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Challenge
The US Government needs to rapidly classify threats, develop responses, and deploy them before additional damage can occur, with challenges in automating security processes such as patch management.

Objective
To leverage SambaNova’s generative AI capabilities to automate response protocols, enabling quick isolation of affected systems and mitigation of damage. AI-driven decision-making will be utilized to determine the best course of action for each specific threat, reducing response times and minimizing impact. SambaNova’s powerful AI platform can handle the computational demands of real-time attack response, ensuring efficient and effective mitigation of cyber threats.

Read the full Cyber Attack Response use case

Challenge
Emergency response teams face the challenge of managing and analyzing vast amounts of emergency data in near real-time. Traditional methods often lead to delays in decision-making, reduced operational efficiency, and increased costs. There is a need for a robust solution that can seamlessly integrate into existing systems to provide timely, accurate, and actionable insights, ultimately improving emergency management and public safety.

Objective
To implement SambaNova Suite for State Emergency Response Teams in Florida and Texas. This will enhance the management and analysis of emergency data through on-site generative AI capabilities. By leveraging SambaNova’s integrated AI platform, teams can expect improved field operations, smarter decision-making, significant cost savings, and more effective emergency management. The full stack solution ensures data ownership, flexibility in deployment (on-site or cloud), and seamless integration into current workflows.

Read the full Near Real Time Operations Augmentation use case

Challenge
The United States Army fell about 25% short of its goal of onboarding 60,000 new active-duty troops in fiscal 2022 due to stringent recruitment requirements. This problem has permeated through fiscal 2024.

Objective
To implement SambaNova AI-driven recruitment tools to automate candidate and recruit screening, analyze large pools of candidate data, and match qualifications with job requirements efficiently. Leverage natural language processing to understand recruitment documentation and structured data analysis to predict candidate success, speeding up the recruitment process and increasing the quality of soldiers delivered to the force.

Read the full Soldier Recruitment use case

Challenge
The United States military is facing a decrease in retention rates. In 2021, the retention rate was on 55%. This has been attributed to a number of issues such as inadequate compensation, toxic leadership, and limited personal freedom.

Objective
Utilize SambaNova predictive analytics to analyze factors contributing to employee turnover, such as job satisfaction or command climate surveys, performance metrics, and external data sources. Then use the results to develop AI-driven strategies to enhance job satisfaction, customize career paths, and create a positive work environment, ultimately improving retention rates.

Read the full Soldier Retention use case

Challenge
The US military needs a robust system to identify and place individuals who exceed standards in appropriate roles. This will ensure efficient talent deployment and leadership development.

Objective
Deploy the SambaNova generative AI platform to analyze employee performance data, career trajectories, and skill sets from the existing evaluation databases for both enlisted personnel and officers. Custom, pre-trained trained large language models will be used to identify patterns and predict high-potential individuals for leadership roles and career advancement, ensuring optimal talent utilization across the agency.

Read the full Talent Identification use case

Challenge
The US faces challenges with bugs in code and flaws in software design that can be exploited. There are also gaps in security procedures, which can lead to security breaches, especially in software deployed to higher impact levels.

Objective
Implement AI-powered tools on the SambaNova platform to analyze and perform comprehensive vulnerability scans across systems and software. Large language models will be utilized to categorize risks based on criticality and likelihood of exploitation, enabling prioritization of remediation efforts. SambaNova’s high-performance AI capabilities will be leveraged to handle large datasets and complex analysis, reducing manual effort and increasing the speed and scale of vulnerability analysis.

Read the full Vulnerability Assessment use case

Challenge
The public sector faces many challenges optimizing workforce scheduling. These include a lack of modern technology, employee shortages, and unequal shift distributions. All this leads to inefficient workforce scheduling.

Objective
Leverage SambaNova generative AI capabilities to optimize workforce scheduling by analyzing operational data, employee preferences, and constraints. This is applicable unit or agency level Standard Operating Procedures. Automate intraday management and schedule adjustments, reducing administrative burden and ensuring efficient resource allocation to meet operational demands.

Read the full Soldier Retention use case