Case Studies — Pareto Edge Consultancy

Case Study 01 · WhataKabob · Nostal Foods portfolio company · Austin, TX

From 40+ hours a week to 5. An AI-enabled operations transformation.

WhataKabob's owner was running seven disconnected operational workstreams across more than 35 separate logins. Five months later, the business runs on an integrated, AI-enabled operating layer. The owner spends 5 hours a week on strategic oversight instead of 40+ hours on manual operations. Revenue is up 2.5x. Costs are down across nearly every line. The growth is leaner than it was when the owner was working full-time.

The Setup

WhataKabob is a fast-casual ghost kitchen and corporate catering operation in Austin, TX, and the flagship portfolio company under Nostal Foods. The business operates across eight sales channels: POS direct in-store and online, four third-party delivery platforms (DoorDash, Uber Eats, Grubhub, Favor), and three corporate catering platforms (Fooda, Hungry, Waiter.com), plus a small but growing direct catering channel. The brief: build the integrated AI-enabled ops infrastructure that lets the business grow faster and leaner, while reducing the owner's operating role from 40+ hours a week to under 5.

The Challenge

Operating across 35+ disconnected logins.

The challenge wasn't the eight sales channels. It was that nothing talked to anything else. The owner navigated more than 35 separate logins. Procurement portals for each supplier. Eight sales-channel dashboards. Inventory tracked on spreadsheets. Demand forecasting based on static snapshots. Pricing decisions on intuition. Marketing performance scattered across Google Ads, Yelp, Instagram, and Meta. Financials in QuickBooks, disconnected from every operational lever upstream.

More than 35 separate logins across suppliers, sales channels, finance, marketing, and quality.
Seven operational workstreams running as silos.
The owner was the only person bridging the silos. Every cross-stream decision routed through them.
Manual reconciliation and login-hopping consumed 40+ hours of owner time each week.
Pricing, procurement, and capacity decisions were intuition-driven. Margin and growth leaked through gaps no one could see.

The Vision

Most small businesses operate in operational silos. Sales lives in the POS. Financials live in accounting software. Procurement runs on email. Marketing data scatters. Each stream gets reviewed monthly, in isolation, by the owner who is the only one with the full picture.

That model is the same operational deficit we see at $50M PE-backed CPG portfolio companies, just at smaller scale. Our thesis: integrate the streams, surface real-time decision data, automate the manual work, and apply AI selectively where it changes the unit economics. Then collapse the owner's operating load to a small number of high-leverage hours a week.

WhataKabob is where we proved the playbook end-to-end. The same methodology scales to a portco at 50x the revenue.

The Five Streams. Connected.

Sales & Demand

POS connected via API as the unified source of truth across all eight sales channels. A browser-agent layer captures order-level data from the corporate catering platforms (Fooda, Hungry, Waiter.com). Item-level revenue, modifier-level revenue, daypart heat maps, channel mix, and demand patterns are queryable on demand. The owner went from logging into eight dashboards every morning to opening one view of the entire day.

Procurement, Inventory & Supplier Network

POS-integrated procurement consolidated par-level management, multi-vendor ordering, and inventory tracking into a single AI-assisted workflow. A browser-agent layer captures supplier-side data automatically, replacing what had been a weekly login-hopping ritual. A detailed menu-recipe layer drives item-level cost tracking and flags any supplier price increase the day it hits, before it compresses margin. Manual purchasing time was cut by ~60% with stockouts on high-velocity items eliminated.

Production & Capacity

A live capacity workbook covers all operating days, with minimum-staffing rules enforced. The kitchen schedule is directly responsive to sales demand, catering-event volume, and prep timing for high-volume orders. Owner hours are an input variable, so the transition out of day-to-day operations was modeled live in the same workbook that runs scheduling, and executed cleanly across the five-month plan.

Pricing, Margin & Financial Visibility

QuickBooks connected for full P&L, balance sheet, and cash flow visibility. Channel-level revenue, commission fees, and promotional discount allocations now aggregate automatically. The true cost of marketing across paid channels became visible for the first time. A live revenue-target sensitivity model lets any pricing or staffing decision update required revenue in real time. Pricing is now margin-math driven, not intuition-driven.

Marketing & Customer Acquisition

The initial marketing diagnostic surfaced the true CAC across paid platforms, including platform-funded promo dollars and commission fees that quietly compress margin without showing up in QuickBooks. An AI agent ingests Google Ads, Yelp, Instagram, and Meta ad performance daily and joins it back to POS sales data so item-level ROI is visible per channel.

