• ActiveLoop
    • Solutions
      Industries
      • agriculture
        Agriculture
      • audio proccesing
        Audio Processing
      • autonomous_vehicles
        Autonomous & Robotics
      • biomedical_healthcare
        Biomedical & Healthcare
      • generative_ai_and_rag
        Generative AI & RAG
      • multimedia
        Multimedia
      • safety_security
        Safety & Security
      Case Studies
      Enterprises
      BayerBiomedical

      Chat with X-Rays. Bye-bye, SQL

      MatterportMultimedia

      Cut data prep time by up to 80%

      Flagship PioneeringBiomedical

      +18% more accurate RAG

      MedTechMedTech

      Fast AI search on 40M+ docs

      Generative AI
      Hercules AIMultimedia

      100x faster queries

      SweepGenAI

      Serverless DB for code assistant

      Ask RogerGenAI

      RAG for multi-modal AI assistant

      Startups
      IntelinairAgriculture

      -50% lower GPU costs & 3x faster

      EarthshotAgriculture

      5x faster with 4x less resources

      UbenwaAudio

      2x faster data preparation

      Tiny MileRobotics

      +19.5% in model accuracy

      Company
      Company
      about
      About
      Learn about our company, its members, and our vision
      Contact Us
      Contact Us
      Get all of your questions answered by our team
      Careers
      Careers
      Build cool things that matter. From anywhere
      Docs
      Resources
      Resources
      blog
      Blog
      Opinion pieces & technology articles
      langchain
      LangChain
      LangChain how-tos with Deep Lake Vector DB
      tutorials
      Tutorials
      Learn how to use Activeloop stack
      glossary
      Glossary
      Top 1000 ML terms explained
      news
      News
      Track company's major milestones
      release notes
      Release Notes
      See what's new?
      Academic Paper
      Deep Lake Academic Paper
      Read the academic paper published in CIDR 2023
      White p\Paper
      Deep Lake White Paper
      See how your company can benefit from Deep Lake
      Free GenAI CoursesSee all
      LangChain & Vector DBs in Production
      LangChain & Vector DBs in Production
      Take AI apps to production
      Train & Fine Tune LLMs
      Train & Fine Tune LLMs
      LLMs from scratch with every method
      Build RAG apps with LlamaIndex & LangChain
      Build RAG apps with LlamaIndex & LangChain
      Advanced retrieval strategies on multi-modal data
      Pricing
  • Book a Demo
Case Study

How Bayer Radiology Uses Database for AI to Disrupt Healthcare with GenAI

Learn how Bayer Radiology, a division of a pharmaceutical powerhouse, used a secure, efficient, & scalable database for AI to pioneer medical GenAI workflows

icon
poster
iconProcess
AI Data in Days

Introduction

Bayer Radiology, a unit of a renowned pharmaceutical company solving pressing societal issues across healthcare and life sciences, faced an increasingly common challenge in large organizations of making their multi-modal biomedical data universally valuable for various users for AI purposes.

Steffen Vogler, a Senior Imaging Technology Scientist at Bayer Radiology, noted that AI developers were spending around 50% of their time making their data AI-ready. They required a platform that could enable internal researchers and partners to build AI medical software while maintaining high standards of scientific rigor.

The goal was to find an efficient, flexible, and scalable database for AI. The search for a suitable solution led Steffen and his team to Deep Lake.

tomography scans

The Challenge

Bayer Radiology’s primary challenge lies in the time-consuming data preparation process for AI. Developers had to manage complex data subsets, control data versions, and constantly add new data to their projects.

The multimodality of data – image class, electronic health records, lab data, genomics, proteomics – further complicated matters.

"The elephant in the room is it takes a lot of time to reach the finish line. Especially the data curation part."

Steffen Vogler

Senior Imaging Technology Scientist, Bayer Radiology
Steffen Vogler
activeloop desktop application

Activeloop's Solution

To overcome these challenges, Bayer Radiology implemented Activeloop’s Deep Lake solution. Deep Lake unifies different data modalities into a single storage solution that can be streamed for pre-processing, training, and inference. The solution was deployed on Bayer Radiology’s Google Cloud account, allowing for efficient search or inference capabilities and the ability to fine-tune own models.

Activeloop's Tensor Query Engine

Querying datasets is a critical aspect of data science workflows that enables users to filter datasets and focus their work on the most relevant data. Deep Lake offers a highly-performant query engine for filtering your data, generating SQL-like queries from natural language.

"We went from a GitHub issue to a working prototype I could use in under 3 weeks."

Steffen Vogler

Senior Imaging Technology Scientist, Bayer Radiology
Steffen Vogler
cubes
"It's next-level. We've enabled a new human-machine interface that is natural to use and yields high-accuracy results for end-users."

Steffen Vogler

Senior Imaging Technology Scientist, Bayer Radiology
Steffen Vogler

Results

In only 2 weeks, Activeloop was fully integrated into Bayer Radiology’s enterprise cloud platform. The time spent on data preparation was reduced from 50% to a mere fraction, allowing developers to focus more on optimizing AI architectures.

Notably, the solution prioritizes security, adeptly managing sensitive data within Bayer Radiology’s secure data centers, essential for safeguarding Personally Identifiable Information (PII).

