<500ms

The Future Of
Retail Intelligence
Starts Here

RetailBrain OS transforms fragmented retail data into real-time operational intelligence, predictive actions, and margin-driven execution across every store.

RetailBrain OS Dashboard
The Problem We Solve

UK Retail Is Data-Rich,
Action-Poor

The UK retail sector hemorrhages margin through delayed decisions, siloed data, and reactive operations. RetailBrain OS transforms this from a reporting culture to an execution powerhouse.

£40M
Annual "shadow loss" per large organisation due to decision latency
British Retail Consortium · 2025
£5B
Rise in UK retail employment costs from NI and minimum wage increases
UK Government · 2025
29%
Of retail initiatives executed correctly at store level without AI precision
Deloitte Retail Report · 2024
$634B
Global cost of stock-outs caused by fragmented inventory decision-making
IHL Group Research · 2024
How It Works

Sense. Simulate.
Act.

RetailBrain OS orchestrates the full commercial cycle from raw data ingestion to prescriptive front-line action in under 500ms.

Data Ingestion
Step 01

Data Ingestion

POS, ERP, WFM and inventory streams are ingested and anonymised in real-time via Apache Kafka pipelines before AI processing.

Economic Decision Graph
Step 02

Economic Decision Graph

Graph Neural Networks model SKU-store-brand relationships and predict propagation effects across the retail estate.

Counterfactual Simulation
Step 03

Counterfactual Simulation

Thousands of Retail Economic Twin scenarios run in parallel to determine the highest-margin operational path.

Precision Tasking
Step 04

Precision Tasking

Front-line teams receive real-time operational directives while headquarters monitors enterprise-wide performance.

Core Platform

The Economic
Operating System

RetailBrain OS is the only platform that synchronises markdowns, inventory transfers, and labour allocation within a single, unified decision logic delivering "Next Best Action" to every product in every store in under 500ms.

Core Engine

Economic Decision Graph

Our proprietary GNN-based engine models non-linear interdependencies across SKU, store, and brand levels capturing propagation effects before they occur.

Unlike traditional silos, the EDG captures how a pricing decision in one SKU affects inventory across related brands and labour in neighbouring territories. Built on PyTorch and Deep Graph Library, it processes 1M+ SKU-store combinations per second with sub-500ms decision latency.
Simulation

Counterfactual Retail Twin

Run thousands of "what-if" scenarios in parallel before physical execution. Compare markdown vs. stock transfer vs. labour reallocation with quantified probability scores.

The Economic Twin reduces the 71% failure rate associated with store-level initiatives by simulating outcomes digitally first. GAN-based synthetic scenario generation addresses cold-start problems for new products and unprecedented market shifts.
Proprietary Metric

Explainable Inaction Costing

A unique mathematical framework that quantifies the daily financial penalty of "doing nothing" for every SKU transforming the platform from a dashboard into a commercial necessity.

The EIC algorithm calculates the "shadow loss" of delayed decisions with 92% accuracy. Every alert is backed by transparent economic logic aligned with ICO guidance on AI transparency, solving the "black box" trust gap at the store level.
Security

Zero-Trust Edge Architecture

Operates autonomously within stores when cloud connectivity fails. All commercial logic encrypted and processed locally "blackout-proof" retail intelligence.

Deployed via Docker and Kubernetes on NVIDIA Jetson or Raspberry Pi 4+ edge nodes, the system maintains millisecond-level inference without constant cloud pings. Compliant with PCI DSS, GDPR, and EU AI Act 2024 with end-to-end Zero-Trust encryption.
Learning

Action-Response Memory Loop

A continuous agentic learning engine that tracks every intervention's outcome, refining future recommendations based on real-world execution accuracy.

The reinforcement learning mechanism adapts to seasonal shifts and evolving UK consumer behaviour without requiring manual retraining. The "Speed of Culture" loop ensures the AI remains relevant to changing market conditions automatically.
Front-Line

Precision Tasking Interface

Store managers receive clear, data-backed directives via React Native mobile interface. Central teams see a Control Tower for group-wide strategic oversight.

