SciSummary

Iris.ai is a world-leading and award-winning AI engine for scientific text understanding. It is a comprehensive platform for all research-related knowledge processing needs. Our Researcher Workspace solution provides smart search and a wide range of smart filters, reading list analysis, auto-generated summaries, autonomous extraction, and systematising of data. Iris.ai allows humans to focus on value creation by saving 75% of a researcher’s time, doing specialised, interdisciplinary field analysis to an above human level of accuracy. Its algorithms for text similarity, tabular data extraction, domain-specific entity representation learning, and entity disambiguation and linking measure up to the best in the world. Its machine builds a comprehensive knowledge graph containing all entities and their linkages to allow humans to learn from it, use it, and give feedback to the system. Applying these features to scientific and technical text is a complicated challenge few others can achieve.

FutureHouse is a nonprofit AI research lab focused on automating scientific discovery in biology and other complex sciences. FutureHouse features superintelligent AI agents designed to assist scientists in accelerating research processes. It is optimized for retrieving and summarizing information from scientific literature, achieving state-of-the-art performance on benchmarks like RAG-QA Arena's science benchmark. It employs an agentic approach, allowing for iterative query expansion, LLM re-ranking, contextual summarization, and document citation traversal to enhance retrieval accuracy. FutureHouse also offers a framework for training language agents on challenging scientific tasks, enabling agents to perform tasks such as protein engineering, literature summarization, and molecular cloning. Their LAB-Bench benchmark evaluates language models on biology research tasks, including information extraction, database retrieval, etc.