AI/ML Integrations

Client

A global leader in the healthcare industry.

Challenge

GenAI revolution enabled a wide range of new use cases that generated significant interest from the business stakeholders at the R&D department, who wanted to tap into the knowledge hidden in the vast body of the company’s text documents and databases to enable and streamline research activity.

They face the following challenges:

While the availability of out-of-the-box AI components via various libraries has increased significantly, their integration into data & analytics workflows and applications is not trivial and requires specialized skills;
While tapping into unstructured content of the text documents databases (e.g. clinical reports, etc.) offered to unlock a significant business value, the sheer size of these data sources came with challenges typical of Big Data solutions and required a modern data infrastructure to handle;
In a highly regulated environment, any software requires robust validation, which is non-trivial for AI-based solutions.

Solution: Leveraged the latest AI components from Databricks

1. Cloud as the Foundation for AI
2. Modern Data Platform on Databricks
3. Technical Expertise + Domain Knowledge
4. Comprehensive GenAI Deployment
5. CI/CD Automation for Speed and Quality

Leveraging existing cloud infrastructure as the base for modern AI and GenAI applications.
Building a scalable, cost-efficient data platform with access to advanced AI libraries and industry-specific model fine-tuning.
Engaging a partner with both technical and industry-specific expertise to reduce risks and upskill the client’s internal team.
Implementing RAG pipelines, content generation, entity extraction, traditional ML, and a chatbot UI.
Applying DevOps practices and CI/CD automation with testing frameworks to streamline quality control and accelerate releases.

Key Outcomes

As a result, the client achieved the following benefits:

The client’s R&D team can now rapidly and easily extract knowledge from a large body of corporate document databases by asking questions in natural language via a chat. This offers significant productivity improvement and opens up new use cases.
Implementations of other AI or GenAI-enabled solutions became possible for the client – they have the infrastructure and a team ready, so that they effectively joined the AI/genAI revolution.
Thanks to leveraging best-in-class data & AI platform (based on Databricks and Azure OpenAI tehcnologies) and the automation processes implemented, including the automation testing, it is easy to ensure frequent releases of the improved software components to ensure optimal performance and to react to evolving business requirements
Cost control of cloud components allows for measuring the benefits and relating them to the actual infrastructure costs. It allows for better measurement of the ROI of individual initiatives and feature requests.