Accelerating Scientific
Discovery Through Trusted Data
From data curation to lab automation, we build the infrastructure that empowers researchers to focus on what matters — real breakthroughs.
Infrastructure for Modern Research
Three pillars of technology, purpose-built to bridge the gap between raw scientific data and actionable discovery.
Scientific Data Curation
Purpose-built algorithms that validate and clean research data — from literature mining and computational simulations to real experimental measurements. Over 1M datasets curated, enabling 10+ published studies.
- Literature data extraction & cleaning at scale (100K+ records)
- Simulation data validation: DFT, MD, CFD with physics-aware filters
- Experimental data curation with domain-specific outlier detection
- Proven 2x+ accuracy gain in downstream ML models after curation
Lab Automation Systems
End-to-end design and development of automated laboratory workflows with intelligent control systems, custom-built for your research objectives.
- Custom automation architecture for research labs
- Real-time instrument control and monitoring
- Intelligent scheduling and experiment orchestration
- Seamless integration with existing lab equipment
Scientific Databases
High-quality, curated private databases co-built with leading research institutions. Production-ready datasets that directly accelerate your R&D pipeline.
- Materials science: CVD synthesis databases for nanomaterials
- Co-curated with university research groups and R&D enterprises
- Standardized schemas with rich metadata and provenance tracking
- API access and flexible data delivery formats
Built by Scientists, for Scientists
We are not another generic data company. We are researchers who became engineers to solve the problems we faced firsthand.
Born from Research
Our founding team comes directly from the research bench. We understand the pain points of scientific data because we lived them — from noisy simulation outputs to irreproducible experimental results.
Purpose-Built Algorithms
Unlike generic data tools, our algorithms are designed from the ground up for scientific data. We account for physical constraints, measurement uncertainties, and domain-specific patterns that off-the-shelf solutions miss.
End-to-End Coverage
From raw data cleaning to curated databases, from manual experiments to fully automated labs — we cover the entire research data lifecycle under one roof.
Accelerate, Don't Replace
We don't aim to replace researchers. We build the infrastructure that removes friction, so scientists can spend their time on hypothesis and discovery, not data wrangling.
Trusted by Leading Institutions
We have delivered successful projects with 4 partners across academia and industry — from joint publications to production data pipelines. Our work spans institutions in Singapore, China, and Europe.
University Research Groups
Joint projects with leading research labs in Singapore and China on data curation and materials informatics
R&D Enterprises
Ongoing collaborations with industry partners on automated data pipelines and proprietary database development
“We prioritize the privacy and intellectual property of our partners. All collaborations operate under strict data governance frameworks.”
From the Lab Bench to the Tech Stack
SciScale was founded by researchers and engineers who lived the pain of broken scientific data workflows — and decided to fix them.
From cleaning noisy CVD growth data to manually controlling lab equipment at 2 AM — we knew there had to be a better way. Today we are building the data infrastructure layer for scientific research: trusted data, intelligent automation, and curated knowledge, all in one place.
Our team spans materials science, biomedical informatics, computational chemistry, and systems engineering. Every product we ship is informed by years of hands-on research experience — not just engineering intuition.
Founding Team
The people behind SciScale
Stella Pan
Co-founder & CEO
Business strategist with experience leading early-stage tech ventures. Drives SciScale's partnerships, go-to-market strategy, and operations across academia and industry.
Yuri Li
Co-founder & CTO
Systems architect and full-stack engineer specializing in scientific computing, data pipeline design, and automation. Leads all technical development and algorithm design at SciScale.
Kevin Guo
Co-founder & Chief Medical Advisor
Biomedical domain expert with research background in clinical data analysis and medical informatics. Bridges the gap between healthcare R&D needs and SciScale's data capabilities.
Research & Engineering
Domain experts driving our core technology
Dr. Wei Lin Tan
Senior Materials Scientist
Specialist in thin-film deposition and CVD process optimization with 8+ years in nanomaterials characterization and process-property mapping.
Dr. Elena Vogt
Computational Materials Researcher
Expert in first-principles simulations (DFT) and molecular dynamics. Focused on data-driven materials discovery and ML-assisted property prediction.
Ready to Accelerate Your Research?
Whether you need to clean your data, automate your lab, or access curated databases — let's talk about how SciScale can help.
Email Us
contact@sciscale.io
Schedule a Demo
See our platform in action
Response Time
We typically respond within 24 hours