Inspectors manually reviewed thousand-page construction applications. Now, AI flags code inconsistencies for final human review.
A government urban development inspectorate processes construction applications containing hundreds or thousands of pages of drawings, explanatory notes, and certificates.
Inspectors must manually review these massive document packages under tight deadlines. Even minor inconsistencies, such as a missing file or a...
“It will create equal digital rules of the game for all participants in the process. For the inspector who makes the decision. For the designer who prepares the documentation. For the expert who verifies it. For the developer who orders the construction. Everyone can use the same digital tool to identify inconsistencies with building codes and legislation at an early stage. This is a fundamental change in approach.”
Central executive body for architectural and construction control in Ukraine.
Developed the 'Digital Inspector' AI system for DIAM to verify construction project documentation.
Provided cloud infrastructure with NVIDIA GPUs and architectural expertise for the 'Digital Inspector' project.
State Inspectorate of Architecture and Urban Development (DIAM)'s Document verification is part of this use case:
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Manual extraction took 4 hours per report. Now, AI ingests 3,000 unstructured files to score schools on 14 specific KPIs.
General AI failed to parse 6,000 complex budget codes. A custom model now maps every line to green goals, cutting manual work by 30%.
Document-heavy compliance workflows bottlenecked scale. Now, AI processes routine case documents, routing exceptions to staff.
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.
Inspectors manually reviewed thousand-page construction applications. Now, AI flags code inconsistencies for final human review.
A government urban development inspectorate processes construction applications containing hundreds or thousands of pages of drawings, explanatory notes, and certificates.
Inspectors must manually review these massive document packages under tight deadlines. Even minor inconsistencies, such as a missing file or a...
“It will create equal digital rules of the game for all participants in the process. For the inspector who makes the decision. For the designer who prepares the documentation. For the expert who verifies it. For the developer who orders the construction. Everyone can use the same digital tool to identify inconsistencies with building codes and legislation at an early stage. This is a fundamental change in approach.”
Central executive body for architectural and construction control in Ukraine.
Developed the 'Digital Inspector' AI system for DIAM to verify construction project documentation.
Provided cloud infrastructure with NVIDIA GPUs and architectural expertise for the 'Digital Inspector' project.
State Inspectorate of Architecture and Urban Development (DIAM)'s Document verification is part of this use case:
Related implementations across industries and use cases
Complex math and chemical structures bottlenecked transcriptions. A fine-tuned OCR model now structures this data into ST36 XML.
General AI failed to parse 6,000 complex budget codes. A custom model now maps every line to green goals, cutting manual work by 30%.
Manual extraction took 4 hours per report. Now, AI ingests 3,000 unstructured files to score schools on 14 specific KPIs.
General AI failed to parse 6,000 complex budget codes. A custom model now maps every line to green goals, cutting manual work by 30%.
Document-heavy compliance workflows bottlenecked scale. Now, AI processes routine case documents, routing exceptions to staff.
New agents manually trawled complex file folders for answers. Now, they ask an AI assistant to instantly synthesize multi-source data.
Staff manually cross-checked hundreds of pages. Agents now synthesize technical files to draft environmental analyses.
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.
Pulling answers from a sprawling customer dataset once meant weeks of SQL; now anyone asks in plain language and explores it in seconds.