SciSure helps scientific organizations replace fragmented, disconnected systems with a single governed platform for managing lab operations, so teams spend less time reconciling data across tools and more time on research. By combining Electronic Lab Notebook (ELN), Laboratory Information Management System (LIMS), and Health & Safety (EHS) capabilities in one system, SciSure improves reproducibility, strengthens visibility into day-to-day lab activity, and helps organizations reduce risk as they scale. Researchers document experiments, protocols, and results in a structured, searchable digital format with customizable templates and version control, replacing paper notebooks and scattered files. Samples are tracked from intake through processing, storage, and disposal, maintaining full lineage and chain-of-custody records alongside chemical and general lab inventory management and workflow automation. Health & Safety functionality is built into the same platform, covering chemical inventory alongside Safety Data Sheets (SDS), regulatory compliance workflows, and audit readiness, so labs don't need a separate system to stay compliant and audit-ready.
Labs can also extend the platform through an optional marketplace of add-ons, so they can bring in additional capability, like AI-powered support, automated data analysis, protocol generation, toxicity prediction, and image analysis, only where it adds value, without disrupting the rest of their workflow or committing to features they don't need. SciSure also connects directly to lab instruments, external databases, and third-party tools, so data moves between systems without manual re-entry.
SciSure supports both cloud and dedicated hosting, giving organizations control over the deployment model that fits their infrastructure, security, and compliance requirements. It's built to serve academic institutions, biopharma and biotech companies, and start-ups alike, with role-based support for scientists, lab operations staff, safety and compliance teams, leadership, and IT professionals, so the platform works the way each type of user actually needs it to.
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AlisQI is a modular, cloud-based Quality Management platform for process and batch manufacturers who want to reduce firefighting, improve predictability, and stay compliant by default.
Unlike traditional EQMS platforms that were built around documents and later adapted for analytics, AlisQI was designed from the start as a data-first system. Quality, lab, and production data are structured and connected in one operational backbone.
That foundation now enables practical AI capabilities inside daily workflows. Manufacturers can automatically extract data from diverse supplier COAs without predefined templates, generate structured digital forms from existing files or plain language, query their QMS conversationally, and detect recurring incident patterns across sites.
Core modules include Document Control, Training, Deviations, CAPA, Audits, Risk Management, Supplier Quality, SPC, and EHS, supported by targeted out-of-the-box Solvers that address specific operational problems.
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ESMC
ESMC is the latest in the ESM family of protein language models, establishing a new frontier in representation learning for protein biology. Trained on billions of evolutionary sequences, it learns representations that reflect a mechanistic reduction of protein structure and function. The model is built on a transformer architecture, supports sequences as its core modality, and is trained on up to 6 billion proteins. ESMC is designed for protein science research, including structure prediction, function annotation, protein design, and understanding evolutionary relationships between proteins. It can generate novel proteins from partial sequence, structure, or functional constraints, helping researchers explore new possibilities in protein design and biological discovery. The Biohub Platform provides access to ESMC through the API and the ESM Python package, with quickstart resources for installing the package, creating an API key, connecting to the platform.
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