In today’s fast-evolving manufacturing landscape, adopting advanced technologies like artificial intelligence and robotics is no longer optional—it’s essential. For Efalia, a software Publisher, expert in dematerialization of documents and processes, integrating AI into their operations was key to addressing automatic code generation, to generate document templates.
Through their collaboration with AI-Matters and support from CEA-List, Efalia was able to accelerate and standardize their coding processes, achieving measurable results. This is their story.
The Challenge
Every organization embarking on an AI transformation faces unique hurdles. For Efalia, the main challenge was using AI to automate code generation thus allowing, to generate document templates quicker, and in a standardized manner. Additionally, they needed support in exploring what is feasible in code generation and what are the constraints related to the implementation of an AI solution.
The Solution
AI-Matters provided Efalia with the resources and expertise they needed to overcome these challenges. Through an access to state-of-the-art testing facilities and experienced research engineers, a tailormade solution for automatic code generation was developed. This solution respond to a specific use case defined by the two parties and allowed, the organization to test and validate new AI models for production optimization.
The Results
The collaboration between AI-Matters and Efalia delivered tangible outcomes. Some of the key results include:
- Time savings: AI-assisted code writing considerably accelerated the end-to-end process, reducing it by 80%: from 3 hours to just 45 minutes.
- Document analysis: LLM and VLM models were used to analyze and understand input documents in PDF format. Their structure was then transformed into StarPage code, which was validated by the Efalia compiler.
- Standardization and code verification: Product quality has been improved thanks to AI-assisted code generation and a compilation loop to reduce deviations.
Looking Ahead
Looking ahead, Efalia intends to build on the research team’s recommendations by exploring data augmentation to further refine their AI models and pursuing model reduction to better accommodate hardware constraints. These next steps aim to enhance the performance and efficiency of their AI solutions for document comprehension and automated code generation.
Conclusion
CEA-List’s story demonstrates the transformative potential of AI in European manufacturing. By addressing challenges head-on and leveraging the resources of AI-Matters, they’ve paved the way for a future of smarter, more efficient operations.
Is your organization ready to embrace AI? Find out how AI-Matters can support your innovation process.
👉 To find out more, read the detailed article published by Efalia and their feedback on LinkedIn.
