AI
In the process of transforming data into knowledge, our AI assist you.
AI plays a key role in biology, with deep learning and large language models (LLMs) revolutionizing data interpretation and research efficiency. Bio big data, including multi-omics, literature, and medical imaging, is analyzed by AI to transform it into meaningful knowledge.
Insilicogen’s AI technology supports time-series data, large-scale unstructured data in healthcare and pharmaceuticals, and image analysis, uncovering hidden patterns and insights through structuring and machine learning. Combining LLM and Retrieval-Augmented Generation (RAG) technologies maximizes research efficiency through real-time data interpretation and literature summarization.
We lead innovation in life sciences research with AI-based data analysis, providing optimal AI solutions for precise decision-making.
DATA-BASED KNOWLEDGE
Maximize research efficiency by semantically structuring bioinformatics data and build a standardized data interpretation environment
Analyze patterns and create predictive models by learning large-scale bioinformatics data such as genomes and transcriptomes.
Processing complex biological data and deriving gene functions using advanced analysis techniques based on neural networks
OUR SERVICE: AI Voucher Supply Company
LLM
This platform supports literature search, data-driven knowledge inference, analysis automation, and customized information generation in life science research. Key features include domain-specific LLM development, RAG-based knowledge inference system, and custom LLM chatbot applications. LLM development aims to build language models optimized for specialized knowledge, while the RAG-based system organizes accurate information through vector DB and real-time API technology, supporting precise Q&A with LLM.
- Large Language Model
- PEFT
- RAG
- LangChain
- Vector DB
CV
Image Detection, Segmentation, and Classification
We can apply the latest deep learning algorithms that detect objects from the image in real-time and divide the significant areas from the image by using segmentation technology. Additionally, we generalize the images in various ways through computer image preprocessing technology to apply the latest deep learning algorithms with the highest accuracy possible. For data labeling, we have a technology that provides an interface for image area labeling for automatic area recognition.
- OpenCV
- Image Detection (YOLO v3)
- Image Classification
- Image Segementation (U-Net)
RECOM
Artificial Intelligence Recommender System
Beyond the existing collaborative filtering and content-based filtering, we provide a solution that customizes products in the company based on the latest recommendation system that combines existing machine learning and deep learning technique. We suggest optimal recommendation results to achieve the target indicator based on product meta-information, customer meta-information, and target indicator information. The recommender system applies in various fields such as product recommendation as well as content preference.
- Wide & Deep Learning for Recommender System
- Deep FM
- AutoRec
- KGCN
ORIGINAL TECHNOLOGY