Examples include: "Shift labour to Beauty Aisle: 15% demand surge predicted for 2 PM" or "Markdown SKU 4821 by 20% before 5 PM: £340 inaction cost per hour." All high-impact recommendations require manual validation by authorised store managers.
Sector Modules

Purpose-Built for
Every Retail Tier

Data Ingestion
Module 01

Grocery & Perishables

Shelf-life decay logic and footfall pattern analysis for automated markdown timing. Reduces food waste by 15–20%, supporting Net Zero commitments.

Economic Decision Graph
Module 02

Fashion & Apparel

Seasonal markdown curves, size-cluster optimisation, and regional demand sensing for fashion retailers managing high-velocity SKU turnover.

Counterfactual Simulation
Module 03

Enterprise Multi-Brand

Group-wide margin control across multi-territory estate. Prevents "local wins" from becoming "global losses" via cross-brand propagation modelling.

Precision Tasking
Module 04

Boutique & Specialist

High-end analytics typically reserved for enterprise giants, democratised for boutique groups at accessible pricing. Protects brand value through precision.

Technology

Enterprise-Grade
Infrastructure

AI & ML

Core AI Stack

PyTorch · Deep Graph Library · CausalML · NVIDIA H100 GPU clusters · Google Cloud TPUs · GAN-based scenario synthesis

Infrastructure

Cloud & Edge

GCP + AWS hybrid · Azure UK South · Docker + Kubernetes · NVIDIA Jetson edge nodes · Apache Kafka + Airflow pipelines

Security & Ops

Compliance Layer

Zero-Trust architecture · AWS KMS encryption · ISO/IEC 27001 · PCI DSS · GDPR anonymisation · Prometheus + Grafana monitoring

About RetailBrain OS

Built by Retail Veterans.
Powered by Causal AI.

RetailBrain OS was born from a systemic frustration. After 15+ years of managing high-volume flagship retail operations, our founders identified a persistent "Execution Gap" the inability of retail groups to convert vast operational data into precise, cross-functional commercial actions.

Recognising that retailers were "data-rich but action-poor," we built a decision-intelligence layer capable of running a retail group on Autopilot combining causal ML, graph neural networks, and counterfactual simulation into a single, unified platform.

Engineered entirely in the UK, RetailBrain OS is fine-tuned for the post-2024 "Workforce Reckoning" where rising NI contributions and minimum wage costs have made manual trading teams a luxury no retailer can sustain.

Execution Gap Analysis · UK 2026
Inaction Cost ID
92%
Decision Latency
<500ms
vs Manual Analysis
+60%
System Uptime
99.95%
TRL 7
Prototype demonstrated in operational environment
Oxford St. Flagship Stress Test
£131.5M
Total Addressable Market across UK retail tiers
Internal TAM Analysis · 2026
168
Institutional clients required to reach £1M ARR
ARPU Model · £4,974/yr
4,800+
Viable retail groups in the UK addressable market
UK Retail Data · 2025
Founding Team

Retail Expertise Meets
Deep Data Science

The combination of senior operational retail leadership and advanced data science is what makes RetailBrain OS uniquely defensible the AI logic genuinely understands physical retail constraints.

NR
Nagaraju Reddyraju
Founder & CEO

15+ years of multi-site and flagship leadership across high-volume premium retail. Currently leading multi-concept operations at the Marks & Spencer Oxford Street flagship. His deep expertise in P&L management, labour cost control, and inventory optimisation drives the platform's "Operational Common Sense."

Marks & Spencer Landmark Group P&L Leadership 15+ Years Retail
PD
Preethi Debli
Co-Founder & Lead Developer

MSc Data Science and Full-Stack Developer with 8+ years designing scalable, high-performance enterprise applications. Engineered the GNN-based Economic Decision Graph, the Zero-Trust Edge synchronisation layer, and the "blackout-proof" offline functionality. Manages Azure/AWS cloud infrastructure and Kubernetes orchestration.

MSc Data Science GNN Architecture Zero-Trust Systems Cloud Engineering
Vision & Mission

Transforming Global Retail Into Autonomous, Margin-Secure Operations

Vision: To transform global retail management into an autonomous, proactive, and margin-secure operation through prescriptive AI that empowers every front-line decision.

