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Success story
Intelligent multi-language AI system for automated ESG data extraction from utility bills
To streamline ESG disclosure, a Southeast Asian reporting platform needed to automate the extraction of carbon data from utility bills—despite inconsistent formats, varied languages, and fragmented inputs. Ekimetrics developed a custom GenAI and OCR-based solution capable of handling document diversity at scale, unlocking speed, accuracy, and multilingual flexibility for thousands of SMEs.
99% accuracy
in extracting multi-month metrics in under 30 seconds
Supports 50+ languages
across diverse bill formats
Significant reduction
in manual validation effort through AI-driven accuracy
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What we did
01
Challenge
- Existing OCR engine was limited to one document type and a single carbon metric
- No support for multilingual or multi-format document processing
- Each new document type, metric, or language required high-effort manual retraining of models
- Scaling across SME sectors and regions was constrained by costly and resource-intensive processes
02
Our approach
- Designed a scalable GenAI-powered system to interpret and extract ESG-relevant data from a wide range of document types and languages, reducing dependency on rigid, template-based models
- Implemented smart filtering and structuring logic to ensure only relevant, high-quality data is captured
- Build and deployed the solution on a secure, cloud-based infrastructure ensuring seamless integration and enterprise-grade performance
03
Outcome
- Achieved near-perfect extraction accuracy (99%) significantly reducing manual effort—through the combined power of Azure AI and OpenAI for intelligent document processing
- 50+ language and multi-format support enabled by the flexible model architecture, unlocking adoption across diverse SME sectors and regional markets
- Improved user experience via a drag-and-drop upload interface triggering real-time extraction, powered by the secure and scalable Azure deployment
Challenge
Our approach
Outcome
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