AI-Assisted Employee Management and Timesheet Platform for Carrier

Project Title

AI-Assisted Employee Management and Timesheet Platform for Carrier

Short Summary

Built a custom employee management and timesheet platform for Carrier to replace manual Excel-based tracking with a centralized system for logging work, monitoring resource utilization, tracking team efficiency, and analyzing employee contributions across projects, sprints, and Program Increments (PIs). The platform combines React, FastAPI, AWS, Jira integrations, and Gemini AI to provide operational visibility and AI-generated work summaries for management teams.

Overview

Carrier required a more scalable and efficient way to manage employee and contractor timesheets, track work contributions, and monitor team productivity across projects.

Earlier, most teams relied heavily on Excel sheets to log working hours and project activities. This process was manual, inconsistent, difficult to maintain, and lacked visibility for leadership teams. Managers had limited ways to understand what employees worked on during a sprint, a month, or a Program Increment (PI), making it difficult to track efficiency, project allocation, and operational return on resource investment.

Additionally, the existing process could not effectively support Carrier-specific operational workflows, reporting needs, or project structures.

To solve this, we built a custom employee management and timesheet platform tailored specifically for Carrier's internal workflow and resource-tracking requirements.

The platform allows employees and contractors to:

• Log hours against projects or specific project modules

• Split daily hours across multiple workstreams

• Attach Jira tickets and work remarks

• Track contributions over time

• Maintain structured work history

At the management level, the platform provides visibility into:

• Resource utilization

• Project-level investment

• Team efficiency

• Employee contribution tracking

• Work distribution across projects and timeframes

The platform also integrates with Gemini AI to automatically generate human-readable summaries of employee activity for specific days, sprints, or Program Increments.

The Problem

The earlier workflow depended heavily on spreadsheets and manual reporting.

This created several operational challenges:

• Employees manually filled Excel-based timesheets

• Reporting formats were inconsistent across teams

• Managers lacked centralized visibility into employee work

• Tracking sprint or PI-level contribution required manual effort

• Resource utilization was difficult to measure accurately

• Leadership teams could not easily correlate effort with business output

• Jira activity and actual logged work were disconnected

• Historical tracking and reporting became difficult as teams scaled

The organization needed a centralized platform that could support both operational tracking and management-level visibility while adapting to Carrier-specific processes.

The Solution

We designed and developed a centralized employee management and timesheet platform tailored to Carrier's workflow and reporting requirements.

The platform enables employees to:

• Log hours against projects and sub-projects

• Split work hours across multiple tasks or modules

• Add work remarks and implementation notes

• Attach Jira tickets directly to logged work

• Maintain structured work history for reporting and audits

Managers and leadership teams can:

• Track team efficiency across projects

• Monitor employee contribution across sprints and PIs

• Analyze resource utilization

• Measure operational investment against output

• Review work summaries at employee or team level

• Identify workload distribution and delivery trends

The system replaced fragmented spreadsheet-based workflows with a centralized and scalable operational platform.

AI-Powered Work Summarization

To further improve management visibility, we integrated Gemini AI into the platform.

The AI layer analyzes:

• Logged timesheet data

• Jira ticket activity

• Employee remarks

• Sprint and PI data

• Historical work patterns

Using this information, the platform generates concise human-readable summaries describing:

• What a user worked on during a day

• Sprint-level contribution summaries

• PI-level delivery summaries

• Work-distribution insights

• Productivity snapshots

This significantly reduced the manual effort required for management reporting and made employee contribution analysis easier to understand at both technical and leadership levels.

Architecture

The platform was designed using a modern cloud-native architecture.

Frontend

The frontend was built using React and TypeScript.

The UI provides:

• Timesheet logging workflows

• Project and module selection

• Jira ticket integration

• Work-summary management

• Employee and manager dashboards

• Reporting and tracking interfaces

Backend

The backend was built using FastAPI and Python.

The backend handles:

• Timesheet processing

• Resource tracking

• Jira integration

• AI summarization workflows

• Reporting APIs

• Authentication and business logic

Cloud Infrastructure

The platform uses AWS services for:

• Application hosting

• Storage

• Backend infrastructure

• Scalable deployment workflows

Jira Integration

The system integrates directly with Jira APIs to:

• Fetch user ticket details

• Connect logged work with development tasks

• Improve reporting accuracy

• Validate work-tracking data

AI Layer

Gemini AI is used to:

• Analyze logged employee activity

• Summarize contributions

• Generate management-friendly reports

• Convert technical work logs into readable summaries

Key Features

Centralized Timesheet Management

Employees and contractors can log daily work hours in a centralized platform instead of maintaining Excel sheets.

Project and Module-Level Logging

Users can split hours across different projects, modules, or workstreams.

Jira Ticket Integration

Employees can attach Jira tickets directly to work entries for better traceability.

Work Remarks and Activity Tracking

Users can describe completed work alongside logged hours.

Sprint and PI Tracking

Managers can review employee contributions across specific sprints or Program Increments.

Resource Utilization Insights

Leadership teams can monitor spending, allocation, and productivity across resources and projects.

AI-Generated Work Summaries

Gemini AI generates readable summaries of employee activity for selected timeframes.

Management Visibility

Managers gain centralized insight into team workload, contribution patterns, and operational efficiency.

Technologies Used

• React

• TypeScript

• FastAPI

• Python

• AWS

• Jira APIs

• Gemini AI

• Cloud-Native Architecture

• Resource Tracking

• Timesheet Management

Challenges

One of the biggest challenges was designing a system flexible enough to support Carrier-specific workflows while remaining simple for employees to use daily.

The platform needed to support:

• Multiple project structures

• Different reporting requirements

• Flexible hour allocation

• Jira integration workflows

• Role-based visibility

• Scalable reporting

Another challenge was transforming raw employee activity into meaningful management insights.

Simply showing logged hours was not enough. Leadership teams needed a clearer understanding of actual work contribution, sprint participation, and operational value. Integrating AI summarization workflows helped bridge that gap by converting technical activity into understandable business-level summaries.

Ensuring accurate synchronization between Jira activity, timesheet data, and AI-generated analysis also required careful backend orchestration.

Impact

The platform significantly improved operational visibility, reporting efficiency, and resource tracking across teams.

Key outcomes included:

• Eliminated dependency on Excel-based timesheets

• Centralized employee and contractor work tracking

• Improved sprint and PI-level visibility

• Simplified management reporting workflows

• Increased visibility into resource utilization and operational spending

• Connected Jira activity directly with logged work

• Reduced manual effort required for contribution tracking

• Enabled AI-generated summaries for leadership teams

• Improved overall transparency across projects and resources

The system provided Carrier with a scalable internal platform tailored specifically to its operational and reporting needs.

Final Result

The project transformed employee and contractor tracking from a fragmented spreadsheet-driven process into a centralized AI-assisted management platform.

By combining React, FastAPI, AWS, Jira integrations, and Gemini AI, the system gave employees a structured way to log work while providing leadership teams with meaningful operational insights into productivity, project allocation, and delivery performance.

The result was a more scalable, intelligent, and transparent workforce management ecosystem designed around Carrier's internal operational requirements.