Mission: To pioneer the retail "Economic Operating System," empowering multi-brand groups to bridge the execution gap through Causal AI, Zero-Trust Edge intelligence, and mathematically vetted prescriptive tasking.

£4.8B
UK retail tech market projected by 2028 at 7.2% CAGR
$45B
Global AI in retail market projected by 2030
1,000+
Target organisations for global market dominance by Year 5
£3.2M
Projected Year 5 revenue under SaaS model
Market Intelligence

A £131.5M Market.
Zero Unified Prescriptive Layer.

The UK retail decision intelligence market is wide open. While incumbents offer descriptive dashboards or siloed supply chain tools, no platform delivers unified prescriptive execution across pricing, inventory, and labour until now.

UK Decision Latency Sources (%)
2026 Data
Retail AI Value Gap Breakdown
Root Causes
Competitive Landscape

No Unified Prescriptive
Platform Exists

Analysis of competitors reveals none combine causal counterfactual simulation with real-time labour-margin orchestration in a unified Zero-Trust framework the RetailBrain OS whitespace.

Feature RetailBrain OS (UK) Blue Yonder (USA) RELEX (Finland) SymphonyAI (USA) Nextail (Spain)
Sub-500ms Prescriptive Actions ✓ ✗ Batch ~ Intra-day ~ Cloud ~ Periodic
Zero-Trust Edge / Offline Resilience ✓ ✗ ✗ ✗ ✗
Explainable Inaction Costing (EIC) ✓ ✗ ✗ ~ ✗
Labour + Inventory + Pricing Unified ✓ ~ ✗ ~ ✗
GNN Causal ML Architecture ✓ ✗ Heuristics ✗ Rule-based ~ Neural ✗ Algorithmic
EU AI Act 2024 Explainability ✓ Built-in ~ ~ ✗ ✗
Entry Pricing (Monthly) £149/mo £100k+/yr Project-based Enterprise only £30k+/yr
Competitive Radar
Competitive Capability Comparison
RetailBrain leads
Market Growth
UK & Global RetailTech Market Growth
Platform Capability Scoring (vs. Peers)
Technology

The Science Behind
Prescriptive Retail AI

RetailBrain OS combines three breakthrough AI disciplines Causal Machine Learning, Graph Neural Networks, and Generative Adversarial simulation into a single real-time orchestration layer. Here's what powers it.

Core Intelligence

Causal Machine Learning

Unlike correlation-based models, our causal inference engine understands why sales patterns shift enabling true counterfactual reasoning. It answers "what would have happened if we acted differently?" before you commit resources.

CausalML DoWhy Framework Counterfactual Graphs
Decision Architecture

Graph Neural Networks

GNNs model the non-linear web of dependencies across SKUs, stores, and brands capturing how a pricing change in one aisle propagates across the entire retail estate. Processes 1M+ SKU-store combinations per second.

PyTorch GNNs Deep Graph Library <500ms Inference
Scenario Engine

Generative Adversarial Networks

GANs solve the "cold start" problem by generating high-fidelity synthetic retail scenarios simulating Black Swan events, new product launches, and hyper-local demand shocks before real data exists.

Synthetic Data Moat Economic Twin Black Swan Resilience
Add-Ons & Extensions

Extend Your
Intelligence Layer

RetailBrain OS is modular by design. Bolt on sector-specific modules, integrate via API into your existing tech stack, or deploy physical edge nodes each extension deepens your prescriptive capability without disrupting what already works.

Sector Module

Grocery Module

Shelf-life decay logic and footfall pattern analysis for perishables. Automates markdown timing to reduce food waste by 15–20% and supports Net Zero ESG reporting.

£1,200/year
Sector Module

Fashion Module

Seasonal markdown curves, size-cluster optimisation, and trend velocity tracking tailored for fashion and apparel retailers managing high-velocity SKU turnover.

£999/year
Precision Tasking
Operational Add-On

Labour Orchestration

Advanced algorithmic shift-scheduling aligned with predicted demand surges. Eliminates 15–25% of wasted paid hours caused by operational friction and misaligned rotas.

£850/year
API & SDK Licensing
Integration

API & SDK Licensing

Embed RetailBrain's prescriptive "Inaction Costing" logic into third-party WFM, logistics, or warehouse automation systems via our API or developer SDK.

