The LIMS for more efficiency with AI
Use SAMPLES and the possibilities of artificial intelligence to take your laboratory to a new level.
From hype to efficient game changer
For the integration of AI applications, the LIMS requires a modern software architecture with open interfaces and structured data. SAMPLES sets new standards here and has everything you need to make the world of AI fully accessible to you.
Exemplary applications include quality control, optimization of work processes, analysis of individual results or learning from large amounts of data.
…or a conversation with ChatGPT about your data in SAMPLES.
Whatever drives you when it comes to AI:
There are virtually no limits to the implementation scenarios. We are happy to support you in the realization of your ideas.
- Big data with AI
- AI-optimized quality control
- AI-based predictions
- AI chat
- Data analysis with AI
Simply interact with the LIMS via AI chat
SAMPLES has everything you need to get the most out of your data with artificial intelligence. In a prototype chat app, we have connected ChatGPT with SAMPLES and thus made the data easily accessible. Watch the video to get a first impression of the fascinating possibilities it opens up…
From the relieving voice control of the LIMS to the diverse access and evaluation options and the direct linking of query results to the LIMS, even this small example clearly shows the great potential of AI for increasing efficiency in the laboratory.
This prototype of a chat app uses both ChatGPT and the SAMPLES interface to interact with the laboratory data in the LIMS in human language.
Our technical article in the SPECTARIS publication
We have also published a technical article on this topic entitled “Efficiently simplifying everyday laboratory work with ChatGPT” in the publication “Artificial intelligence in the laboratory” by SPECTARIS, the association of German laboratory equipment manufacturers.
We have prepared this for you in the white paper of the same name. You can download it as a PDF below.
GraphQL – API
GraphQL is the high-performance interface technology that GitHub, Twitter, Airbnb and the New York Times also rely on.
The entire SAMPLES data schema is documented in a structured manner. The interface enables direct access to all data and functions of the application. To work with the interface, you need knowledge at the level of a web developer (or enough motivation and some support from ChatGPT).
SAMPLES provides free, clearly documented access to all your laboratory data and metadata.
Hands-on GraphQL interaction with SAMPLES
Query data
GraphQL queries are used to query data via the interface. These return the desired result in the common JSON format.
Compared to REST interfaces, GraphQL is much more efficient and performs better, as it only returns the desired data points rather than entire data sets.
Create & change data
GraphQL mutations are used to create or change data in SAMPLES.
SAMPLES validates all changes on the server, i.e. you receive the same error messages via the interface as in the frontend.
Many data analysis tools offer functions for statistical analyses, machine learning and artificial intelligence.
Use them with your data from SAMPLES.
- TensorFlow
- KNIME
- Altair AI Studio
- H2O.ai
- PyTorch
Experience & test SAMPLES now!
We invite you to experience the award-winning SAMPLES in a compact live demo. If you are interested, you can also test SAMPLES free of charge and without obligation. We look forward to your registration.