Retail intelligence
The brain of retail.
The best action for every SKU, every week, for more revenue, profit and cash.
This week's top actions
1
Replenish 3,200 units of core denim
Inventory+$420K
2
Match price on 14 outdoor SKUs
Competitiveness+$310K
3
Promote fleece next week to drive baskets
Promotions+$180K
4
Fix main image and copy on the down parka
Marketing+$70K
✓ Ranked by value ✓ Conflicts resolved ✓ Checked against your strategy
Illustrative week
Trusted by retailers including
Series A led by Accenture Ventures
Also backed by AI Fund · Magarac Venture Partners · Lightscape Partners · HKSTP
The weekly business review
Your weekly business review finds a fraction of the money.
Hundreds of reports. Thousands of hours in Excel. A meeting to talk through what was found, and only a fraction of it acted on.
Meanwhile, profit slips away every week across pricing, promotions, inventory, assortment, marketing and competitiveness. Nobody has the hours to check every SKU against every lever.
How it works
Specialist agents find the opportunities. A director agent picks the best.
1
Every SKU, every lever
Specialist agents review pricing, promotions, inventory, assortment, marketing and competitiveness for every product, every week.
2
Sized in dollars
The director agent values each action, resolves conflicts between them, and checks every one against your strategy and business rules.
3
One ranked list
Your team gets the best actions first, in the Profitmind app, in weekly reports, or sent straight into your pricing, allocation and ERP systems.
4
Smarter every week
Merchants decide, and say why. Profitmind learns from every decision, for your business and across retail.
The agents
Every lever. Every SKU. Every week.
Pricing
The most profitable price for every SKU, from elasticity built for retail.
Pricing Agent →Promotions
Which items to promote, when, and at what depth, judged on total profit, not just units.
Promotions Agent →Inventory
Find stockouts and overstocks early, and move units to where they'll sell.
Inventory Agent →Assortment
See what competitors carry that you don't, by price and attribute.
Assortment Agent →Marketing
Is the product the problem, or the page? Every product page audited for search, AI answer engines and conversion.
Marketing Agent →Competitiveness
Every competitor product matched like-for-like, every week.
Competitive Intelligence Agent →Plus the Planning, Strategy, Data Load and Monday Morning agents.
New · Profitmind Awase
Every competitor product, matched like-for-like.
Awase reads the image, description and specification together. It finds the exact match where one exists, and the closest comparable where it doesn't, even in fashion, where barcodes don't line up.
61%
fewer first-attempt errors than the strongest retail-specific alternative tested
Your product
Women's Pure Linen Shirt
100% linen · relaxed fit · long sleeve
Competitor
Premium 100% Linen Shirt
Competitive match
Competitor
Relaxed Shirt With Linen
Rejected
A title match would accept both shirts. Illustrative.
Launching at NRF · January 2027
Ask Profitmind. The same brain, on demand.
Ask in your own words, in any language. The answer comes from the brain that runs your weekly review: your history, your market, and what has worked before, sized in dollars and ready to act on.
The language model is the voice. Profitmind is the brain. Not a generic chatbot.
Outerwear is behind plan for November. What should we do this week, and what's it worth?
Profitmind
Outerwear is −6.1% vs Plan month to date, a $910K gap. Two-thirds of it is eCommerce volume: parka traffic is down 18% since a rival cut prices on 31 matched styles. Stores are on plan.
1
Match the rival on 12 of the 31 styles, where the volume pays for the margin
Competitiveness+$310K
2
Move 2,400 parkas from warm-climate stores to the Northeast before the cold snap
Inventory+$240K
3
Fix the main image on the top 5 parkas, where shoppers drop off on the product page
Marketing+$90K
+$640K together, about 70% of the gap. Not recommended: a 30%-off event lifts units but costs $180K in margin.
Abrigos va por debajo del plan en noviembre. ¿Qué hacemos esta semana y cuánto vale?
Profitmind
Abrigos va −6,1% frente al plan en el mes, una brecha de $910K. Dos tercios son volumen de eCommerce: el tráfico a parkas cae un 18% desde que un rival bajó precios en 31 estilos equivalentes. Las tiendas van según el plan.
1
Igualar al rival en 12 de los 31 estilos, donde el volumen compensa el margen
Competitiveness+$310K
2
Mover 2.400 parkas de tiendas de clima cálido al noreste antes de la ola de frío
Inventory+$240K
3
Mejorar la imagen principal de las 5 parkas líderes, donde los clientes abandonan la página
Marketing+$90K
+$640K en total, cerca del 70% de la brecha. No recomendado: un evento de 30% de descuento sube unidades pero cuesta $180K de margen.
Les manteaux sont sous le plan pour novembre. Que faire cette semaine, et combien cela rapporte-t-il ?
Profitmind
Les manteaux sont à −6,1 % du plan depuis le début du mois, soit un écart de 910 K$. Les deux tiers viennent du volume eCommerce : le trafic sur les parkas a baissé de 18 % depuis qu'un concurrent a baissé ses prix sur 31 modèles équivalents. Les magasins sont dans le plan.