£0.05–0.15
per action · SDK license £5–10k/yr
Zero-Trust Edge Nodes
Hardware

Zero-Trust Edge Nodes

Pre-configured Edge-AI processors for store clusters. Includes the Zero-Trust secure hardware bridge, local inference engine, and 1-year maintenance for true blackout-proof resilience.

£4,500
per node incl. VAT · bundle discounts for 10+
Certification Programme
Training

Certification Programme

Operational certification for Area Managers and Store Heads. Ensures your leadership team can fully leverage prescriptive directives and maximise ROI from day one.

£1,500–£4,000
per group annually · scales with team size
Build on RetailBrain OS

Developer Partner Programme

Access our SDK documentation and sandbox environment to embed RetailBrain's Inaction Costing logic into your platform. Partner integrations include Digital Catapult, Oracle, SAP, and Blue Yonder connectors.

Democratised Intelligence

Pricing Built for
Every Retail Tier

90% more cost-effective than traditional enterprise consulting. Our democratised pricing model ensures access to world-class AI for boutiques and enterprise groups alike.

All plans include GDPR compliance, ISO 27001 alignment, and dedicated onboarding support
Specialised

Boutique & Specialist

For independent retailers, luxury boutiques, and niche multi-brand groups.

£149/mo
£1,000/month · £12,000/year billed annually
  • Core Economic Decision Graph access
  • Real-time prescriptive tasking
  • Up to 5,000 SKU-store combinations
  • Mobile Precision Task interface
  • Standard support (48hr response)
  • Counterfactual simulation layer
  • Custom sector modules
  • White-label interface
Most Popular
Professional

Mid-Market Chains

For regional chains seeking full simulation and labour orchestration capabilities.

£2,900/mo
£35,000/year · save 17% vs monthly
  • Full Economic Decision Graph
  • Counterfactual simulation layer
  • Up to 100,000 SKU-store combinations
  • Cloud analytics and reporting
  • Priority ERP integration support
  • Labour Orchestration add-on (£850/yr)
  • Fashion or Grocery module (£999/yr)
  • White-label interface
Enterprise

Major Retail Groups

For Tier-1 multi-brand groups and international conglomerates requiring full-stack deployment.

£12,500/mo
£150,000/year · multi-site licensing
  • Full API integration suite
  • White-label Precision Task interfaces
  • Unlimited SKU-store combinations
  • 24/7 strategic support
  • Zero-Trust Edge-AI hardware nodes
  • Custom ERP connectors (Oracle, SAP)
  • All sector modules included
  • Dedicated implementation lead
Ultra-Enterprise

Grocery & Perishables

Ultra-enterprise logic for high-volume grocery networks with decay-sensitive supply chains.

£41.6K/mo
£500,000/year · national network pricing
  • Shelf-life decay and footfall logic
  • Automated markdown trigger system
  • GS1-compliant data exchange
  • ESG and Net Zero reporting
  • Robotic fulfilment API integration
  • Multi-site edge node deployment
  • Regional distribution optimisation
  • Quarterly performance reviews
Add-Ons & Extensions

Extend Your
Intelligence Layer

API Licensing

API & SDK Access

£0.05–0.15 per action recommendation · SDK developer license £5,000–£10,000/yr for third-party WFM and logistics platforms.

Hardware

Edge-AI Nodes

£4,500 per node (incl. VAT) · Zero-Trust secure hardware bridge, local inference engine, 1-year maintenance included.

Training

Certification Programme

£1,500–£4,000/year per group · Operational certification for Area Managers and Store Heads to maximise platform utilisation.

