Manual extraction took 4 hours per report. Now, AI ingests 3,000 unstructured files to score schools on 14 specific KPIs.
A national public administration body monitors Lithuania's education system by collecting annual management reports from thousands of schools and municipalities.
Analysts faced an unsustainable workload processing 3,000 annual reports containing unstructured data across various file types. Extracting raw data...
“This innovative project would not have been possible without S2P’s dedication and expertise.”
Lithuanian government agency managing educational quality, assessment, and curriculum.
Built an AI-enriched automation solution to extract and analyze school report data for NAE.
Enterprise technology and consulting for cloud computing, AI, and business solutions.
National Agency for Education's Report analysis is part of this use case:
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Inspectors manually reviewed thousand-page construction applications. Now, AI flags code inconsistencies for final human review.
Undocumented 1990s systems made upgrades risky. AI reverse-engineered decades of legacy code to map architectures and build modern APIs.
Staff spent 3 hours interpreting text per case. An LLM now classifies goods and validates declarations in seconds.
Staff spent 3 hours interpreting text per case. An LLM now classifies goods and validates declarations in seconds.
Complex math and chemical structures bottlenecked transcriptions. A fine-tuned OCR model now structures this data into ST36 XML.
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Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.
Manual extraction took 4 hours per report. Now, AI ingests 3,000 unstructured files to score schools on 14 specific KPIs.
A national public administration body monitors Lithuania's education system by collecting annual management reports from thousands of schools and municipalities.
Analysts faced an unsustainable workload processing 3,000 annual reports containing unstructured data across various file types. Extracting raw data...
“This innovative project would not have been possible without S2P’s dedication and expertise.”
Lithuanian government agency managing educational quality, assessment, and curriculum.
Built an AI-enriched automation solution to extract and analyze school report data for NAE.
Enterprise technology and consulting for cloud computing, AI, and business solutions.
National Agency for Education's Report analysis is part of this use case:
Related implementations across industries and use cases
Inspectors manually reviewed thousand-page construction applications. Now, AI flags code inconsistencies for final human review.
Undocumented 1990s systems made upgrades risky. AI reverse-engineered decades of legacy code to map architectures and build modern APIs.
Staff spent 3 hours interpreting text per case. An LLM now classifies goods and validates declarations in seconds.
Staff spent 3 hours interpreting text per case. An LLM now classifies goods and validates declarations in seconds.
Complex math and chemical structures bottlenecked transcriptions. A fine-tuned OCR model now structures this data into ST36 XML.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Teams manually monitored 395km of track. Now, AI predicts faults like wire sagging in real time, targeting 20% less downtime.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.