  • 2 weeks
    Time to Integrate
  • Process AI Data in Days
    Instead of Spending Up to 50% of Project Time
  • Words instead of SQL
    In-App Chat with Biomedical Data below

Future Plans

Bayer Radiology’s collaboration with Activeloop and the successful implementation of Deep Lake has paved the way for future collaborations.

Powerful query features to curate subsets in natural language.
Chat with multi-modal data, at scale
tomography

Powered by Intel

The Intel RISE and Intel Disruptor Initiative Program further bolstered Bayer Radiology’s collaboration with Activeloop. Intel technology was used at multiple stages in the project, including feature extraction and processing large batches of data. Intel Xeon 4th Generation processors, powering Activeloop’s Tensor Query Engine, facilitated quick and efficient queries across millions of scans, significantly shortening innovation cycles.

As Bayer Radiology continues to innovate and push the boundaries of AI in healthcare, Activeloop’s Deep Lake, powered by Intel technology, remains an integral part of its AI tech stack.

Overall, the collaboration between Bayer Radiology, Activeloop, and Intel showcases a successful example of combining cutting-edge technology with heavily regulated industry needs to deliver a sizeable impact. This collaboration promises to redefine how AI enables the pharmaceutical and healthcare industry, with Bayer Radiology leading the charge.

"The Intel RISE program gave us flexibility and room to experiment, setting us up for success."

Steffen Vogler

Senior Imaging Technology Scientist, Bayer Radiology
Steffen Vogler
layers
“I am confident that adopting Activeloop was a value-add through improved innovation that will compound as our AI operations grow.”

Steffen Vogler

Senior Imaging Technology Scientist, Bayer Radiology
Steffen Vogler
“The collaboration between Intel, Bayer, and Activeloop highlights the critical role of fast-paced innovation and economic scalability in advancing healthcare AI. Utilizing Intel’s latest AI Hardware and IA based software assets, Bayer has unlocked the full potential of Activeloop Deep Lake. This collaboration has not only delivered significant performance enhancements but also achieved a more cost-effective approach to AI initiatives, paving the way for future advancements in the sector.”

Arijit Bandyopadhyay

CTO of Enterprise Analytics & AI, Head of Strategy Cloud and Enterprise – CSV Group, Intel Corporation
Arijit Bandyopadhyay
  1. Bayer's GenAI Initiative: Information is based on data available as of my last update in January 2022. Additional details may have emerged since that date.
  2. Radiology Transformation: Further details about the transformation of radiology using GenAI from Bayer may be provided by official Bayer sources or published scientific papers.
  3. Database for AI: Information about the artificial intelligence (AI) database within this initiative is based on data provided by Bayer. Additional technical details may be available in official technical reports or press releases from the company.
  4. GenAI Impact on Data Preparation: Information about the reduction in data preparation time is provided based on available project information. Actual results may vary depending on specific project conditions and settings.
  5. Innovation and Research: For more detailed information on how Bayer utilizes artificial intelligence in radiology, it is recommended to refer to official company sources, publications in the field of medical science, or scientific papers presented by the company.
  6. Activeloop is SOC 2 Type II compliant, for more information, please see https://www.activeloop.ai/resources/activeloop-is-now-soc-2-type-ii-certified/.

Intel Disclaimers

Performance varies by use, configuration and other factors. Learn more on the/Performance Index site.
Performance results are based on testing as of dates shown in configurations and may not reflect all publicly available updates. See backup for configuration details. No product or component can be absolutely secure.
Your costs and results may vary. For workloads and configurations, visit 4th Gen Xeon® Scalable processors at www.intel.com/processorclaims.
Results may vary.
Intel technologies may require enabled hardware, software or service activation.
Intel does not control or audit third-party data. You should consult other sources to evaluate accuracy.
Intel® technologies may require enabled hardware, software, or service activation.

© Intel Corporation. Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others.

    Book a Call
    Case studyLarge Language Models (LLMs) are pioneering the next frontier in enterprise workflows. Learn how top companies unlock value by linking their multimodal data to LLMs with the database for AI

    Increase in Lawyer Productivity with Hercules.ai by 18.5%

    Discover how Ropers Majeski, a leading law firm, utilized Hercules.AI, powered by Activeloop's cutting-edge enterprise data solutions, to achieve remarkable productivity gains and cost efficiencies with LLMs

    Read more
    Herculesai

    IntelinAir faster AgriTech with Aerial Machine Learning Data Pipelines

    Learn how IntelinAir, the leading crop intelligence company, transformed 1500 terabytes of aerial imagery into vital insights for farmers with scalable plug-and-play data pipelines with Activeloop and NVIDIA.

    Read more
    Intelinair
    • deep lake database

      Deep Lake. Database for AI.

      • Solutions
        AgricultureAudio ProcessingAutonomous Vehicles & RoboticsBiomedical & HealthcareMultimediaSafety & Security
      • Company
        AboutContact UsCareersPrivacy PolicyDo Not SellTerms & Conditions
      • Resources
        BlogDocumentationDeep Lake WhitepaperDeep Lake Academic Paper
    • Tensie

      Featured by

      featuredfeaturedfeaturedfeatured