Faisal Zain is a healthcare expert specializing in medical technology. He has extensive experience in the manufacturing of medical devices used for diagnostics and treatment, driving innovation in the field.
Can you tell us more about the seed funding round?
The seed funding round was truly exciting for us at RISA Labs. It was led by Binny Bansal, the co-founder of Flipkart, along with contributions from Oncology Ventures, General Catalyst, z21 Ventures, ODD BIRD VC, and Ashish Gupta. With the $3.5 million secured, our main focus will be on accelerating the deployment of our technology in the next 100 cancer centers across the country over the next two years.
What inspired you to start RISA Labs?
The inspiration to start RISA Labs stemmed from my previous experience at Urban Health. I witnessed firsthand the inefficiencies and fragmented nature of healthcare workflows, which significantly slowed down processes and increased error rates. With RISA, we aim to tackle these specific challenges by taking a systems-first approach, leveraging advanced technology to streamline and optimize healthcare operations.
How does RISA’s Business Operating System as a Service (BOSS) work?
RISA’s BOSS is a full-stack orchestration engine designed to handle the vertical complexity of healthcare. Instead of relying on humans to manage paperwork or bots that can easily break, BOSS breaks down complex workflows into micro-tasks and assigns them to intelligent agents like LLMs, digital twins, and reinforcement learners. This creates a parallel digital workforce that significantly enhances efficiency by managing tasks across the institution’s software stack.
Can you elaborate on the concept of intelligent agents within BOSS?
Intelligent agents are central to BOSS’s functionality. These include large language models (LLMs), digital twins, and reinforcement learners. Each plays a unique role: LLMs understand and process textual information, digital twins simulate real-world processes for prediction and optimization, and reinforcement learners improve decision-making processes through continuous learning. Together, they integrate seamlessly with an institution’s existing software, creating a cohesive, intelligent ecosystem.
What are some of the success stories or case studies from using RISA in healthcare institutions?
One notable success story comes from a leading US cancer center, where BOSS dramatically reduced prior authorization times from 30 minutes to under 5. Additionally, within a few months, BOSS processed over $1 million in medications, freed up 80% of staff time, and cut administrative costs by 66%. These outcomes highlight the significant impact of our technology on improving efficiency and reducing costs in healthcare settings.
How does RISA address the issue of prior authorization delays in oncology?
Prior authorization delays are a major barrier in cancer treatment, often leading to significant impacts on patient outcomes. By leveraging BOSS, we can streamline the authorization process, significantly reducing these delays. In practical terms, our system has achieved a reduction in authorization times from 30 minutes to under 5, which is crucial in a field where every minute counts towards improving patient outcomes.
What are your plans for scaling RISA across more cancer centers?
Our goal is to implement BOSS in the next 100 cancer centers within the next two years. This ambitious plan involves a methodical approach to scaling, focusing on building robust infrastructure and forming strategic partnerships with healthcare providers. We foresee challenges, particularly around integration with existing systems, but we’re prepared to tackle these with our expertise and a dedicated team.
What is your long-term vision for RISA within the oncology ecosystem?
Our long-term vision for RISA is to be the AI-driven orchestration hub for the entire oncology ecosystem. This involves enabling seamless coordination and intelligence across providers, life sciences organizations, and other key stakeholders. We see AI playing an increasingly prominent role in not just operational efficiencies but also in enhancing clinical workflows, thus improving patient outcomes.
Can you explain the quote about work in the post-ChatGPT era from Kshitij Jaggi?
The quote underscores the transformative potential of BOSS in simplifying the work process. In the post-ChatGPT era, where software complexity has increased, BOSS aims to allow users to focus on expressing intent rather than learning to use tools. Essentially, it automates and streamlines workflows, freeing up human workers to concentrate on higher-value tasks and decision-making.
Do you have any advice for our readers?
My advice to readers, especially those in the healthcare sector, is to embrace technological advancements and consider how systems like RISA’s BOSS can be integrated into their operations. Automation and AI are no longer futuristic concepts; they are present realities that can drastically improve efficiency and patient care. Stay curious, stay informed, and be open to innovation.