Common Questions

Frequently Asked
Questions

Standardised API connectors are ready for Oracle Retail, SAP, and Blue Yonder. For other systems, our ETL pipeline adapts within 2–4 weeks. Most clients see their first live prescriptive action within 30 days of kickoff.
Our Zero-Trust Edge Architecture means each store runs its own local inference engine. Commercial decisions continue without interruption the system is "blackout-proof" by design, not a cloud-dependent add-on.
A dashboard tells you what happened. Inaction Costing tells you what it costs per hour to not act for every SKU, in every store. This transforms optional analytics into a quantified financial imperative that drives immediate action.
Yes. Every recommendation is backed by an explainable economic "Why" aligned with ICO transparency guidance. Our compliance strategy includes UKCA/CE certification, ISO 27001, PCI DSS, and GDPR, with human-in-the-loop validation for all high-impact actions.
We require POS transaction history (min. 12 months), current inventory data, and basic labour schedule exports. Our GAN-based synthetic data engine can supplement gaps in historical data during the onboarding phase.
Enterprise and Grocery tiers include unlimited SKU-store combinations with volume-based API pricing (£0.05–0.15 per action). Multi-site hardware node bundles are available with discounted pricing for 10+ locations.
Knowledge Base

Everything You Need
to Know

Answers to the most common questions about RetailBrain OS from technical integration to pricing, compliance, and deployment timelines.

🔍
Standardised API connectors are ready for Oracle Retail, SAP, and Blue Yonder. For other systems, our proprietary ETL pipeline adapts within 2–4 weeks. Most clients receive their first live prescriptive action within 30 days of kickoff. We provide a dedicated implementation lead and full technical documentation throughout.
We have standardised connectors for Oracle Retail, SAP, Blue Yonder, Lightspeed, and Deputy. For workforce management, we integrate with most major WFM platforms via our FastAPI backend. Our GS1-compliant data exchange layer ensures compatibility with legacy ERP systems, and our ETL pipeline cleanses and normalises fragmented data before it reaches the AI engine.
We require POS transaction history (minimum 12 months), current inventory levels, and basic labour schedule exports. Our GAN-based synthetic scenario engine supplements gaps in historical data during onboarding, solving the cold-start problem for newer product lines or recently opened stores. All data is anonymised before processing.
Yes. Our Developer Partner Programme provides SDK documentation, a sandbox environment, and API access at £0.05–0.15 per prescriptive action recommendation. SDK developer licenses start at £5,000–£10,000/year. This enables third-party logistics platforms, WFM providers, and warehouse automation systems to embed our Inaction Costing logic natively.
RetailBrain OS is built on a Privacy-by-Design architecture. All personnel and performance data are anonymised before AI processing via proprietary ETL pipelines that strip PII from labour logs. We adhere to UK and EU GDPR data minimisation principles, maintain a completed DPIA for store-level personnel data, and store all enterprise data in encrypted UK-based sovereign data centres.
Yes. Every recommendation is backed by an explainable economic "Why" aligned with ICO guidance on AI transparency and the EU AI Act 2024 explainability requirements. Our Explainable Inaction Costing layer ensures no "black box" decisions. All high-impact recommendations require manual verification by authorised store managers before execution (human-in-the-loop).
Our Zero-Trust Edge Architecture means each store runs its own local inference engine on NVIDIA Jetson or Raspberry Pi 4+ hardware. Commercial decisions continue without interruption there is no dependency on constant cloud connectivity. The system is "blackout-proof" by design, not a cloud-dependent add-on. Local data is encrypted end-to-end and synchronised securely when connectivity resumes.
RetailBrain OS is aligned with ISO/IEC 27001, PCI DSS, GDPR, and NCSC Cyber Essentials Plus standards. AWS KMS encryption is applied at rest and in transit. We conduct biannual internal compliance audits and annual third-party penetration testing. UKCA and CE certification submissions are targeted for Q4 2025 to support enterprise deployment.
RetailBrain OS offers four SaaS tiers: Specialised (£149/mo) for boutiques, Professional (£2,900/mo) for mid-market chains, Enterprise (£12,500/mo) for major groups, and Grocery/Ultra-Enterprise (£41,600/mo) for national supermarket networks. Annual billing provides further savings. All tiers include GDPR compliance, ISO 27001 alignment, and onboarding support.
Enterprise and Grocery tiers include unlimited SKU-store combinations with volume-based API pricing (£0.05–0.15 per action recommendation). Multi-site hardware node bundles are available with discounted pricing for 10+ locations. Custom framework agreements are available for Tier-1 retail groups with 100+ stores contact our sales team for a bespoke proposal.
