Shelf Intelligence,
Engineered at Scale
We are a multi-disciplinary team of AI researchers, distributed systems engineers, and retail specialists building the infrastructure that powers modern shelf auditing for the world's largest brands.
Retail Shelf Auditing
Is Broken
Consumer packaged goods companies spend $40 billion annually on field merchandising and shelf auditing. Yet the process remains painfully manual: representatives with clipboards counting products one by one, taking blurry photos, and transcribing data into spreadsheets.
The result? Incomplete data, inconsistent coverage, and weeks of delay before insights reach decision-makers. By then, the shelf has already changed.
Existing computer vision solutions are either too slow for real-time use, too expensive for mid-market brands, or too generic to handle the visual complexity of real-world retail environments.
AI That Sees the Shelf
Retail AI replaces manual shelf audits with a fully automated computer vision pipeline that detects, classifies, and counts every SKU in seconds.
Detect Everything
Our proprietary YOLO-based model detects individual products, shelf facings, and price tags in cluttered retail environments with 97.4% accuracy.
Process Anywhere
Upload images via API, dashboard, or mobile SDK. Process in the cloud on auto-scaling GPU clusters or deploy edge inference for real-time use.
Act on Insights
Get structured JSON results with bounding boxes, confidence scores, and SKU mappings. Integrate directly into your BI tools, ERP, or field force apps.
Numbers That Speak
From Research to Global Scale
Research Phase
Started as a research initiative with a team of computer vision PhDs. Trained first prototype on 50K shelf images from partner supermarkets.
Platform Architecture
Built the inference pipeline with YOLO11, TensorRT, and distributed GPU workers. Designed the credit-based billing system from scratch.
Enterprise Pilot
Launched private beta with 3 major CPG brands across LATAM. Achieved 97.4% detection accuracy on real-world store shelves.
Public Platform
Released the self-serve dashboard, REST API, and SDK. Scaled infrastructure to handle 10K+ images per day with sub-second latency.
Global Scale
Now processing millions of images monthly across 12 countries. Continuous model retraining with federated data from enterprise clients.
Built on Modern Foundations
Every layer of our stack is chosen for performance, reliability, and developer experience.
AI / ML
- YOLO11 (Detection)
- TensorRT (Optimization)
- PyTorch (Training)
- ONNX Runtime
Backend
- Django 5 + DRF
- PostgreSQL 16
- Redis 7 (Cache/Queue)
- Celery Workers
Infrastructure
- Kubernetes
- Docker
- GitHub Actions
- Terraform
Frontend
- Next.js 14 (App Router)
- TypeScript
- Tailwind CSS
- shadcn/ui
Six Specialized Teams, One Mission
Retail AI is the product of dozens of engineers, researchers, and designers working across disciplines to solve one hard problem.
AI Research
8 researchers
Computer vision PhDs and ML engineers building proprietary detection models trained on millions of real shelf images.
Platform Engineering
12 engineers
Distributed systems engineers designing the async inference pipeline, Celery workers, and GPU orchestration.
Frontend & Design
6 designers & devs
Product designers and frontend engineers crafting the dashboard experience with pixel-perfect UI and real-time visualizations.
Data Infrastructure
4 engineers
Data engineers managing the ingestion, annotation, and storage pipeline. S3-compatible object storage with 30-day lifecycle.
DevOps & Security
5 engineers
Infrastructure and security team managing multi-cluster Kubernetes, CI/CD pipelines, and enterprise-grade compliance.
Customer Success
3 specialists
Dedicated team for onboarding enterprise clients, providing API integration support, and building custom inference solutions.
Values We Live By
Accuracy First
Every pixel matters. Our models are trained and validated against ground-truth datasets with sub-percent error margins.
Privacy by Design
No image is retained beyond the processing window. End-to-end encryption. SOC 2 Type II compliance roadmap.
Performance at Scale
Sub-second inference on standard resolutions. Auto-scaling GPU workers. 99.9% uptime SLA for Enterprise.
Developer Experience
Clean REST API, comprehensive docs, SDKs, and responsive support. We obsess over the integration experience.
Transparent Pricing
No hidden fees. Pay for what you use. Real-time credit balance tracking with detailed usage breakdowns.
Continuous Improvement
Models retrain weekly on new data. Your feedback directly improves detection quality for all customers.
Powering Global Brands
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Your Shelf Audits?
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