Secure and privacy-preserving data management and analytics.

Connect, protect and explore your data with our secure, integrated platform. Resolve data inconsistencies via data hygiene, and yield new data structures that favor analysis and various data derivations. Accelerate data-driven decision making with comprehensive data visualization for various applications – while protecting data at rest, in transit and in use. 

The Problem

Manual data management workflows are time-consuming, prone to errors, inefficient, generate duplication, ad-hoc, and hard to inspect for errors. Algemetric’s platform enables entire workflows to be mapped and automated, becoming a process within applications. This process generates the same output as manual processing, without the problems associated with manual operations – all while fortifying data privacy and security.

Secure Data Management Prevents:

The Solution:

Algemetric provides a secure and privacy-preserving data management and analytics platform. It handles data collection, preparation, and visualisation for providing insights, analytics, and intelligence from multiple independent data sources in a unified way. The platform provides the flexibility to handle arbitrary formats and complex patterns, ensuring that these datasets are informative. It also offers a comprehensive set of data visualisation mechanisms that can be extended to address the specific needs of various niche applications.


Take control of inefficient manual data management. 


Fortify your data privacy and security. 


Derive insights and  intelligence from valuable and sensitive data.  

How Algemetric's Platform Works

Initially, Algemetric conducts an assessment to determine your data-driven needs. Upon inspection of all functional, legal and corporate requirements, the applicable algorithms are defined in the platform. The Data Collector will then obtain data from the data sources an organisation uses in its operations. Data sources can be from external services and/or from manual input. Once data is properly obtained, it is subject to a comprehensive process of data preparation. The output of the preparation process is sent to storage as a unified data structure ready to be used. From that point on, the application is ready to operate via the dashboard where users will request reports, visualisations, and integrations with external tools where required. 

Dashboard: The control room for data management. The dashboard is composed of three main components:


  1. Data Connector – The mechanism responsible for connecting to many arbitrary data sources and executing a series of pre-defined procedures for data preparation. The Data Connector is also able to receive new instructions and expand its data preparation capabilities.
  2. Data Visualization – Every main algorithm specified in in the platform has a visualization mechanism defined for the associated result data set. The default visualization objects are graphs from a wide variety of graph types. However, custom visualization options can easily be added.
  3. Recommendations – From collected and processed data, the platform provides recommendations whenever applicable. Data used for recommendations is tagged and can be used as an input for machine learning algorithms, providing recommendations according to predefined rules. 

Storage: The unified data structure organized by the platform. A hygienic and consistent database for strategic data processing.


Platform API: The brain of the entire data processing operation. The Platform API is responsible for managing algorithms and their output – providing the dashboard information required for its operation.

Data Source Management: Add, configure, modify, and remove data sources even if no API is available. Also, input data manually via the dashboard. Manual inputs are enabled by forms that can be defined and managed on the dashboard.


Report Management: An expandable collection of customizable and collaborative reports.


Visualization Management: Decide how data is displayed by choosing from a collection of predefined graphs and tables, or by creating a new one.


Integration Management: Configure and export results directly to other tools, when desired.


Recommendation Engine: Data points are considered for data classification and training, according to selected decision targets, to establish a recommendation system.

Secure Data Processing: When working with encrypted data, data is protected in use.


M2M IAM: When working with plain data, data is protected at rest and in transit.

Automation: Well-defined procedures must be automated to save time and eliminate human error – increasing the efficiency of data workflows.


Complexity Reduction: Manage large data sets with various data sources working together. Automate data processing for insight generation and business intelligence – handled by a unified and powerful platform. Eliminate the need for a large number of tools offering partial and overlapping solutions.


User-Friendly: Engage with an easy to use and rewarding platform -without needing in-depth technical knowledge. 

Versatility: We enable customized capabilities on an as-needed basis. 

Augment Customer Strategic Information: No matter how valuable customer data is, add strategic value to your operations.

Data Collection: Collect and input data, either from external services or manually within the application.

Data Preparation: Automated data hygiene, unification, and readiness.

Data Processing: Includes all reports and intelligence on data.

Data Visualization: Render data results with lists, files, graphs and other visualisation objects – or export to external tools like Tableau and Microsoft Power BI. 


Actionable insights and intelligence. 

Secure and privacy-preserving.

Automated data processing.

Efficient and scalable computation.

Identity and access management. 

Simplified analytics workflows. 


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