Agentic AI for Scientific Research
Notes9 is an AI-native electronic lab notebook that unifies experimental records, inventory management, literature, and analysis in a single, structured workspace.
To design an AI-augmented research environment that reduces manual overhead, strengthens reproducibility, and helps scientists move from hypothesis to robust results with fewer fragmented tools.
We envision every research group working alongside an AI assistant that understands their projects, preserves institutional knowledge, and provides transparent support across the entire discovery lifecycle.
Our Story
Notes9 emerged directly from the day-to-day experience of working in academic and industrial laboratories. As bench scientists and data scientists, we repeatedly encountered the same pattern: project-critical knowledge scattered across paper notebooks, PDFs, and ad-hoc spreadsheets.
Conventional ELNs improved record-keeping but did little to help researchers reason with their data. Generic LLMs showed promise but lacked the domain awareness required for serious rigor.
Notes9 is our response: an agentic AI layer built on top of a structured research workspace, designed to assist with literature triage, experiment design, data curation, and analysis—while preserving clear provenance and oversight.
Our Team
Notes9 is led by a multidisciplinary group of scientists and engineers with backgrounds in pharmaceutical sciences, AI, and software development.
Pharmaceutical science Phd Scholar focusing on PBPK modeling, translational pharmacokinetics, and dose projection. Industry and academic experience bridging quantitative modelling with drug development strategy. Registered Patent Agent in India.
Full-stack engineer currently working at Asanify, where he builds and maintains production SaaS platforms for HR and payroll. Experienced in designing scalable web architectures, setting up robust developer tooling, and translating product requirements into reliable, ship-ready features.
Machine learning engineer specialising in agentic AI systems and clinical-trial data extraction. Research experience in healthcare AI applications, model evaluation, and deployment in regulated environments.
Research Assistant at the Jenner Institute, University of Oxford, working on malaria vaccine development and protein engineering. Experienced in end-to-end experimental design, biophysical characterisation, and collaborative translational research.
Formulation scientist with experience in nanoparticle-based drug delivery, and forecasting for pharmaceutical portfolios. Former analyst at PharmaACE working at the interface of science, strategy, and health economics.
Applied AI developer with expertise in document-processing pipelines, information retrieval, and human–computer interaction. Has contributed to production AI systems at Equifax and multiple early-stage technology startups.
Get in Touch
Notes9 is currently in an early-access phase. We are actively seeking design partner labs and investment opportunities.