A top-tier European rail corporation managing 25,000+ km of track, facing inefficiencies in digitizing legacy rail signaling diagrams.
Challenges Faced
This section outlines the core difficulties and pain points the client was experiencing. It provides context on the hurdles that needed to be overcome before achieving the successful outcome.
Excessive Labor:
100-150 engineer hours per job spent manually converting scanned diagrams.
Error-Prone Processes:
Manual symbol recreation led to accuracy issues and metadata loss.
Unsustainable Costs:
Six-figure annual labor expenses with no scalability.
Stalled Innovation:
Engineers bogged down in tedious tracing instead of strategic design.
Akraya’s Strategic Solution
Akraya’s Team introduced a two‑agent LangGraph workflow which ensured maximum output with least manual intervention.
PaddleOCR & Detectron2 for multilingual text/table extraction and 50+ rail symbol detection (93% F1 accuracy). Converted PDF scans into JSON blueprints with metadata tags.
PyAutoGUI and custom macros to auto-place symbols, snap wires, and populate attributes in AutoCAD. LangGraph orchestration for scalable, fault-tolerant workflows.
Measurable Outcomes
Operational
96% faster conversions (120h → <4h per job); 93% symbol accuracy; zero metadata loss.
Financial
Six-figure annual savings; ROI in <3 months; engineers shifted 90% time to innovation.
Business
Scalable framework for 10x project volume; automated compliance with evolving rail standards.
Conclusion
Akraya transformed manual processes into a hyper-efficient AI-driven pipeline, cutting costs, boosting accuracy, and empowering innovation in Europe's rail modernization.
