Projects

To address OSHA's stringent equipment inspection documentation requirements and streamline the maintenance reporting process, our team developed an innovative mobile app. This app empowers operators to easily report on the condition of equipment through voice messages and photographs, ensuring real-time, accurate maintenance updates.

A leading US construction entity grappled with ensuring the timely availability and operability of equipment. TeamArt rose to the occasion with a cloud-based application, replete with real-time monitoring and image analysis features. This solution optimized equipment readiness, fostering efficient project executions.

In the rapidly evolving healthcare sector, the demand for digital solutions that streamline patient-doctor interactions and facilitate remote consultations has been on the rise. Addressing this need, a UK-based healthcare provider sought to develop a mobile application that leverages a chatbot for initial assessments and information collection, enabling efficient matching of patients with relevant medical professionals.

Confronted with the cumbersome nature of manual, paper-driven dispatching processes for over 280 FTEs, a US construction company sought to digitize and streamline its operations. TeamArt devised an Amazon event-driven application, integrating it with the Twilio communication API, enabling enhanced communication, automatic SMS notifications, and streamlined reporting.

The transition from paper to digital was the primary goal of a US logistics firm. TeamArt catered to this need by designing a mobile app, enabling dispatchers and truck drivers to seamlessly assign and accept jobs. The solution streamlined operations, offering real-time GPS-based tracking and enhanced communication.

TeamArt was approached to develop a sales enablement tool with a focus on self-service and stellar graphic design. Leveraging Outsystems, a low-code/no-code platform, TeamArt produced 'Bizbridge', a tool adept at scraping data from public sites, extracting key information, and providing users with intuitive visuals.

We created a machine learning-powered solution for automated people counting in public venues. The system uses computer vision and edge device hardware to count the number of people on-premise in real-time, while ensuring privacy compliance.

We designed a machine learning-powered web scraper to extract key data from diverse company websites. Using natural language processing (NLP) techniques, the system quickly identifies and gathers high-value information from web pages.

We developed an AI-powered system that optimizes container tracking and positioning at busy port terminals. The system uses a combination of computer vision and virtual mapping to track containers in real-time and assign optimal retrieval paths.

We developed a machine learning system that uses photogrammetry and computer vision to create high-fidelity 3D models of industrial objects. The system accurately identifies objects from over 1,000 categories, even under challenging conditions like low visibility or partial damage.