SD Innovations

AI Data Abstraction

Intelligent Medical Data Extraction

AI-driven platform for a U.S. healthcare firm that automated medical document analysis cutting processing time from hours to minutes.

ClientHealthcare Technology Company from the U.S.
Duration24 months
Year2017

Project Overview

Challenges
The client needed to extract actionable insights from vast volumes of unstructured medical documents, which included both text and image formats. Traditional manual processing was time-consuming and inconsistent, making automation a strategic imperative.

Solution
SD Innovations delivered a turnkey AI-based platform that leveraged deep learning and neural networks to accurately abstract relevant information from medical documents. The solution included a custom ML pipeline and robust backend architecture.

Project Details

Timeline24 months (2017)
Team15
Key Results
Automated document reviewImproved accuracySeamless workflow integration

Our Approach

We employed a strategic methodology to tackle the challenges and deliver exceptional results.

S / 1

We began with tech selection and planning, identifying suitable neural networks for text and image processing, preparing structured datasets, and securing stakeholder sign-off on specifications and milestones.

S / 2

In the execution phase, a proxy product owner from SD ensured alignment, while the team iteratively trained models, built GRPC-based middleware, and completed system integration testing.

S / 3

During handover and support, we provided six months of post-launch assistance and deployed five experts to strengthen the client’s internal AI and development team.

Results & Impact

Our solution delivered significant measurable outcomes for the client.

R / 1

Accelerated data extraction from complex medical documents

R / 2

Improved model precision over time using feedback-driven training loops

R / 3

Enabled healthcare professionals to focus on insights, not data entry

R / 4

Reduced document processing time from hours to minutes

Technologies Used

Key technologies and tools that powered this solution.

Python-based deep learning models
Golang with GRPC interoperability
Google Cloud Platform
Custom UI/UX tailored for healthcare use cases
Intelligent tagging and abstraction mechanisms

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