Yes. Our UK Pilot Programme provides a bespoke "Inaction Cost" audit using your own anonymised historical data before you commit to any subscription. We provide a validated margin recovery report at 90 days. If RetailBrain OS doesn't demonstrate measurable ROI during the pilot, you pay nothing beyond the pilot fee. Contact us to apply.
A dashboard tells you what happened last week. Inaction Costing tells you what it costs per hour to not act right now for every SKU, in every store. The EIC algorithm calculates the "shadow loss" of delayed decisions with 92% accuracy, quantifying the daily financial penalty of keeping an underperforming item on shelf versus acting. This transforms optional analytics into a quantified financial imperative.
Our Graph Neural Network models retail as a connected network each SKU, store, and brand is a "node," with relationships (sales velocity, stock levels, labour capacity) as "edges." This allows the system to understand how a pricing change in one aisle propagates across the entire estate before you action it. Built on PyTorch and Deep Graph Library, it processes 1M+ SKU-store combinations per second.
Generative Adversarial Networks (GANs) solve the "cold start" problem in retail AI when you launch a new product or face an unprecedented market event, there's no historical data. Our GAN engine creates high-fidelity synthetic retail scenarios to train the model on situations it hasn't yet encountered, including "Black Swan" events like hyper-inflation, rapid supply chain collapse, or new product demand patterns.
Yes. The Action-Response Memory Loop is a continuous reinforcement learning engine that tracks whether each recommended action (e.g., a specific markdown) achieved its predicted outcome. It automatically refines future models based on real-world execution accuracy adapting to seasonal shifts and changing consumer behaviour without manual retraining by your team.
For standard ERP integrations (Oracle, SAP, Blue Yonder), first live prescriptive actions appear within 30 days. Edge-AI node deployment for physical stores adds 1–2 weeks for shipping and configuration. A full enterprise rollout across multiple sites typically completes within 60–90 days, including model calibration, staff training, and compliance documentation.
For blackout-proof offline operation, we deploy pre-configured Zero-Trust Edge-AI nodes (NVIDIA Jetson Orin or Intel Xeon-based edge servers). These are £4,500 per node (incl. VAT) and include the Zero-Trust secure hardware bridge, local inference engine, and 1-year maintenance. For cloud-only operation (Professional tier and above), no additional hardware is required beyond your existing handhelds and POS terminals.
All plans include onboarding support and access to our Precision Tasking mobile interface documentation. Our Operational Certification Programme (£1,500–£4,000/year per group) trains Area Managers and Store Heads to maximise prescriptive intelligence from day one. Enterprise clients receive a dedicated implementation lead, 24/7 strategic support, and quarterly performance reviews.
RetailBrain OS has reached TRL 7 (System Prototype Demonstrated in Operational Environment), validated through stress-testing in simulated high-volume flagship environments modelled on Oxford Street sites. The system maintains 92% Inaction Cost identification accuracy, sub-500ms decision latency, and 99.95% uptime. We are targeting TRL 8 status with financial proof-of-concept in live pilot stores by mid-2026.
Still Have Questions?

Talk to Our Team Directly

Our implementation leads are retail and data science experts. We'll answer any technical, commercial, or compliance question and can run a bespoke Inaction Cost audit on your anonymised data.

Get Started

Request Your
Pilot Programme

Join the UK's first cohort of retailers deploying prescriptive AI at the store-floor level. Request a bespoke "Inaction Cost" audit using your own anonymised data and see your margin recovery opportunity before you commit.

Pilot Application Form

What Happens Next?

After submitting your application, a RetailBrain OS implementation lead will contact you within 48 hours to:

Schedule a discovery call with your trading team
Request anonymised historical POS data for audit
Deliver a bespoke Inaction Cost report within 2 weeks
Agree pilot scope, timeline, and success metrics

Get in Touch Directly

theretailbrainuk@outlook.com
London, United Kingdom
Response within 48 business hours

Pilot Programme Guarantee

Our pilot programme is designed for zero-risk evaluation. We provide a validated margin recovery report at 90 days. If RetailBrain OS doesn't demonstrate measurable ROI, you pay nothing beyond the pilot fee.

90-Day ROI Report No Lock-In GDPR Compliant
30
Days to first live prescriptive action from integration
£149
Entry tier per month — cheaper than one analyst hour daily