TimeFlow AI

a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk
a computer monitor sitting on top of a wooden desk

What we built: Smarter time tracking for field teams

For field workers, every minute matters. Yet time tracking is often slow, manual, and disconnected from the reality of daily work.

TimeFlow AI was born from a simple but powerful idea: if AI can understand human speech, it can also understand how work actually happens and remove administrative friction from people in the field.

This POC shows how a team can turn a long-standing operational pain point into a natural, efficient, and automated workflow.

The challenge: Manual logs that slow down real work

The demo places us in the daily routine of a construction field worker:

  1. Opening a complex mobile app every day

  2. Manually selecting tasks, phases, and activities

  3. Spending 20 to 30 minutes per day logging time

  4. Making inevitable mistakes, such as forgotten or duplicated entries

  5. Losing 2–3 hours per week to repetitive administrative work

The outcome: inaccurate reports, slow approvals, and limited visibility for managers. The core issue was clear: a process meant to be simple was stealing time, focus, and accuracy.

How we built it: Voice-powered, context-aware time tracking

The team envisioned a system where workers don’t log time, they simply tell it. TimeFlow AI transforms natural speech into structured, validated time entries ready for internal systems. The POC includes:

Voice input with contextual understanding: Workers describe their activity (“Worked on the electrical phase of Project Delta from 8 to 12”), and the AI interprets:

  • Project

  • Work order or phase

  • Duration

  • Delays or anomalies

Automatic time-entry generation: The system:

  • Assigns hours to the correct project and phase

  • Calculates effective time

  • Detects inconsistencies

  • Updates management systems automatically

Adaptive AI processing: TimeFlow AI learns from work patterns and suggests:

  • Likely work orders

  • Frequently used phases

  • Automatic completion when information is missing

Smart verification for managers: The AI validates entries, flags anomalies, and accelerates approvals, reducing administrative load. The guiding idea is simple: let work flow, and let AI take care of the rest.

What changed with this POC: Time tracking that works for people

Thoughtful ideas and purposeful AI can transform an overlooked process into an intuitive, human-centered experience, and deliver clear value:

  • Time logging up to 10× faster through voice input

  • Significant reduction in human error via automated interpretation and validation

  • Lower administrative burden for managers

  • Field workers regain hours to focus on real work

  • A process redesigned around humans, not forms.

The team

Johan Tabori
Johan Tabori

Johan Tabori

DM

Santiago Fuentes
Santiago Fuentes

Santiago Fuentes

Senior Dev

Mariano Brolio
Mariano Brolio

Mariano Brolio

Senior Dev

Jere Lopez
Jere Lopez

Jere Lopez

Senior Dev

Axel Antunez
Axel Antunez

Axel Antunez

Senior Dev

Industries

AI Agents

Construction

Reskilling for the Future

Learning turned into action

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