simultaneous commercial levers:
WHY AGENTIC AI
Three reasons why agentic AI is uniquely suited to revenue intelligence — and why neither traditional tools nor point-in-time engagements can replicate it.
Revenue leakage happens between teams — where pricing meets inventory, spend meets purchase behavior, competitive signals meet portfolio decisions. Agents span those boundaries by design. No single dashboard or team owns all of it.
Dashboards surface what already happened. Consultants diagnose last quarter. Agents detect signals continuously and trigger recommendations while recovery is still possible. The difference isn't intelligence — it's timing.
Every consulting model is static the day it's delivered. An agent learns from every outcome — automatically improving its next recommendation. Value in month twelve is structurally higher than month one. That's the opposite of consulting.
How We Work
We start with one high-value recurring decision, deploy and operate the loop around your data and workflow, then measure whether the recommendations improve outcomes.
Define the recurring decision, current workflow, decision owners, and business metric.
We deploy agents into your commercial workflow — connecting signals, recommendations, human approvals, actions, and memory. We operate it, not hand it off.
Run the loop, measure outcomes, and turn what works into a reusable operating system.
Consulting-grade problem solving, productized through reusable agents.
Who We Are
Every quarter without a diagnostic is a quarter you can't recover. We'll show you exactly where — in 2 weeks, not 6 months. Real findings from your actual commercial data.
Based on evidence, not promises.