Cross-Stream Integration

The streams talk to each other. That is the entire point.

Sales channel mix shifts → procurement par levels recalibrate → labor schedule adjusts → financial sensitivity model updates required revenue.
Marketing surfaces a high-conversion item → recipe data reveals item-level margin → pricing decision is made on margin math, not static assumptions.
Catering pipeline fills → kitchen schedule books prep capacity → supplier orders auto-adjust → financial forecast updates without manual intervention.

What used to take weeks of meetings, login-hopping, and manual reconciliation collapses into hours. The owner is removed from the critical path of most routine decisions.

Early Outcomes

40+ → 5

Owner hours per week

2.5x

Revenue growth, Q1 to Q2

60%

Manual purchasing time cut

35+

Logins consolidated to 1 view

Same-day

Decision cycle (was monthly)

Real-time

Item-level profitability

The owner now works ON the business, not IN it. Operations run without daily owner attention.
Costs reduced across nearly every line. Low-ROI channel promos cut. True CAC surfaced.
Decision cycle collapsed from monthly to same-day across sales, procurement, financials, and marketing.
Item-level profitability visible in real time. Pricing decisions driven by margin math.
Cross-stream feedback loops automated. Sales shifts trigger procurement and labor adjustments.
Leaner growth, not just bigger growth. Quarterly growth projected at 2 to 3x through next two quarters.

What's Possible at Scale

The practitioner view.

This is the work we do. We are operators, not theorists, with deep hands-on experience scaling regulated manufacturing, complex supply chains, and consumer brands from prototype to multi-facility, multi-million-dollar operations.

The same playbook scales. For any CPG, food-tech, or biotech operation that has outgrown its founding infrastructure, or is looking to use AI to get leaner and more profitable, the operational deficit looks identical: more streams, more complexity, same root cause. Siloed data, lagging decisions, owners or GMs in the middle of every routine call. We bring unified data infrastructure, real-time decision layers, integrated cross-stream feedback loops, and AI applied only where the math justifies it. Never for its own sake. Implementation costs stay low and most engagements recover them within the first quarter through efficiency gains alone.

If you are running, advising, or sitting on the board of a business that looks like this, and you want an operator who has built it before, not a consultant who has read about it, we should talk.

At Pareto Edge, we test our methodology in live operating environments before recommending it to clients. WhataKabob is one example of tools that have worked in practice: integrated data infrastructure, cross-stream feedback loops, and selective AI deployment tied to measurable operating outcomes. This is not meant to be a fixed or all-inclusive menu. The field is moving too quickly for that. Our role is to stay at the forefront, pressure-test what works, and apply the right tools to each company's specific margin, supply chain, and operating constraints.

Case Study 02 · Meal Prep Company

Putting a 20-year chef back in the kitchen.

A growing meal prep company had strong demand and strong unit economics, but growth was capped by a hidden constraint: the founding chef.

With 20+ years of high-volume culinary experience, he created the most value in production. Instead, much of his week was being consumed by pricing decisions, procurement spreadsheets, menu planning, demand tracking, vendor follow-up, and customer service. The business performed well when he was in the kitchen. The problem was that the operating model kept pulling him out of it.

We built an AI-enabled operating layer across pricing, procurement, vendor management, demand planning, and marketing ROI tracking. The system handled the repeatable analysis and surfaced clear recommendations in plain English. The chef still made the final calls, but he no longer had to spend hours gathering, cleaning, and interpreting the data himself.

Case Study 03 · B2B Supplement Ingredients

End-to-end integration across 50+ suppliers and the full production stack.

A B2B supplement ingredients manufacturer was managing a complex operation with manual tracking across more than 50 suppliers, multiple SKUs, and a production flow that stretched from procurement to warehousing, manufacturing, and finished product.

The team was capable, but the system was fragmented. Inventory visibility lagged. Supplier cost changes were not flagged early enough. Quality data lived in disconnected spreadsheets. Each function had information, but no single operating view connected the full chain.

We integrated the operation into one AI-enabled workflow across procurement, ordering, warehousing, manufacturing, and finished goods. Each stage fed the next. Supplier cost changes triggered procurement reviews. Inventory and quality data were reconciled continuously. Instead of managing five disconnected workflows, the team had one operating system for the full production stack.

How we apply the playbook.