Grants and Contributions

This project will develop an innovative AI-powered data extraction vision agent to address the critical lack of integration between different software vendors in pharmacy workflows and integrate this into Medi-scribe's clinical workflow. The module will use an AI vision agent to intelligently capture patient information directly from third-party applications, eliminating manual data re-entry, reducing transcription errors, and enabling richer, more accurate documentation and data extraction.

The Dark Crawler enables the collection and analysis of online data for the purposes of risk assessment, cybersecurity, and commercial applications. This project will enhance the existing software and prepare it for deployment in a pilot initiative, followed by subsequent commercialization.

This project aims to develop next-generation all-solid-state batteries (ASSBs) using hybrid solid-state electrolytes (Hybrid-SSEs) to address critical limitations of conventional lithium-ion battery systems. By embedding high-conductivity ceramics within cross-linked polymer matrices, the project seeks to combine the ionic conductivity of ceramics with the flexibility and processability of polymers. The focus lies in overcoming issues like ceramic brittleness, interfacial instability with Li-metal anodes, and incompatibility with high-voltage cathodes.

This project will develop technologies tailored for space applications, enabling immersive synthetic data generation, simulation, and real-time interaction in extended reality environments. The Mixed Reality platform will support critical use cases across the space sector—including autonomous mission planning, astronaut training, satellite operations, & space sustainability assessments. The platform will provide a spatial computing environment where users collaborate and interact with high-fidelity simulations of spacecraft systems, space asset monitoring and mission workflows. Through these interactive experiences, the platform will generate valuable datasets, to enhance AI models operational readiness, system design, command and control.

Build a hyper automation platform using data science, artificial intelligence (AI), and machine learning (ML) techniques to hyperscale firm’s unique business model and expand by unlocking the predictive and learning capabilities of its data.

BuildBase proposes to develop a Procurement Automation Module to streamline the sourcing, purchasing, supplier and contract management, and cost change processing needs of homebuilders. This module will integrate seamlessly with existing BuildBase ERP modules and automate procurement workflows to reduce cycle times, improve accuracy, and enable near-real-time decision-making. The end-to-end system will empower builders with data-driven tools and automation that replace manual tracking and vendor communication with a modern procurement solution.

The Project will support pilot testing of AI strategies, determine target architecture and quantitative technical objectives for implementation of an AI solution that supports the natural language description of a query to a reporting database.

A software project to enhance the company’s physics-based structural digital twin platform for application to steel structures.

This project explores the market feasibility of enabling privacy-compliant marketing based on verified affiliations instead of personal data.

Enhancement of AI-Powered Script Analysis Module with Advanced Visual Generation.