Inspiration
In many hospitals, doctors and staff spend a lot of time searching for drug details, prescriptions, and reimbursement rules. The information exists, but it is scattered across documents, portals, and government websites. We were inspired by the idea that technology should reduce this burden, not add to it. We wanted to build something that quietly works in the background and gives the right information at the right time, so healthcare professionals can focus more on patients.
What it does
Digital Medical Representative is an agent AI system that helps healthcare professionals quickly find accurate drug, prescription, and reimbursement information. A user can ask questions in simple language, and the system understands the intent and fetches the correct data from trusted sources. It adapts answers based on hospital rules or government schemes and keeps itself updated automatically as policies change. All this information is shown through a simple dashboard that is easy to use and easy to trust.
How we built it
Challenges we ran into
Keeping information up to date Drug rules and government schemes change frequently. Making sure the system always shows the latest information requires reliable data sources and regular updates. We solve this by designing automated data refresh pipelines and clear version tracking.
Understanding vague or incomplete questions Users may ask questions without giving full details, such as patient age or condition. This can lead to confusion. We handle this by using AI to infer intent and ask smart follow up questions when needed.
Accomplishments that we're proud of
We will successfully deliver an AI agent that can understand natural language queries and map them to structured drug and reimbursement data. We will also build a clean dashboard that turns complex healthcare rules into simple answers. Most importantly, we want to create a system that can adapt its responses based on hospital policies or government schemes.
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