ALAB Laboratoria selected a modern AI Voice Agent to better understand patient enquiries and conduct more natural conversations. The solution went live in four months with five integrations across different systems and custom APIs. Today, 80% of inbound calls involve AI processing.
For medical diagnostic networks, patient communication runs at scale and directly impacts patient experience. Enquiries include test pricing and availability, information about sample collection points and opening hours, while more complex cases can be transferred to a consultant.
The Company
ALAB Laboratoria, a leader in Polish diagnostics and part of the European Limbach Group since 2008, operates approximately 90 laboratories and 754 sample collection points nationwide. The company performs over 85 million tests annually, offering an extensive catalogue of 3,500 diagnostic procedures ranging from basic haematology to advanced molecular genetics and pathomorphology. ALAB Laboratoria has a history of technical leadership. It was the first in Poland to implement electronic signatures for results and the first in Europe to transport medical samples via drones.
The Challenge: Modernising patient communication with AI
As ALAB Laboratoria continued to expand, there was an opportunity to modernise the way incoming patient enquiries were handled. The organisation wanted to introduce a more advanced AI-based voice solution that could understand patient intentions more naturally and support consultants with repetitive enquiries.
ALAB Laboratoria needed a solution that could understand complex medical terminology, connect to multiple data sources and route calls accurately within its existing customer service processes.
- AI-driven patient communication: The new solution was selected to improve the naturalness and accuracy of conversations while taking over simple, repetitive enquiries and supporting consultants with more complex cases.
- Compliance and transparency requirements: As a healthcare provider handling sensitive patient data, ALAB Laboratoria set detailed requirements for technical transparency, data protection, cybersecurity and European data residency. These criteria were an important part of the selection of the new solution.
- Operational efficiency: With a large network of sample collection points and over 4,000 test SKUs, ALAB Laboratoria handles a high volume of incoming enquiries. The AI Voice Agent takes over simple, repetitive requests so consultants can focus more time on cases requiring an individual approach.
The Solution
Following a competitive evaluation, ALAB Laboratoria selected the provider based on the quality and scalability of the technology as well as the team behind it.
The implementation was initially scoped as an FAQ-style AI Voice Agent. It evolved into a more advanced deployment with five integrations across ALAB Laboratoria management systems and third-party services.
- Real-time pricing and availability. A direct connection to a database of over 4,000 SKUs allows the Agent to perform approximate matching. When a patient says “sugar test”, the system interprets and resolves it to “Blood Glucose Level” and returns accurate pricing.
- Geo-aware location search. Integrated with Google Maps API, the Agent identifies the nearest sample collection point based on the patient’s postcode, accounting for differences in test availability and opening hours by location.
- Intent-based smart routing. ACD logic maps each caller to the relevant location and consultant queue. This component required additional platform development beyond the original scope to reflect ALAB Laboratoria’s existing infrastructure.
- Human-in-the-loop design. The AI Voice Agent acts as the first line of support. When a query requires individual handling, the system transfers the call to a human consultant.
- Data residency. The solution operates exclusively within the EEA and supports ALAB Laboratoria’s Polish network. Given the sensitivity of medical data, the implementation was designed to meet European data residency and data protection requirements.
- Security and data protection. ALAB Laboratoria provided detailed requirements based on the sensitivity of medical data. Security, data protection and technical transparency were important criteria in the selection and design of the new solution.
“The configuration process went very smoothly, and the implemented solution met our assumptions and requirements. I was positively surprised that all the arrangements made during the design stage were implemented as expected.”
Diana Ciba, Customer Service Department Manager, ALAB Laboratoria
The project moved from preparation and analysis into a four-month development cycle. The AI Voice Agent’s core construction was complete within 60 working days. After technical refinement and telecom integration, the solution went live 18 weeks after kick-off.
After launch, our team ran a dedicated hypercare period, working closely with ALAB Laboratoria to check integrations and review anonymised call logs. The AI Voice Agent reached stable, high-volume operation within the first three months of production.
Results
In its first two weeks of live operation, the AI Voice Agent processed 19,844 inbound calls and 29,202 voice minutes. These volumes demonstrated the system’s ability to support a high volume of incoming patient enquiries from the start.
| Figure | Metric |
|---|---|
| ~ 80% | Calls with AI impact – 28% fully automated end-to-end; 52% pre-populated data for consultants |
| 28% | Fully automated end-to-end inbound calls |
| 52% | Pre-populated data for consultants with verified caller identity and intent |
| 15-FTE Capacity | Instant capacity for peak-hour surges at a fixed operational cost |
ALAB Laboratoria processes over 25,000 inbound calls per month. AI-driven workflows are involved in 80% of these interactions. This figure consists of 28% of calls handled fully end-to-end by the AI Voice Agent and 52% where the AI verifies the caller’s identity and intent and pre-populates information for a consultant. The AI Voice Agent averages 1.47 minutes per call, supporting enquiries that require lookups across 4,000 SKUs, sample collection point data and real-time availability. The solution also reduced repetitive workload, making over 700 labour hours available for other tasks.
Why it works
1. Automation shaped around the client’s workflows. We designed the solution to work within ALAB Laboratoria’s existing processes. Five integrations across different systems and data sources, custom APIs and geo-aware location search were built around the organisation’s requirements. 2. Accuracy in medical enquiries. Medical enquiries demand accuracy. The AI Voice Agent supports fast, consistent responses across test information, pricing, availability and sample collection point data, using real-time data retrieval where required. 3. Transparent implementation. ALAB Laboratoria placed strong emphasis on clear communication, technical transparency and defined data protection requirements throughout the project.
“We appreciate the competitive pricing model and the professional support provided by the team at every stage of the project.”
Diana Ciba, Customer Service Department Manager, ALAB Laboratoria
Automate your patient communication
Our Agentic AI Voice Agent understands medical terminology, integrates with relevant laboratory data sources and supports patient communication across large diagnostic networks. It handles simple, repetitive enquiries and transfers more complex cases to consultants when needed.
Last updated: August 2026.
