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Case studies

AI-Powered Time Tracking for Field Teams

How Hendlmaier Timer Replaced Manual Timesheet Entry With Voice-First AI Capture and Smart Property Resolution

Hendlmaier Timer is a time-tracking and task management app for property management professionals. It features AI-powered voice recognition that lets users dictate time entries in natural sentences, automatically filling in fields like property, category, and duration. With dual timers, filters, and local reminder notifications, it streamlines the logging of work hours across multiple properties.

Challenges

Field teams struggled with slow, error-prone manual timesheet entry, and voice transcription often mis-assigned properties due to typos and address variations. Network restrictions caused silent failures, while the admin side lacked visibility into AI errors and tools to manage growing data at scale.

Solutions

We built a comprehensive AI-powered time tracking system combining a voice-first Flutter client with a hardened PHP API and a full-featured React admin dashboard. The solution was designed for real-world field conditions — unreliable networks, locked-down corporate environments, and multilingual teams — with structured AI extraction, robust error handling, and end-to-end observability.

  • Voice-first capture flow with guided timesheet creation, editing, filters, sorting, and search across date, property, and "all" views
  • AI-suggested categories, ratings, transcript field, and in-app stats including today/total duration and session ratings
  • Dual timers, timer auto-resume, and UX safeguards to prevent duplicate submissions after send
  • Fuzzy property resolution with token matching, house number and street suffix normalization, scoring, and alias APIs with validation
  • Structured workflow response types (e.g. Workflow Response) for predictable AI response parsing
  • Request timeouts, consistent error logging, and centralized HTTP client configuration including proxy-aware behavior
  • Proxy support, offline/connectivity detection, and targeted handling for SSL and system clock issues on Windows

Impact

Faster field capture with less typing and clearer session boundaries for payroll and reporting

Fewer mis-assigned timesheets and less manual cleanup in admin through fuzzy property resolution

Reduced "works on my machine" failures on locked-down networks and corporate desktops

Faster, repeatable releases with controlled rollouts via Fastlane and GitHub Actions

Scalable operations with fewer bad records entering the system through validated admin workflows

Ops teams can spot-check and correct AI quality issues systematically rather than via ad-hoc tickets

Technologies we used

People who worked on

Sajath Ahamed

Developer

Ammar Shaffy

Developer

What our
customers say

We adopted the AI-powered time tracking into our own app, leveraging the same voice-first approach behind the Hendlmaier Timer. Our team now just dictates their entries and the AI picks up the project, task, and duration automatically. Timesheet errors have dropped, our developers save time every day, and we finally have accurate data flowing into billing and reporting. It's been one of the best investments we've made in our workflow

Dr. Markus Lehmann

Dr. Markus Lehmann

CEO & Co-Founder BayLanka

Let's talk about your product.

Dr. Markus Lehmann

CEO & Co-Founder BayLanka
markus@baylanka.net

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