Client overview

The client is a U.S.-based SaaS operations management platform designed for first responders, including EMS, fire, and police departments. Their cloud-based solution centralizes inventory, narcotics, high-value assets, and fleet maintenance management. By automating supply chain processes and electronic check sheets, the platform keeps emergency teams mission-ready and reduces manual compliance overhead.

Business Challenges

Prior to the implementation of AI, end users encountered challenges in maintaining accurate records for vehicle repairs and facility audits.

➤ Manual Data Entry: Maintenance staff transcribed details from physical invoices or service reports into the system.
➤ Data Neglect: The tedious process led users to skip form entry and attach raw files, resulting in unsearchable data that hindered long-term fleet analysis.
➤ Operational Latency: Data re-entry diverted staff members from essential vehicle maintenance and slowed operations.

Solution

Our approach advanced beyond basic OCR and focused on a sophisticated AI workflow. We created an intelligent assistant that serves as a copilot, allowing users to retain full control while reducing manual effort.

1. The WorkOrder AI Assistant

This expert assistant increases productivity and saves time. When a user uploads a file, such as a vehicle repair invoice, the AI initiates a multi-step process.

Asynchronous Extraction: Users upload a file (PDF, PNG, JPEG, WEBP, or GIF), and processing occurs in the background, enabling continued work on the site.
Contextual Identification: The AI analyzes file content to identify the relevant asset or facility and then suggests the appropriate form from the database.
Intelligent Form Mapping: The system employs multimodal LLMs to extract key values, such as inspection dates or repair results, and map them to the correct field.
UI-Driven Validation: The system pre-fills forms and highlights AI-populated fields. Additional data appears in a sidebar for easy copy-pasting if no direct field is available.

2. Knowledge Base Assistant

To support software adoption, we introduced a knowledge center assistant.

Product Intelligence: This RAG-based chat interface is trained on comprehensive product documentation.
Instant Support: Users can ask questions about platform features in natural language and receive immediate, context-aware responses.

3. Smart Configuration Platform

We developed an internal platform for configuring and tuning agents.

This allows for iterative improvement of prompts and extraction logic.

Value Delivered

Accelerated Backlog Processing: One user cleared a backlog of 50–70 documents that had been ignored for years due to manual entry challenges.
Operational Efficiency: Processing a complex document now takes about one minute and occurs asynchronously, eliminating wait time from the user’s workflow.
Proven Adoption: Around 60 organizations have been actively using these AI features.
Data Quality: By reducing skipped entries, the client now captures structured data for all maintenance events, significantly improving audit readiness.
High Accuracy: Users consistently select the AI’s suggested forms, showing strong alignment between AI predictions and user intent.

Technologies used

We prioritized security and scalability by adopting a microservices-based architecture with AWS.

How AI-Driven Document Automation Accelerated Technology Adoption for EMS Providers