Health and life sciences

Challenges We Address

Manual microscopy image analysis is time-consuming, and it can be automated.

Researchers' time is precious. They need to focus on their research tasks - not on data infrastructure and ML model operations.

Accelerate Discovery with AI-Powered Research

AI empowers life sciences and R&D teams to accelerate innovation, reduce development costs, and make data-driven decisions with confidence. By automating complex processes such as molecule design, image analysis, and data interpretation, AI helps scientists focus on what matters most—discovering new therapies and delivering better outcomes faster. With scalable and production-ready solutions, AI transforms scientific research into actionable impact.

Digital Pathology Pipeline

Enable Use Cases

Tumor Detection

Medical Image Analysis

Automation

Automate your medical image analytics at scale

The AI-powered Digital Pathology Pipeline is revolutionizing cancer diagnosis by rapidly analyzing millions of medical images and reducing inaccuracies. It uses AI to automate and streamline the analysis of microscopy images. Built on the Databricks Lakehouse Platform, this solution is utilized by pathologists, molecular biologists, and researchers.

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Certified solution

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Accelerating Drug Discovery with AI

AI is transforming how we design the medicines of tomorrow. By leveraging advanced generative models and Large Language Models (LLMs), we help pharmaceutical teams fast-track drug discovery—from virtual screening to biomolecule design.
Our solutions reduce experimental costs, boost predictive accuracy, and enable data-driven innovation across the entire drug development pipeline. We streamline the discovery process and support smarter, faster decision-making in pharma R&D.

MLOps for Life Sciences R&D

MLOps streamlines the path from data to discovery in Life Sciences R&D. It enables research teams to focus on science, not infrastructure, by automating model versioning, deployment, and monitoring. With integrated tools for reproducibility and scalability, MLOps ensures reliable AI pipelines. Fast to implement, secure by design, and built for collaboration, MLOps reduces time to insight and bridges the gap between research and production.

Data Integrity in GxP

In GxP environments, data integrity is critical—but hard to ensure across complex regulatory documents. AI-powered cross-validation automates the comparison of parameters and meanings across SOPs, instructions, and records, detecting deviations and inconsistencies early.
Designed solution supports automated reporting (e.g. Annual Product Review), minimizes human error, and simplifies audits—improving QA and release efficiency while being scalable across teams.

Featured Case Study

Automating Pathology Image Analysis with Deep Learning

Researchers can easily integrate their own deep learning models or train new ones to allow AI to take charge of tedious tasks like segmentation, detection and classification of pathology images.

Client:

Leading Pharma Company