High-Performance Data Engineering. 100% Sovereign.
TIMi delivers the full power of a enterprise data cloud—on-premises, fully sovereign, and blisteringly fast.
No vendor lock-in. No hidden costs. Just pure engineering excellence that gives your team total freedom to experiment, innovate, and solve your toughest AI and automation challenges in record time.
The TIMi Advantages:
No-Code Integration: Automate complex workflows and connect your entire tech stack instantly—from SAP and Salesforce to SharePoint and Google BigTable.
Radical Efficiency: Competitors such as Databricks, Dataiku, and MS Fabric relies heavily on a Spark back-end. Spark quickly burns budget because of bloated Java virtual machines. TIMi strips away the waste with pure, bare-metal, hand-optimized assembly code. The result: A single €2k TIMi server outperforms a 267-node Spark cluster, processing billions of rows in seconds and effortlessly running petabyte-scale data lakes at a fraction of the cost.
Pioneering AI: Harness advanced machine learning built on the legacy of the first Auto-ML engine (pioneered in 2007).
Available on-premises or via our EU-Hosted Sovereign Cloud. Trusted across Telecoms, Banking, Manufacturing, Retail, Defense, and Government.
Learn more
Docket's AI Marketing Agent engages website visitors through real, human-like conversations, responding to nuanced evaluation questions with expert-grade answers from your approved knowledge, running live discovery to qualify intent, and converting high-intent buyers into qualified leads, booked meetings, and pipeline. 24/7, without a human in the loop at each step.
Beyond inbound engagement, Docket's governed knowledge foundation gives revenue and pre-sales teams instant access to product knowledge, collateral, and competitive intelligence — and drafts customized content grounded in your enterprise knowledge in seconds.
Learn more
Delta Lake
Delta Lake acts as an open-source storage solution that integrates ACID transactions within Apache Spark™ and enhances operations in big data environments. In conventional data lakes, various pipelines function concurrently to read and write data, often requiring data engineers to invest considerable time and effort into preserving data integrity due to the lack of transactional support. With the implementation of ACID transactions, Delta Lake significantly improves data lakes, providing a high level of consistency thanks to its serializability feature, which represents the highest standard of isolation. For more detailed exploration, you can refer to Diving into Delta Lake: Unpacking the Transaction Log. In the big data landscape, even metadata can become quite large, and Delta Lake treats metadata with the same importance as the data itself, leveraging Spark's distributed processing capabilities for effective management. As a result, Delta Lake can handle enormous tables that scale to petabytes, containing billions of partitions and files with ease. Moreover, Delta Lake's provision for data snapshots empowers developers to access and restore previous versions of data, making audits, rollbacks, or experimental replication straightforward, while simultaneously ensuring data reliability and consistency throughout the system. This comprehensive approach not only streamlines data management but also enhances operational efficiency in data-intensive applications.
Learn more
Cribl Search
Cribl Search unveils a groundbreaking search-in-place feature that enables users to seamlessly explore, discover, and analyze data previously considered unreachable, directly from its origin across various cloud platforms, including data protected by APIs. Users can navigate through their Cribl Lake or inspect information housed in major object storage solutions like AWS S3, Amazon Security Lake, Azure Blob, and Google Cloud Storage, while also enriching their findings by querying multiple live API endpoints from different SaaS providers. The primary benefit of Cribl Search lies in its ability to transmit only the necessary data to analytical systems, effectively reducing storage-related costs. With built-in support for platforms such as Amazon Security Lake, AWS S3, Azure Blob, and Google Cloud Storage, Cribl Search presents a distinctive chance to analyze all data right where it is stored. Additionally, it enables users to conduct searches and analyses on data no matter its location, whether it be debug logs at the edge or information archived within cold storage, thus enhancing their data-driven decision-making capabilities. This flexibility in data access not only simplifies the insight-gathering process from varied data sources but also fosters a more agile and responsive analytical environment. As a result, organizations can more swiftly adapt to changing data landscapes and make informed decisions based on real-time insights.
Learn more
