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AI Development Case Studies With Measured Results

Explore our production deployments delivering measurable impact across industries.

Text-to-SQL Business Intelligence Solution: Natural Language Database Querying.
Enterprise SoftwareGENERATIVE AI

Text-to-SQL Business Intelligence Solution: Natural Language Database Querying.

THE PROBLEM

Many businesses depend on databases to manage daily operations. However, extracting useful information from those databases can be difficult for users who do not have technical SQL knowledge.

OUR APPROACH

The proposed solution follows four phases to convert everyday questions into usable database queries while maintaining control over data access and query execution.

Python EngineLangChainLarge Language Models (LLM)FastAPIReact & Next.js

OUTCOME

Data querying: Reduced manual SQL creation

Intelligent PPE Detection & Workplace Safety System: Real-Time Computer Vision Across Active Industrial Jobsites.
ConstructionCOMPUTER VISION

Intelligent PPE Detection & Workplace Safety System: Real-Time Computer Vision Across Active Industrial Jobsites.

THE PROBLEM

The organization had security cameras installed, but passive recording provided zero proactive protection. Safety officers were overwhelmed by manual spot-checks while dangerous areas remained unmonitored during busy shifts.

OUR APPROACH

We designed an efficient system that processes live video feeds on-site to provide instant alerts without internet delays, while sending safety summaries to a central supervisor dashboard.

AI Vision ModelsImage Processing EngineSafety Gear DetectionSafety Rule ValidationWorker Tracking

OUTCOME

Safety gear compliance rate: ↑ 31% increase

Loading & Unloading Monitoring System: Accurate Tracking & Shipment Verification.
Warehouse & LogisticsVIDEO ANALYTICS

Loading & Unloading Monitoring System: Accurate Tracking & Shipment Verification.

THE PROBLEM

Loading docks are busy environments where workers, forklifts, vehicles, and goods move simultaneously. Without proper monitoring, even small mistakes can affect the entire dispatch process.

OUR APPROACH

The proposed solution follows four implementation phases to connect warehouse cameras, item counting, shipment records, and operational reporting.

Python EngineOpenCVYOLO & Object TrackingDirectional CountingReact & Web Dashboard

OUTCOME

Loading and unloading: Reduced manual counting effort

Cement Bag Counting & Dispatch Monitoring System: Real-Time Bag Counting & Automation.
Cement ManufacturingVIDEO ANALYTICS

Cement Bag Counting & Dispatch Monitoring System: Real-Time Bag Counting & Automation.

THE PROBLEM

Manual counting and limited visibility can create difficulties in high-volume manufacturing environments. The solution is designed to address key operational bottlenecks.

OUR APPROACH

The proposed implementation follows a structured approach to ensure that the counting system works reliably within the factory's existing operational environment.

Python EngineOpenCVYOLO & Object TrackingConveyor Line TrackingReact & Web Dashboard

OUTCOME

Bag counting: Less manual counting effort

Construction Quantity & Cost Management Platform: Centralized Real-Time Estimation.
Construction & EngineeringCONSTRUCTION TECH

Construction Quantity & Cost Management Platform: Centralized Real-Time Estimation.

THE PROBLEM

Construction estimation requires teams to work with quantities, materials, rates, calculations, revisions, and project-specific information. As projects become larger, maintaining this information manually can create additional operational effort.

OUR APPROACH

The platform was structured around a four-phase estimation workflow designed to connect project data, quantities, calculations, and cost information.

Web-Based ApplicationResponsive User InterfaceRole-Based AccessProject-Based Data ManagementREST APIs

OUTCOME

Quantity Management: Easier quantity organization

Automatic Number Plate Recognition (ANPR): Real-Time Vehicle Monitoring & Identification.
Smart InfrastructureCOMPUTER VISION

Automatic Number Plate Recognition (ANPR): Real-Time Vehicle Monitoring & Identification.

THE PROBLEM

Vehicle entry and exit areas can become difficult to manage when traffic volumes increase and identification depends heavily on manual checks.

OUR APPROACH

The proposed solution follows four implementation phases to connect camera feeds, vehicle detection, license plate recognition, and centralized monitoring.

PythonOpenCVYOLOOCR EngineTracking Engine

OUTCOME

Vehicle identification: Reduced manual identification

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AtlasML scoped the work honestly, flagged what our data could and couldn't support up front, and delivered on the timeline they committed to. The handover documentation meant our team could maintain it without them.
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Transport Guru
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