Teradata VantageCloud: Open, Scalable Cloud Analytics for AI
VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.
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LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents.
Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development.
Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
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PhysChem Suite
Calculate the physicochemical properties of organic compounds such as boiling point, aqueous solubility and logD, logP, pH, pKa, and other molecular descriptors from chemical structure.
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alvaMolecule
alvaMolecule serves as a no-code cheminformatics platform designed to visualize, curate, and standardize molecular datasets in preparation for analysis. It accommodates popular molecular formats, including SMILES and SDF/MOL2, allowing users to navigate through collections in either grid or spreadsheet formats, with automatic import of relevant data. This tool ensures structure verification and standardization via pre-set standardizers and customizable SMIRKS rules, facilitates the identification and management of duplicates, and provides scaffold analysis for summarizing fundamental frameworks.
Additionally, it features integrated filters and charting options that allow sorting based on substructures, calculated molecular descriptors, and physicochemical properties. alvaMolecule is capable of calculating around 88 structural and physicochemical properties, which encompass drug-like and lead-like scores such as LogP, TPSA, and the Lipinski alert index, ultimately assisting users in generating high-quality datasets for QSAR/QSPR modeling, descriptor calculations, and virtual screening processes. Furthermore, its user-friendly interface ensures that researchers, regardless of their coding expertise, can easily navigate and utilize the tool to enhance their cheminformatics tasks effectively.
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