Scaling Medical Data Infrastructure for FluidAI

FluidAI partnered with Ample Insight to develop a robust and scalable data infrastructure, enabling efficient processing and analysis of biosensor data, driving new medical insights and innovations in postoperative care.

Predictive AI tools could reduce hospital admissions by 50%.

(19+ AI in Healthcare Statistics for 2024, All About AI, 2024)

The Opportunity  

Accelerating Medical Insights with Scalable Data Infrastructure

FluidAI, a leader in IoT biosensors for postoperative care, sought to revolutionize patient monitoring by predicting anastomotic leaks through advanced data analysis. FluidAI’s biosensors generate large volumes of complex biochemical data, requiring an advanced infrastructure to:

  • Consolidate and Transform Data: Efficiently manage and process large volumes of biosensor data.
  • Support Machine Learning: Prepare and optimize data for machine learning models focused on predicting patient health issues.
  • Provide Actionable Insights: Deliver real-time analytics and visualizations to medical specialists and data scientists.

To achieve these goals, FluidAI required a partner with expertise in data engineering, machine learning, and data analytics. Ample Insight was chosen to build the necessary data technologies, workflows, and best practices.

The Solution

Building a Scalable and Robust Data Infrastructure

Ample Insight collaborated closely with FluidAI to address their data challenges by focusing on:

  • Ensuring Data Consistency and Accuracy: A thorough audit of FluidAI’s biosensor data was conducted to ensure reliability. This process involved identifying potential edge cases and anomalies, which were addressed by standardizing and consolidating raw data through custom workflows and pipelines.
  • Developing Advanced Analytics and Visualizations: Tailored analytics and visualizations were developed in collaboration with FluidAI’s medical experts. These tools will support the discovery of patient health issues related to anastomotic leaks, enabling FluidAI to make informed decisions and extract valuable insights from their data.
  • Designing Scalable Data Workflows: Scalable data workflows and best practices were established to align with FluidAI’s expanding data needs, ensuring continued support for their AI initiatives and long-term growth.

The Impact

Driving Medical Innovation with Advanced Data Infrastructure

The successful implementation of this project empowered FluidAI to:

  • Achieve a Trusted Data Infrastructure: FluidAI now benefits from a scalable, standardized data infrastructure that consolidates complex medical data, ensuring accuracy and consistency across their systems.
  • Enhance Predictive Analytics: The newly developed data pipelines and visualizations enable better identification of patient health risks, particularly anastomotic leaks, while effectively preparing data for machine learning models.
  • Sustain Long-Term Growth: With integrated data science workflows and best practices, FluidAI is well-equipped to continue innovating and scaling its AI-driven medical solutions.

The Ample Insight team rapidly launched our project and got onboarded faster than any previous engagement I've had in the past. It was remarkable. With that, we were able to accelerate our development and path to market by adding resources to our most critical path, and better understand our long-term talent needs. The team automated data reporting and found more effective methods of processing to improve data integrity.

Abdallah El-Falou, CTO & Co-founder, FluidAI

The Ample Insight team rapidly launched our project and got onboarded faster than any previous engagement I've had in the past. It was remarkable. With that, we were able to accelerate our development and path to market by adding resources to our most critical path, and better understand our long-term talent needs. The team automated data reporting and found more effective methods of processing to improve data integrity.

Abdallah El-Falou, CTO & Co-founder, FluidAI
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