AI-powered retail decision engine
OMNIA
The operating system for retail performance
📅 2026 👥 Adrien Naeem & Laetitia Lamari 🎯 Enterprise AI SaaS 💰 Seed — €3M
The Problem

Retail is structurally inefficient

Every retailer struggles with the same fundamental issues — and existing tools only address symptoms, not the root cause.

💸

Margin erosion is systemic

Retailers lose 5–15% of margin annually through poor inventory allocation, reactive pricing, and blind spots across channels. With net margins at 3–5%, every point matters.

🧩

Data exists but decisions don't connect

ERP, OMS, POS, e-commerce — data sits in silos. Teams build dashboards but nobody connects insights to action. The gap between "knowing" and "doing" costs millions.

🐢

Decisions are manual and too slow

By the time a pricing decision, stock rebalance, or markdown is validated, the window has closed. Retail moves in hours; decisions take weeks.

🔧

Tools solve pieces, not the puzzle

Every vendor adds AI to their silo — Shopify for e-com, SAP for ERP, Blue Yonder for supply chain. Nobody connects it all into a single decision layer.

The result: Retail leaders fly blind. They have data, dashboards, and teams — but no system to operate the business intelligently.
Timing

Why now

The retail industry is under existential pressure. Three structural shifts create a once-in-a-decade window.

17,000+
Store closures in Europe (2023–2025)
-40%
Average margin decline in mid-market retail over 5 years
$32T
Global retail — still run on spreadsheets and gut instinct
📉

Margin pressure is existential

Inflation, Chinese competition, and channel fragmentation are compressing margins to survival levels. Retailers who don't optimize will not survive the next cycle.

🏗️

Data infrastructure finally exists

Cloud warehouses (BigQuery, Snowflake), semantic layers (dbt), and API-first systems mean data is finally accessible — but nobody is turning it into decisions.

🤖

AI agents can now reason and act

Unlike chatbots, today's AI agents can cross systems, reason on structured data, and propose ranked actions with financial impact. The technology gap has closed.

The window: Retailers are desperate for solutions. The tech stack is ready. The first mover who builds the decision layer wins the category.
The Solution

OMNIA — The Real-Time Operating Layer for Retail

Not dashboards. Not reports. A system to operate the business.

From insight to action — in real time

OMNIA connects all your data sources, reasons across them, and tells you exactly what to do next — with the estimated margin impact.
It's not analytics. It's not BI. It's the operating layer that sits between your data and your decisions.
🔗

Unified performance layer

One system that connects ERP, OMS, POS, e-commerce, supply chain, and market data into a single decision view.

👁️

Real-time visibility

See what's happening across all channels and locations — right now. No waiting for weekly reports or BI team queries.

⚡

Action engine

AI-powered recommendations ranked by margin impact. Every insight comes with a clear next step and its expected financial outcome.

Data sources OMNIA ingests

ERP Systems
Order Management (OMS)
Warehouse Management (WMS)
Point of Sale (POS)
E-commerce Platforms
CRM / CDP
Footfall & Traffic Counters
Staffing / HR Data
Loss Prevention / Shrinkage
Logistics & Carrier Data
Third-party Market Benchmarks

Data Lake / Warehouse

Google BigQuery
Snowflake
Databricks

Semantic Layer

dbt
LookML (Looker)
AtScale
MicroStrategy
What we don't do: CRO. Web personalization. OMNIA focuses on operational profitability & retail decision intelligence.
🔒

Zero-Knowledge Data Processing

No human access to raw client data. All processing is encrypted, anonymized, and fully auditable. Your data never leaves your infrastructure with our self-hosted option.

End-to-end encryption SOC 2 ready On-premise option GDPR compliant
Live Demo
Request a personalized demo with your own data
See OMNIA in action on real retail scenarios — inventory rebalancing, markdown optimization, and margin recovery across channels.
Integration

Plug & play — live in weeks, not months

OMNIA connects to your existing stack. No rip-and-replace. No 12-month integration project.

🔌

Pre-built connectors

Native integrations with Shopify, SAP, Salesforce Commerce, WMS, OMS, and major ERPs. API-first architecture for custom sources.

⏱️

4-week onboarding

From signed contract to first actionable insights in 4 weeks. Data mapping, validation, and first recommendations included.

🏗️

Works with your data layer

Connects directly to BigQuery, Snowflake, Databricks. Supports dbt, LookML, and semantic layers you already use.

No lock-in: OMNIA sits on top of your existing infrastructure. Your data stays yours. Switch off anytime.
Core Engine

11 Performance Drivers

Each driver answers a strategic question, ranked and scored. Organized across 3 pillars of retail profitability.

