
High-Performance Data Engineering. Total Sovereignty.
TIMi delivers the power of a complete cloud data stack—on-premises, fully sovereign, and ridiculously fast.
We reject artificial vendor lock-in and hidden costs. Instead, we offer absolute peace of mind through engineering excellence, giving your team the freedom to experiment, innovate, and solve complex AI, analytics, and automation challenges in record time.
Why Top Enterprises Choose TIMi?
Enterprise Integration & *No-Code* ETL/Data preparation: Automate complex workflows and seamlessly link your entire stack: SAP, Salesforce, SharePoint, S3, Azure Storage, PowerBI, Tableau, etc.
Unmatched Infrastructure Efficiency: Our competitors such as Databricks, Dataiku, and MS Fabric all rely on Spark—and that makes them inherently inefficient since a single €2k TIMi server outperforms a 267-node Spark cluster. TIMi process billions of rows in seconds and manage petabyte-scale data lakes at a fraction of the cost.
Proven AI Leadership: Harness pioneering machine learning from the creators of the first Auto-ML engine (est. 2007).
Whether deployed on-premises or via our EU-Hosted Sovereign Cloud, TIMi empowers leaders in Banking, Telecoms, Manufacturing, Retail, Defense and Government.
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Knak is the enterprise-grade, no-code solution that transforms how marketing teams build emails and landing pages — without relying on developers or agencies.
With a robust modular design system, real-time collaboration, and native integrations with platforms like Marketo, SFMC, and Eloqua, Knak eliminates production bottlenecks while preserving brand governance. Empower your team to deliver high-performance assets quickly, securely, and at scale — no code required. Trusted by global brands to streamline campaign execution and accelerate time-to-market.
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alvaModel
alvaModel is an advanced software application designed for the construction, validation, comparison, and implementation of QSAR and QSPR models. It excels in supporting both regression and classification tasks through the use of molecular descriptors and fingerprints, emphasizing transparency, interpretability, and scientific rigor in its models.
This software offers a variety of data splitting techniques, variable selection approaches, and modeling algorithms, as well as thorough internal and external validation methods. Additionally, alvaModel includes diagnostic visualizations, applicability domain evaluations, and tools for model comparison, which aid users in pinpointing reliable and predictive modeling solutions.
Crafted in accordance with the highest standards of chemometrics, alvaModel promotes the creation of interpretable models that align with OECD guidelines for QSAR validation, making it ideal for both research and regulatory uses. Its user-friendly graphical interface walks users through the entire modeling process while providing comprehensive control over every aspect of the modeling journey, ensuring a seamless experience. Ultimately, alvaModel stands out as a valuable asset for chemists and researchers aiming to enhance their modeling capabilities.
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Develve
Develve is a statistical software designed for the quick and straightforward analysis of experimental data within scientific and research settings, making it especially beneficial for both novice and experienced users. This package not only streamlines analysis but also minimizes the risk of erroneous conclusions. It prioritizes user-friendliness by eliminating complex hidden menus, ensuring that users can easily access all features and see results instantly, thereby enhancing overall efficiency. For example, users can seamlessly scroll through result graphs, and a simple click will enlarge them for better visibility. Develve also provides clear indications of significant differences between variables and assesses the adequacy of sample sizes to avoid misleading assumptions. It supports the Design of Experiments by assisting in the creation of test matrices and detects any imbalances among factors. Consequently, this software is instrumental in developing robust, high-quality products, establishing it as an invaluable tool in Six Sigma methodologies, and ultimately contributing to improved research outcomes and product success.
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