Investments in AI tools for healthcare were expected to reach $11 billion last year, reflecting the conviction that artificial intelligence will revolutionize this critical sector. Many startups, including Hamburg-based Elea, are leveraging AI to streamline healthcare administration. Elea is specifically targeting pathology labs, which analyze patient samples for disease, with the goal of scaling its AI-powered workflow system globally.

Elea’s AI tool is designed to replace legacy systems and automate various tasks, such as speech-to-text transcription, to significantly reduce the time it takes to produce diagnoses. After working with its first users for about six months, Elea reports that its system has cut the time to produce around half of the lab’s reports to just two days.

Step-by-Step Automation

According to Elea’s CEO and co-founder, Dr. Christoph Schröder, the manual workflow in pathology labs presents an opportunity for AI-driven productivity gains. The startup’s cloud-based software automates tasks, such as preparing slides and printing reports, allowing doctors and medical technical assistants to focus on higher-value tasks.

Elea’s AI operating system integrates with various Large Language Models (LLMs) and fine-tunes them with specialist information to enable core capabilities in pathology labs. The platform includes speech-to-text and text-to-structure capabilities, allowing staff to dictate voice notes that are then transcribed and turned into actionable directions for the AI agent.

While Elea plans to develop its own foundational model for slide image analysis, its initial focus is on scaling its current offering. The startup’s pitch to labs emphasizes the potential to reduce the time it takes to produce reports from weeks to hours or days, eliminating manual errors and workflow inefficiencies.

The system can be accessed through various touch-points, including an iPad app, Mac app, or web app, to accommodate different user types. Founded in early 2024, Elea launched its first lab in October and has since partnered with a major German hospital group, with hundreds of users on board.

Seed Backing

Elea has secured a €4 million seed funding round, led by Fly Ventures and Giant Ventures, to build out its engineering team and bring its product to market. While this amount may seem modest compared to the billions invested in AI healthcare solutions, Schröder argues that startups don’t need vast resources to succeed, but rather a focused approach and smart application of existing resources.

The startup is planning to raise a larger Series A round, likely this summer, to scale its marketing efforts and expand its customer base. Discussing its approach, Schröder highlights the difference between Elea’s vertically integrated solution and other AI tools that are add-ons to existing systems.

Scaling a Workflow Mindset

Elea’s strategic choice to start with pathology labs was driven by the addressable market size and the global nature of the industry. Schröder believes that by solving the workflow challenges in one application, they can scale to other regions and languages, given the similarities in lab workflows worldwide.

The startup is focused on maturing its lab use case before expanding into other areas, such as supporting hospital doctors or image processing for radiology. Schröder emphasizes the importance of a workflow mindset, where everything is treated as a task, and the end goal is a report that needs to be sent out.

Challenges

Accuracy is a critical concern in healthcare, and Elea’s AI transcriptions must be reliable to avoid serious consequences. The startup evaluates accuracy by tracking changes made to automated reports, with a current error rate of around 5-10%. Schröder notes that doctors ultimately review and approve AI outputs, and the buck stops with them.

To mitigate risks, Elea has implemented a “safety net” feature that prompts doctors to review potential issues. The startup also addresses patient confidentiality concerns by separating patient identities from diagnostic outputs and using pseudonymization for data protection compliance.

Schröder emphasizes that Elea works with European servers, ensuring data privacy compliance, and has received approval from its lead customer, a publicly owned hospital chain in Germany. The startup prioritizes data security, recognizing the sensitivity of medical data and the need to be “on the safe side.”