Demand — 4 drivers
OTB Efficiency
Active
Are we investing inventory budget where it generates revenue?
Assortment Relevance
Active
Does each product earn its shelf space in every location?
Stock-out Impact
Active
Where are we losing sales because shelves are empty?
% Inventory Exposure
Soon
What share of our inventory is actually visible and sellable?
Commerciality — 4 drivers
Price Index
Active
Are we priced right vs. competition in every market?
Retail Network Efficiency
Active
Is every location contributing positively to the P&L?
E-commerce Services
Soon
Are our digital services (C&C, SFS) driving conversion?
Geo-fulfillment Coverage
Locked
Can we reach every customer within optimal delivery windows?
Network Efficiency — 3 drivers
Transportation Spending
Active
Are logistics costs optimized across our distribution network?
Tax Scheme Efficiency
Locked
Are we maximizing fiscal optimization across jurisdictions?
E-retail Relevance
Soon
How effectively do we compete on marketplace visibility?
Strategic Planning

Strategy Builder

Build multi-layer strategies with initiatives, track impact over time, and align operational decisions with business goals.

Quarterly
Quick wins & tactical actions
Full Year
Annual business plan alignment
3 Years
Long-term transformation goals
🎯

Initiative-Based

Each strategy contains concrete initiatives with owners, deadlines, and estimated margin impact.

📊

Impact Synthesis

Real-time aggregated view of expected revenue impact, cost savings, and margin improvement across all initiatives.

🔗

Driver-Linked

Strategies tie directly to Performance Drivers — every initiative connects to measurable KPIs.

Competitive Advantage

The Data Moat

Three layers of proprietary data that no LLM or generic AI tool can access or replicate.

🔐

First-party Client Data

Direct integration with ERP, OMS, POS, e-commerce systems. Real operational data from customer businesses — the proprietary foundation.

📊

Third-party Data & Benchmarks

Price per sqm, market benchmarks, open data, purchased databases. Combined with first-party data to provide contextualized recommendations.

📈

Cross-client Anonymized Benchmarks

Aggregated insights across all OMNIA customers. Network effect: the more clients, the better the benchmarks, creating exponential competitive advantage.

Why OMNIA

Why Claude / ChatGPT can't replace OMNIA

Addressing the #1 investor concern: what's to stop a generic LLM from doing this?

OMNIA's Unfair Advantages
🔐 Proprietary Data
First-party, third-party, and cross-client benchmarks that LLMs have no access to. Data moat compounds daily.
🎯 Vertical Specialization
20+ years of domain expertise baked into the model. Retail decision logic, not generic AI chat.
📊 Network Effect
More clients = better benchmarks = better recommendations. Self-reinforcing competitive moat.
⚙️ Integrated Layer
Connected to actual operational systems (Shopify, SAP, OMS). Not just chat — it orchestrates real action.

Grounded & Ranked Insights

Every recommendation is ranked by estimated margin impact (€K) and grounded with a transparent justification — no black box.

#1
+€340K

Rebalance overstock: Paris → Lyon

Transfer 1,200 units of slow-moving SKUs from Paris flagship to Lyon where sell-through is 3x higher.

Why this ranking: Lyon has 89% sell-through vs. 31% in Paris for this category. Transfer cost is minimal (same logistics hub).
#2
+€210K

Adjust price index: Accessories

Accessory line is priced 12% above market average with declining conversion. A 5% adjustment recovers volume.

Why this ranking: Price elasticity analysis shows 5% reduction yields 18% volume increase in this category.
#3
+€95K

Enable Ship-from-Store: Bordeaux

Bordeaux store has excess inventory and sits within 2-hour delivery radius of 240K online customers.

Why this ranking: Fulfillment from Bordeaux saves €4.20/order vs. central warehouse. Estimated 22K eligible orders/year.
User Architecture

CFO as primary user

OMNIA's user hierarchy: decision-maker at the top, operational teams implementing.

🤖

My Agent — Proactive AI Assistant

OMNIA's AI agent continuously monitors all Performance Drivers and pushes prioritized alerts to each user based on their role. Alerts are classified by severity so teams focus on what matters most.

Critical Attention Opportunity

CFO / Finance Director

Primary user. Logs in daily.
Views margin optimization dashboard → Approves & dispatches recommendations
Retail Director
Executes store initiatives
Head of Logistics
Manages supply chain recommendations
Supply Chain Manager
Implements procurement changes
Category Manager
Owns assortment decisions

Proactive Alert Channels

OMNIA pushes actionable insights directly to your team's existing tools — no need to log in.

📧
Email Digest
💬
Slack
👥
Microsoft Teams
🔗
Webhook / API
Value

Concrete, measurable value

No magic multipliers. Here's what OMNIA delivers in real terms.