1
S'aligner sur le concurrent pour 12 des 31 modèles, là où le volume compense la marge
Competitiveness+310 K$
2
Transférer 2 400 parkas des magasins des régions chaudes vers le Nord-Est avant la vague de froid
Inventory+240 K$
3
Corriger l'image principale des 5 parkas phares, où les clients quittent la fiche produit
Marketing+90 K$
+640 K$ au total, environ 70 % de l'écart. Déconseillé : une opération à −30 % augmente les volumes mais coûte 180 K$ de marge.
Illustrative answer
Results
Positive ROI for every client.
Positive ROI within 4–8 weeks of go-live.
$1B+
in opportunities identified
200M+
products learned from
Every segment
Apparel, footwear, home, hardlines, grocery, beauty, sporting goods, specialty
$4M
Higher Revenue and Profit in Auto Batteries, First 9 Months
Batteries Plus Reverses Margin Decline with Zone Pricing Strategy
Read the case study →85%
Reduction in Evaluator Time
Retailer Reduces Search Evaluation Time by 85% and Projects Up to $460M in Revenue Uplift
Read the case study →$25M
Annualized Sales Opportunity
Specialty Apparel Retailer Discovers $25M Annual Opportunity at Zero Net Working Capital Cost
Read the case study →Up to $18M
Annual Margin Improvement Potential
Regional Grocery Chain Identifies Up to $18M in Annual Margin Through Promotional Optimization
Read the case study →$7M
Average Weekly Annualized Opportunities
Multi-Brand Retailer Finds $7M in Weekly Annualized Opportunities Across Four Brands
Read the case study →$2M
Annualized Revenue Opportunity
E-commerce Retailer Projects $2M Annual Revenue Across 10,000 SKUs
Read the case study →$2.5M
Revenue Gain from Budget-Neutral Reallocation
Home Decor Retailer Gains $2.5M from Budget-Neutral Marketing Reallocation
Read the case study →$6-13M
Annual Revenue Recovery Opportunity
Online Jewelry Retailer Identifies $6–13M Recovery Opportunity After Price-Driven Revenue Decline
Read the case study →88%
Total SKU Coverage at 100% Match Score
DIY Retailer Achieves 88% Competitive Coverage Across 19 Competitors with Profitmind Matching
Read the case study →99.9%
High-Confidence Match Accuracy
Home Improvement Retailer Achieves 99.9% Competitive Match Accuracy
Read the case study →$75M
Conservative Annual Impact (12% of Revenue)
Plus-Size Fashion Retailer Unlocks $75M in Conservative Annual Value Through AI Forecasting
Read the case study →+73%
Peak CTR Improvement (All Users)
Telecom E-commerce Platform Achieves Up to 73% Click-Through Rate Improvement with AI Personalization
Read the case study →$12M+
Highest-Confidence Opportunities Identified
Footwear Retailer Identifies $12M+ in Immediate Opportunities Across 14,000 SKUs
Read the case study →$8M
Gross Margin Increase, Flagship Category (Annual)
Global Footwear Brand Projects $8M Gross Margin Increase on Its Flagship Category
Read the case study →+25%
Increase in Sales
Regional Home Improvement Retailer Lifts Sales 25% and Profits 15% with Full-Stack Deployment
Read the case study →90%
MAPE Reduction
Beauty Conglomerate Cuts Forecast Error by 90% Across 13 Countries in 9 Weeks
Read the case study →$8M
Annual Working Capital Saved
Fashion Retailer Saves $8M a Year in Working Capital with Demand Forecasting Across 15 Departments
Read the case study →€3.5M
Annualized Profit Opportunity
Home Improvement Retailer Identifies €3.5M in a Single Category Within 9 Weeks
Read the case study →$14M
Projected Incremental Revenue (12 months)
How an Intimate Apparel Retailer Found $14M in Revenue with Profitmind
Read the case study →Why Profitmind
We know retail from the inside.
Built by retail operators
CEO and co-founder Dr. Mark Chrystal is a 25-year retail executive across merchandising, planning, inventory and eCommerce.
Chaired by an AI pioneer
Our chairman, Dr. Andrew Ng, helped define agentic AI.
Five years of retail learning, built in
Trained on 200M+ products and on how real merchants decide. You bring your data and your strategy.
Into your systems
Actions flow into your ERP, pricing and allocation tools. No rip-and-replace.
Dr. Mark Chrystal
CEO & Co-Founder
Dr. Andrew Ng
Chairman
Barney Govan
CTO & Co-Founder
Mark DiBello
Director of Customer Success
Megan Donadio
VP, Product & Customer Value
Jeff Rix
Head of AI
Lori Pike
Head of Engineering
Sonia Hernandez
Director of Delivery
See what Profitmind would find in your business.
Book a demo and we'll show you the ranked, dollar-sized actions for a retailer like you.