Project Overview
Strategy & Advisory
AI Products & Platforms
Agents
Knowledge Systems
Automation & Integration
A healthcare technology company engaged SF AI Labs to develop an AI copilot for improving how healthcare professionals access pharmaceutical and medical information.
Prescribers often need to navigate dense prescribing information, clinical materials, and product documentation while engaging with pharmaceutical companies. The opportunity was to make this information easier to access without requiring healthcare professionals to manually search through large volumes of content.
SF AI Labs designed and integrated a RAG-based AI system that could ingest structured and unstructured medical materials, retrieve relevant information, and generate contextual responses within the existing platform.
The engagement combined AI strategy, retrieval architecture, evaluation, and product integration to move the copilot from concept into a working product capability.
Challenge
Pharmaceutical information is extensive, highly structured, and often distributed across prescribing information, clinical studies, and supporting product materials.
Healthcare professionals needed a more efficient way to navigate this information, while pharmaceutical companies needed a digital engagement experience that reduced friction without adding more administrative work for providers.
The product required an AI layer capable of finding relevant information while remaining grounded in approved source materials.
Strategy
Build a retrieval-first AI copilot around trusted medical content.
SF AI Labs designed the system to ingest pharmaceutical materials, structure the underlying knowledge, retrieve information relevant to each query, and use the retrieved context to support AI-generated answers.
The roadmap also incorporated evaluation and platform integration so the RAG system could operate as a product capability rather than a standalone prototype.
Solution
RAG system for structured medical and prescribing information
Ingestion pipelines for multiple medical content formats
Retrieval layer for finding relevant source material
AI agent capabilities for contextual question answering
Evaluation and integration into the existing healthcare platform
Execution
Defined the AI product strategy, user workflows, and technical architecture
Built ingestion and retrieval capabilities for structured medical content
Expanded the knowledge system to support additional clinical materials
Developed AI agent capabilities on top of the retrieval layer
Evaluated and integrated the RAG experience into the core platform
Results
Delivered the core AI strategy and technical roadmap
Built the medical-information ingestion and retrieval system
Expanded RAG support across structured and unstructured source materials
Completed AI quality evaluation and platform integration
Established the foundation for a broader AI-enabled prescriber engagement experience
Business Value
The copilot creates a faster way for healthcare professionals to navigate complex medical information.
Instead of manually searching through prescribing information and supporting documentation, users can interact with an AI experience grounded in the underlying source materials.
For the platform, this creates a differentiated engagement layer that can make pharmaceutical information more accessible while providing a foundation for additional AI-enabled scheduling, communication, and engagement capabilities.
Why SF AI Labs
SF AI Labs combines AI product strategy with hands-on development of retrieval, agentic, and enterprise AI systems.
For this engagement, we worked across the full AI product lifecycle—from defining the user experience and knowledge architecture to building the RAG system, evaluating its outputs, and integrating it into the existing healthcare platform.
Confidential (Healthcare Technology Company)
FAQ
What does SF AI Labs do?
SFAI Labs exists to help organizations turn bold ideas into real, scalable AI systems. We operate as an applied AI lab, combining rapid experimentation with disciplined execution to create technology that delivers lasting business and social value.
Who can work with SF AI Labs?
We partner with founders, operators, and enterprise leaders who want to use AI thoughtfully and responsibly to solve meaningful problems and build enduring organizations.
What kind of AI products does SF AI Labs build?
We design and build custom AI systems that augment human work, unlock hidden insights, and transform complex operations into intelligent, adaptive systems.
How long does it take to develop an AI prototype?
Our lab model allows most teams to move from idea to working prototype in four to eight weeks, creating early proof while laying the foundation for long-term impact.
Do I need a technical team to work with SF AI Labs?
No. We embed with your team as an extension of your organization, bringing research, engineering, and design together to turn ambition into working systems.