📦

Reduce overstock waste

Smart rebalancing across locations reduces dead stock by 15–25%. A €200M retailer saves €300K–€500K annually on inventory alone.

💰

Recover lost margin

Optimized markdown timing and pricing recommendations recover 0.3–0.8% of total margin — that's €600K–€1.6M for a mid-size retailer.

⏱️

Faster decisions, less headcount

Replace 3–5 FTE of manual reporting with automated intelligence. Teams focus on strategy, not spreadsheet wrangling.

ROI: For a €200M retailer, OMNIA delivers €1M+ in annual value from a €120K license — a credible 5–8x return.
Why Us

We are operators, not just builders

OMNIA isn't built by engineers guessing what retail needs. It's built by people who've lived the pain.

🏪

Decades inside retail

Our team has 60+ combined years in retail, e-commerce, and SaaS — from Kering and Lacoste to Salesforce and Adobe.

🔁

Repeat founders

We've built companies before. We know how to go from zero to product-market fit, and how to scale from first client to Series A.

🤝

Direct access to buyers

1,500+ retail decision-makers in our network. Relationships with CFOs and supply chain leaders at top European brands.

The Team

The founding team

Four co-founders with deep retail, tech, and operational expertise.

Adrien Naeem
Adrien Naeem
Co-Founder
Repeat Founder
20+ yrs SaaS — Adobe, Salesforce, Narvar. VP Europe.
Adobe Salesforce Narvar
Laetitia Lamari
Laetitia Lamari
Co-Founder
Repeat Founder
20 yrs global marketing, social & payment solutions.
Marketing Payments Content
Julien Nouet
Julien Nouet
Co-Founder
Repeat Founder
20 yrs e-commerce & omnichannel — Kering, Lacoste.
Kering Lacoste Omnichannel
Bruno Enten
Bruno Enten
CTO
Repeat Founder
Serial tech entrepreneur. Full-stack architecture.
CTO Architecture AI/ML
AwardRanked #1 Ecommerce Influencers in France
Previously co-founded Butterfly Agency (7 years in retail consulting, €0 to ~€1M in 2 years). OMNIA was born from this hands-on operational experience.
Market Opportunity

Addressable market

$32T
Global retail market
3–5%
Average retail net margin
60–70%
Of costs tied to operations
(inventory, pricing, supply chain)
~30%
Of inventory decisions still manual or spreadsheet-driven
OMNIA is built for mid-size retailers that are too complex for spreadsheets but underserved by enterprise software.

< €50M

Simple operations. Limited data. Not priority.

€50M – €1B

Fragmented data. Complex decisions.
→ OMNIA sweet spot

€1B+

Existing enterprise tools. Internal data teams. Longer sales cycles.

Initial focus: Europe (France & UK first), then global. Our network, language capabilities, and retail relationships are strongest in Western Europe. UK expansion in Year 2, global by Year 3.
Expansion

Industry expansion roadmap

Starting with Retail as the anchor market, expanding into adjacent high-margin sectors.

Retail
(Current)
Travel &
Hospitality
B2B
Distribution
CPG &
Manufacturing
Fashion &
Luxury

Relationship Building: Already building relationships in B2B distribution through Salesforce B2B events (Brands to Buyers). The expansion thinking has started.

Positioning

Competitive Landscape

Every platform is adding AI — but only in their silo. Nobody connects it all. OMNIA is the transversal layer.

AI & Reporting
Analytics

Palantir
Snowflake
Tableau
Power BI

Order
Management

Manhattan Associates
Fluent Commerce
Kibo

Warehouse
Management

Blue Yonder
Körber
Manhattan

Supply Chain
Solutions

Kinaxis
o9 Solutions
Coupa

E-commerce
Platforms

Shopify
Salesforce Commerce
SAP Commerce
OMNIA — Transversal Layer
AI Retail Decision Engine that connects across ALL systems
Note: Zipline does next-best-action, but only from their silo data. OMNIA spans the entire retail operation.
Traction

Early market traction

Strong interest from top-tier luxury, retail & lifestyle brands. Contract values ranging from €80K to €160K.

~€1.3M
Qualified pipeline
10+
Enterprise prospects
Coralie Sitbon · Adrien Martin
COO · Head of Digital Operations
~€110K
Giorgia Carastro
VP Commercial
~€145K
Julien Godefroy
Global Planning Director
~€130K
Stéphanie Pigasse
Controlling Director
~€95K
Arnaud Pignerol
Head FP&A
~€120K
Thomas Voisinditlacroix
CDO
~€155K
Imen El Karoui · J. Vallet
Data & AI Director · Korea Supply-Chain Director
~€140K
F. Chancholle
Head of E-commerce
~€105K
Marie Laure Cassé
Marketing & Digital Director
~€125K
Marie Laure Cassé
Ex — Marketing & Digital Director
~€115K
Go-to-Market

Sales motion & network

Leveraging founder expertise and relationships to accelerate enterprise adoption.

