Data Matrix

Data MATRIX process data, analyse it and develop documents to be accepted by the Ministry of Health of Russia, FDA (USA), and EMA. Our products automate the processes of clinical trials; the users manage and monitor its progress online. We adjust and validate our software before the project start and take into account all its aspects to do it the best way. Our team has conducted 158 projects for pharmaceutical and biotech companies and CROs. With Data MATRIX products 6 out of 10 TOP Big Pharma companies reduced their R&D costs by 15%.Our employees are proud to be members of the professional communities, which unite clinical data specialists (CDISC), data managers (ACDM, SCDM), biostatisticians (ISBC), and medical writers (EMWA, AMWA).


TaxTaker is your firm's business savings software. Our first automated, cloud-based solution is the answer to your firm's increasing need to manage R&D Tax Credit studies. Whether you have experience with the incentive or not, each client project will be managed accurately, efficiently, and comprehensively. TaxTaker offers the first white-label R&D Tax Software for CPA firms. Built by experienced CPAs and R&D Tax Attorneys, our technology is a powerfully accurate alternative to the standard R&D study model, helping clients save time and maximize tax benefits.

Balex Technologies, LLC

Balex Technologies is developing patented technology demonstrated to increase Input/Output (I/O) speeds and reduce latency by orders of magnitude. Our technology, which works with existing computer hardware and software, can provide unmatched performance capabilities and can also be more than 10 times more cost effective than current technology. Our addressable market extends far beyond the high performance computing space to include data centers, Fortune 1000 companies, and small to medium size businesses. Our technology is hardware with embedded proprietary software. Future generations of are hardware can be miniaturized and included in mobile systems. We believe that our technology will be widely used in AI applications. We are collaborating with the Texas Advanced Computing Center (TACC) at the University of Texas at Austin.