How Indiana's Department of Transportation used AI to solve a critical reporting challenge, save 360 labor hours in one week, and set the standard for 60 other state agencies.
Indiana's Department of Transportation faced an impossible deadline. Nine divisions needed to compile comprehensive efficiency reports using scattered policies, varying data formats, and limited time. The work was entirely manual, requiring staff to synthesize information across multiple systems and documents. With the deadline approaching and the volume of work overwhelming, INDOT reached out to identify a solution that could deliver results in days, not weeks.
Scattered Information: Policies and procedures were distributed across multiple documents, some in different formats. No single source of truth.
Tight Timeline: Reports needed to be compiled for nine divisions in a matter of days, not weeks.
Complexity at Scale: Each division had unique circumstances, but the core framework needed to be consistent.
Operational Risk: Any solution had to work within existing systems and security constraints. No experimental tools. No cloud dependencies.
Instead of hiring temporary staff or asking existing teams to work weekends, we deployed a retrieval-augmented generation (RAG) system using Google's Gemini and Vertex AI. The system was trained on INDOT's policy documents and historical reporting structures. It could ingest division-specific data and generate comprehensive draft reports that were accurate, consistent, and ready for executive review.
Rapid Deployment: The system was built, tested, and operational within one week using agile methods and rapid prototyping.
Security First: All processing occurred on-premises within INDOT's secure infrastructure. No sensitive data left the organization.
Human-in-the-Loop: The AI generated draft reports, but human reviewers validated accuracy and context. The system amplified human capability, not replaced it.
The project delivered measurable impact across multiple dimensions:
Deadline Met: All nine divisions delivered draft reports on schedule, with high accuracy and consistency.
Time Savings: What would have taken 360 labor hours (roughly 2 months of full-time work) was completed in one week.
Quality Improvement: Draft reports were more consistent than traditional manual compilation. Fewer errors, clearer formatting, better structure.
Broader Adoption: INDOT's success prompted 60 other state agencies to adopt the same approach for their own reporting challenges.
Google Cloud Recognition: The project was recognized as a significant achievement in practical AI deployment within government.
"The government efficiency report was a novel experience for many on our executive team, demonstrating firsthand the transformative potential of large language models like Gemini. This project didn't just help us meet a critical deadline. It paved the way for broader executive support of AI initiatives that will ultimately enhance our ability to serve Indiana's transportation needs."
Rapid Deployment is Possible: Complex AI projects don't always require long timelines. With clear scope, agile methods, and experienced teams, measurable results can be delivered in days.
Government Can Move Fast: Security and compliance don't require months of delay. On-premises solutions with proper oversight can be deployed quickly within government constraints.
AI Amplifies Human Capability: The most effective government AI implementations keep humans in the decision loop. Technology handles volume and consistency. People handle judgment and context.
Success Creates Momentum: One successful project became the blueprint for dozens of others. Proof of concept is often the biggest hurdle.
For government agencies, nonprofits, and large organizations facing similar challenges:
Explore how AI can address your organization's biggest bottlenecks. No obligation, just clarity on your next steps.
Let's Talk