Case Studies
Explore our success stories and learn how we’ve helped businesses achieve their goals.
Embross Case Study
Embross sought to upgrade their baggage scanning system with a more efficient and accurate solution. Citric Sheep developed an AI-powered system that replaced their four-camera setup with a single, intelligent camera. This system uses advanced computer vision to provide real-time suitcase sizing, fraud detection, and IATA compliance monitoring. Deployed in Brisbane Airport, this solution enhances efficiency, accuracy, and safety.
Key Highlights:
- Replaces a four-camera setup with a single AI-powered camera.
- Provides real-time suitcase sizing with high accuracy.
- Enables fraud detection and IATA compliance.
- Enhances safety with anomaly detection.
CarbonHQ Case Study
CarbonHQ needed a solution to automate the extraction of data from complex carbon credit accreditation documents. Citric Sheep developed an AI-powered system using the latest GPT/LLM technology to automatically process these documents. This solution provides CarbonHQ’s clients with real-time updates on their project’s accreditation, ensuring efficiency and accuracy. The AI parser is versatile, compatible with various document types, and can be deployed in the client’s cloud environment.
Key Highlights:
- Automates data extraction from PDF and DOCX files.
- Provides real-time updates on accreditation allocations.
- Handles various document types and methodologies.
- Offers flexible deployment options.
Joe Case Study
Joe’s company, involved in day-ahead electricity markets, needed a weather prediction model for daily, 48-hour forecasts to inform their AI bidding algorithms. Citric Sheep delivered a solution that backtested two years of data (2022-2023), automated ERA5 seed data collection, and interpolated the data to Joe’s specifications. This allows Joe’s team to assess prediction accuracy against other data and ensures confidence in the model’s viability.
Key Highlights:
- Developed a 48-hour weather prediction model.
- Backtested with two years of observational data.
- Automated data collection and processing.
- Improved prediction accuracy.
- Cost-effective solution.
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