🎓

20 Years SaaS Sales

Adrien's experience scaling enterprise SaaS across Europe. Direct B2B sales expertise.

📻

Café de l'E-commerce

Premier e-commerce & retail media in France. Direct channel to top decision-makers.

🤝

Decision-Maker Network

Personal relationships with CFOs, supply chain leaders, and brand CMOs across luxury & retail.

📈

Land & Expand

Personal relationship-driven entry. Expand from initial CFO sponsor to full organization adoption.

Opening is the New Closing

AI spam killed cold outreach. The only way to access decision-makers now is through real human networks.
The juxtaposition: Sales used to be automated → now human again. Margin optimization used to be human → now automated. OMNIA combines both.
1,500+
Decision-makers in WhatsApp community
Tens of thousands
On LinkedIn network
Prestige Collaborations
Store tours with Hermès, consulting with L'Oréal, B2B events at Salesforce
Strategic Focus

Where we focus — and where we're going

We start narrow, go deep, and expand from a position of strength.

Now — Year 1

Inventory & margin intelligence

Optimize stock allocation, markdown timing, and pricing across channels. The biggest pain point for mid-market retailers.

Next — Year 2

Cross-functional decision layer

Expand from inventory to supply chain, store operations, and commercial planning. One system for all operational decisions.

Then — Year 3+

Industry operating system

Network effects kick in. Cross-client benchmarks make OMNIA the industry standard for retail decision intelligence.

Vision

3-Year Vision

Vertical focus first, then expansion.

2026

Launch in Retail (France)

First clients, product-market fit. 3–5 enterprise clients, €400K–€600K ARR.

2027

Scale & Expand

8–12 clients, €1M–€1.5M ARR. Expand to UK. Series A preparation.

2028

Market Leadership

18–25 enterprise clients, €3M–€5M ARR. First moves into adjacent verticals.

Revenue

Commercial Traction Trajectory

€0 €300K €600K €900K €1.2M 0 3 6 9 12 Q3 '26 Q4 '26 Q1 '27 Q2 '27 Q3 '27 Q4 '27 H1 '28 €120K €240K €400K €600K €900K €1.2M 1 2 3 5 8 10 ARR (€) Clients
ARR (€)
Active clients
Business Plan

Business model & projections

Business Model

Enterprise AI SaaS for retail decision intelligence

Annual license€80k–€160k / retailer
UpsellData modules + analytics + enterprise deployment
TargetRetailers & brands €50M–€1B revenue

Pricing Options

Base License
€80K–€160K annual SaaS fee
Performance-Based
Base + % of margin improvement realized

Projections

Y1 — 3–5 clients€400K–€600K ARR
Y2 — 8–12 clients€1M–€1.5M ARR
Y3 — 18–25 clients€3M–€5M ARR

Key Metrics

ACV~€120k
Gross margin~80%
NRR120%+

Client ROI

Average ROI: 5–10x license cost

A €200M retailer recovering just 0.5% margin = €1M/year in additional profit from a €120K license.

Investment

Funding Ask

Raising
€3M
Seed
Runway
18–24
months

Use of funds

70%
Product
20%
Operations
10%
Sales

Path to Series A: Reach €1.5M ARR and 10+ clients within 24 months to trigger Series A round.

Goals

Advisory

The Advisory Board

Guillaume Beaumont
Guillaume Beaumont
CTO Hermès

Ecommerce CTO at CapGemini for 10 years
Anthony Gavin
Anthony Gavin
VP WW for SaaS tech for 20 years
Marie Cappelaere
Marie Cappelaere
Chief Data & AI Officer
Boulanger
Soumaya Hamzaoui
Soumaya Hamzaoui
Co-Founder & CPO/CCO
RedCloud (NASDAQ: RCT)

15+ years in fintech & global commerce. Led product & operations across Africa, Asia & EMEA. Engineering background, serial entrepreneur.
Thomas Voisin dit Lacroix
Thomas Voisin dit Lacroix
VP Global Digital
Lacoste

Led Lacoste Digital Factory. 15+ years driving digital transformation & omnichannel strategy for global retail brands. IMD Business School.

Sources & Backup

McKinsey & Company
Data & Analytics / AI adoption research
Deloitte
Global CIO Survey / Tech Trends
Microsoft
Work Trend Index / Security reports
IBM
Data governance & risk reports
Gartner
Data & Analytics Governance research