To raise awareness about NAMC Member capabilities within the consortium, NAMC launched the Member Spotlight last year to showcase an organization from the capability areas identified in the DAI OTA.
With over 500+ members, we encourage you to take advantage of this opportunity and nominate your company via the Member Spotlight application. Many exciting projects are in the pipeline, and the spotlights help raise awareness of your company's capabilities.
If you have any questions, please submit an email using our contact form. To access Member Spotlights from previous months, please visit our News page.
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RJA Technologies
POC: Chetan Peddada | Click here to show email address
Company Profiles: Website | LinkedIn
Technology Objective Area: Modeling & Simulation (M&S)
Organization Type: Nontraditional
Q: Within the NAMC ecosystem, what are your top priorities for forming strategic partnerships, and how do you envision these collaborations benefiting all parties involved?
A: We envision a partnership that is a win-win for all parties involved. Each member should be able to create immense value to the customer, push the boundaries of innovation, and achieve shared success.
Our priority is to bring a set of complementary skills, expertise, and resources to the table. Our deep capabilities in AI/ML, cybersecurity, and extended reality can add technical value to any team to deliver innovative solutions. Further, our team is highly nimble and can evolve quickly to adapt to new opportunities or challenges. Our team is as passionate today as we were the day we started the company. Lastly, we place high trust on all our team members and give them the autonomy to make decisions. This helps clarify who is responsible for what and ensures accountability and prevents overlap or confusion.
Q: What are the most critical capability gaps in the industry today, and how does your organization propose to fill them?
A: The AI/ML industry is incredibly fast-paced and the challenges and breakthroughs occur at breakneck speed. At present, many advanced AI/ML models are considered “black boxes” that are difficult to decipher how they arrived at predictions. We have developed methods to explain how the model made decisions and ensure that nontechnical users can understand them. We use AI Agents, layered on LLMs, to help us clarify how the LLM arrived at the answer. Second, models are extremely large and difficult to scale to lower compute settings. We have developed open-source models that use a fraction of the compute that foundational models use to deploy them onto edge devices. Third, there is a shortage of high-quality talent in AI/ML. Our team has invested heavily in internal training and mentorship for less-experienced developers to bring them up to speed quickly.
Q: Can you share an instance where your product or service solved a critical challenge that no one else could?
A: Software developers in an Air Force organization were experiencing challenges with learning highly-specialized technical domains. This was directly impacting their work as their ability to write/read code in a particular domain was incredibly slow.
We connected with the organization and briefed them on our AI capabilities and showed them how our product could be used as an educational/learning tool. We quickly ingested as much data as we could in various technical areas that they had a need for and trained our machine to answer questions on their questions. This helped save hundreds of developer hours of work and get the developers back on track to accomplishing their mission.