Henosis turns raw electrochemistry measurement files into structured knowledge, computed results, searchable experiments and publication-ready scientific output.
Upload entire folders or multiple
.DTA raw files up to 20MB.
Henosis inspects headers, identifies the experiment type,
selects axes and plots instantly.
Henosis connects measurement data, analysis and scientific interpretation into one continuous workflow.
Import raw files from electrochemical instruments and transform them into a consistent, structured data model.
Calculate scientifically defined quantities such as onset potential, Tafel slope, peak separation and electrochemical performance metrics.
Use structured experimental data as a reliable foundation for AI workflows, assistants and scientific knowledge systems.
Generate consistent figures, datasets and analysis outputs suitable for reports, presentations and scientific publications.
Search across experiments, samples, catalysts, conditions, measurements and computed results instead of digging through folders.
Turn repeated analysis procedures into standardized workflows that can be executed consistently across experiments and teams.
Henosis creates a structured layer between your instruments and the scientific decisions you need to make.
Instead of keeping measurements, metadata, calculations and figures separated across files and software, Henosis creates one connected representation of your experiments.
This makes your data easier to reproduce, search, analyze and ultimately use for scientific decision-making.
Henosis is designed to work across the measurement and analysis methods used in modern electrochemical research.
Henosis combines hands-on electrochemical research with software engineering, data processing and scientific characterization.
Dara combines several years of hands-on experience in chemistry and electrochemistry with expertise in scientific data processing, visualization and software development. His work focuses on transforming complex electrochemical measurements into structured, analyzable and reusable scientific data, while implementing AI-driven tools for research workflows.
Enado holds a Master's degree in Mechanical Engineering from Ruhr University Bochum and works as a scientific researcher in electrochemistry and electrocatalysis. His expertise covers electrochemical characterization methods, experimental design and the investigation of electrochemical systems and catalytic materials.
Henosis brings together electrochemical expertise and digital infrastructure to solve a problem that sits between science and software: making experimental knowledge structured, reproducible and computationally useful.
Henosis Intelligence is focused on one problem: electrochemical research produces enormous amounts of valuable data, but much of that knowledge remains trapped inside files, spreadsheets and individual researchers' workflows.
Henosis is building the infrastructure to turn that data into a persistent, searchable and computational scientific asset.
Interested in using Henosis in your laboratory or organization? Get in touch to discuss your workflow.
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