Grants and Contributions

The project’s focus is to enhance sales enablement by introducing automation with the purpose of streamlining the buyer’s journey. This will involve testing automation in a CRM with all digital and social media assets, while introducing new processes for content creation. In addition, the firm will be experimenting with packaging and pricing models, in order to gauge buyer demand.

Crafting and executing customer success strategies and procedures to guarantee client contentment and loyalty.

The Enhanced Virtual Machine Streaming project aims to transform access and use of computational resources. It focuses on delivering scalable, efficient, and secure virtual machine streaming services, reducing costs and enhancing user experiences.

As part of the international consortium project "Viral Enhancers - Development of small molecule formulations for enhanced production of AAV", this project will focus on developing and demonstrating at scale small molecule formulation(s) which increase the yield of next-generation gene therapies.

Design mobile app to expand the firm's reach to lower/mid-market and improve services for existing clients

This project entails the engineering design, customization, and integration of a rugged thermal enclosure to house the current Dragon Fire PCB design with increased abilities on electronics platform for the current (OI V01.0).

To enhance SuiteSpot SaaS platform for multi-family property operators which digitizes, automates and improves the efficiency of property maintenance processes with technology. This project would augment SuiteSpot's offering by enabling automatic scheduling of technical staff thus reducing management overhead and increasing the efficiency of the existing workforce.

Jurisage Group aims to solve a crucial pain point faced by lawyers’ legal research and writing workflows by helping them contextualize their research and write legal documents more efficiently with AI/ML-assisted tools. This includes tools for organizing legal research for citation purposes, collaborating with others on citations in documents, and maintaining consistent citations that are acceptable for court filings.

The Project aims at the discovery and optimization of Metal-Organic Frameworks (MOFs) for carbon capture, utilization, and storage (CCUS) applications, particularly focusing on ocean carbon capture and electrochemical CO2 conversion. Leveraging the advanced capabilities of Large Language Models (LLMs) and AI-driven laboratory automation, the Project aims to rapidly identify and synthesize promising MOF candidates, a task traditionally hindered by the vast chemical diversity and slow experimental processes. The Project objective is to develop an LLM/AI driven framework towards MOF discovery, and then apply this framework towards applications in bicarbonate (ocean capture) and electrochemical CO2 reduction. Alongside these performance metrics, the Project will prioritize properties desirable for CCUS applications, such as moisture stability, synthesizability, low-toxicity, and alignment with industry standards. A significant outcome will be establishing a pioneering ML-guided framework for material discovery, contributing a novel dataset to the scientific community, thereby enhancing research and development in CCUS technologies.

The Project aims at the discovery and optimization of Metal-Organic Frameworks (MOFs) for carbon capture, utilization, and storage (CCUS) applications, particularly focusing on ocean carbon capture and electrochemical CO2 conversion. Leveraging the advanced capabilities of Large Language Models (LLMs) and AI-driven laboratory automation, the Project aims to rapidly identify and synthesize promising MOF candidates, a task traditionally hindered by the vast chemical diversity and slow experimental processes. The Project objective is to develop an LLM/AI driven framework towards MOF discovery, and then apply this framework towards applications in bicarbonate (ocean capture) and electrochemical CO2 reduction. Alongside these performance metrics, the Project will prioritize properties desirable for CCUS applications, such as moisture stability, synthesizability, low-toxicity, and alignment with industry standards. A significant outcome will be establishing a pioneering ML-guided framework for material discovery, contributing a novel dataset to the scientific community, thereby enhancing research and development in CCUS technologies.