In 1979, the Soviet Union’s invasion of Afghanistan shook the world and left families displaced and forced to flee. Among these families were the parents of Nilo Rahamani and Jennifer Rahamani, founders of Thoras.AI. Little did their parents know, this event would eventually lead to the birth of twin girls who would grow up to become successful engineers, working for companies like Slack and the Department of Defense.
Having inherited their parents’ strength and courage, the Rahmani sisters noticed a recurring issue in their previous jobs with engineers relying too heavily on intuition rather than data when sourcing Kubernetes workloads. Driven by their desire to solve this problem, the sisters made the bold decision to leave their comfortable jobs and launch Thoras.AI.
Today, the company announced a significant pre-seed investment of $1.5 million to support their mission. According to company CEO Nilo Rahmani, Thoras.AI integrates with cloud-based services to efficiently monitor their usage. This allows the application to not only forecast demand, but also autonomously scale up or down to prepare for increased or decreased traffic. Additionally, it can notify engineers of any performance issues, giving them ample time to address and resolve them before they escalate into more serious problems.
“The goal is to not only forecast demand, but then to autonomously scale the application up or down in anticipation of increased traffic or decreased traffic,” said Nilo Rahmani in an interview with TechCrunch.
The company launched earlier this year and has already secured their pre-seed funding. They have also released the first version of their product and are actively working with live customers and generating revenue, all promising signs for a startup in its early stages.
While the founders were hesitant to disclose too much about the backend operations, they did mention that the application connects directly to the company’s development environment, with no APIs involved and no information being shared. This was a critical design factor for them, as they prioritized security and privacy. On the frontend, developers can access a dashboard displaying key information about the application’s resources. The founders emphasized their focus on creating a visually appealing user experience in the dashboard.
In terms of AI, the company currently utilizes task-based machine learning, rather than generative AI and large language models. This approach allows them to proactively identify and address potential problems, as they deal with systemic issues and vast amounts of data. However, the founders do see the potential for incorporating LLMs in the future, particularly in troubleshooting after the fact.
“We definitely have products in our roadmap that make use of LLMs, but natural language processing is super helpful in a situation where there’s a lot of words involved, and right now, we want to get to the the root of the problem before it actually occurs instead of just going through logs to figure out what happened and why it happened after the fact,” explained Nilo Rahmani.
Reflecting on their upbringing and the opportunities they have been given in the US, the Rahmani sisters are grateful for their parents’ sacrifices and the privilege to pursue their dreams. “There isn’t a day that I don’t think about how privileged I am to be in a country where I can pursue my dreams. I talk about that all the time,” Nilo shared. Jennifer added, “It definitely helps drive us to work as hard as we can and succeed, I would say.”
Today’s pre-seed investment was co-led by Storytime Capital and Focal VC, with participation from Hustle Fund, Precursor Ventures, the Pitch Fund, and several unnamed strategic angel investors.
