Advanced visual data mining and prediction system that enables you to analyse diverse, multi-dimensional and complex datasets.
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Better analysis of complex data

Deep Topological Analysis is an evolution of cutting edge data science which combines Topological Data Analysis and Deep Learning. This approach delivers provable performance gains over competing technologies.

Faster workflow

The simplicity of the DataRefiner platform saves time. Automated checks for data consistency, automatic selection of model parameters and other features make your data analysis pipeline orders of magnitude faster.

Explainable Artificial Intelligence

We have unique algorithms designed to make the process visual and accessible. Understand and communicate results with your organisation, clients and regulators.

How much do you know about your data?

Most data is not organised or structured making it hard to find the important patterns.

Your data is the biggest asset of your business

High level data segmentation can help any business thrive.

But what if its sources are user activities, sensors or texts?

Current business intelligence systems do not allow you to segment or discover patterns in such data. That’s where DataRefiner comes in: it provides tools to understand such data.

Transform your data into a data map

Imagine you could transform your data into a data map in just a few clicks and without specialist knowledge.

Deep Topological Analysis

Using machine learning, we group complex data into clusters, which allows users to discover hidden patterns.

State-of-the-art data segmentation

DataRefiner uses a unique algorithm to group complex data into clusters using deep topological analysis. It maps the segments and describes them to any business user without specialist training.

Visualise patterns in your data

You’re in control of the results: you can identify anomalies, predict behaviour, target audiences or eliminate engineering errors.

Customer and user activities

Extract personas from your user activities to understand their needs, experiences, behaviours and goals.

Internet of Things

Telemetry from your sensors provides important patterns for your equipment. Understanding of such patterns allow you to make improvements.

Bank transactions or crypto currency analysis

Spot anomalies or unusual patterns in your data. Perform deep analysis of such patterns using most advanced technology available on the market.

Discover things you haven't even started looking for

Patterns in your data are visualised to make them clear to anyone: from data scientists to business users.

Explainable AI

Achieve explainable results. DataRefiner visualises features in your data and makes them clear to data scientists or business users. It allows you to easily understand and communicate results within your organisation, to clients and regulators.

Сomply with GDPR

Make sure your machine learning systems are not biased against different groups of people. DataRefiner helps you verify the results of your algorithm.


Use Cases

User activity segmentation

DataRefiner allows you to visualise complex user activities and to find activity patterns that are important for your business. Group your users and tailor your app or a website to their needs.
Example: Find “personas” in your activity data
Add to A/B test

User Activities

Activities, captured from user interactions with the app

S3, RedShift or in-house DBs

Activities are stored in the database or a message queue


DataRefiner performs segmentation of user activities and extracts users' personas

Export segmentation result

Download a user segment using DataRefiner API

Perform a targeted marketing campaign

Target user groups precisely according to their activity patterns and be GDPR compliant

Analysis of text or user comments

Perform segmentation of the posts, user comments or any other user generated content. Fight spammers, scammers and other unwanted behaviour on your platform. Using DataRefiner you're able to visualise and understand common patterns much faster than with traditional NLP approach.
Example: Fight spammers and scammers by analysing your users' text data

Collection of texts or messages

User comments or posts, stored in your databases

CSV file with the texts

Prepare a collection of comments or user posts as CSV file


DataRefiner performs segmentation of texts and extracts common topics

A data analyst reviews the structure

An analyst understands the formed clusters and extracts the anomalies

Present the findings

Use DataRefiner player to show your findings to internal or external audiences

Analysis of sensors data (IoT) and
anomaly detection

Analyse telemetry from your hardware equipment: civil aerospace, defence, power systems, robotics and any other source of complex IoT data. Find the unexpected operational patterns and improve the performance.
Example: Find the unexpected operational patterns in aircraft engines

Time series data streams from sensors

A stream of real-time data from sensors

AWS or Azure cloud infrastructure

Raw sensor data is stored and pre-processed


DataRefiner performs segmentation of telemetry data

A data analyst reviews the structure

A subject matter expert reviews the structure and identifies the unexpected patterns

Present the findings

The findings are presented to equipment engineers for further review and re-configuration

Analysis of the bank or blockchain transactions

Identify patterns in the bank or blockchain transactions. Visualise complex schemes: fight money laundering and fraud. Understand how your initial coin offering performs and identify real users and bots among your clients.
Example: Find money laundering schemes

Crypto currency ledger

A list of account transactions with related metadata

Bank account ledger with metadata

A list of account transactions with related metadata


DataRefiner finds account activity patterns

Data Analyst / Regulator reviews the structure

Data structure reveals different account patterns including undesirable ones

Bank security review the threat

A list of suspicious accounts is reviewed in details

Analysis of graph data for ratings,
votes or questionnaires

Analyse a wide range of graph and network data: social graph, user activity graph, reviews, telecom network statuses. Visualise and understand interaction and differences between the subgroups.
Example: Find the different groups of audiences using their ratings or likes on your platform

Collection of user ratings or answers

User rating for movies, music, cafes; user votes or answers to multiple selection questionnaires

CSV file with the votes

Collection of user votes and ratings in one CSV file for analysis


DataRefiner finds common patterns and presents its structure

A data analyst describes user groups

An analyst reviews users grouped by their preferences and identifies the key questions or important issues for a community

Present the structure to a monitoring team or a client

Use DataRefiner player shows your findings to the internal or external audiences

Cyber security (analysis of the packets and flows)

Identify activity patterns in your network using data from a wide range of agents. Allow your security analysts to identify the dynamic threats by going beyond the predefined security patterns.
Example: Identify the dynamic threats in your corporate network
Agent 1
Agent 2
Agent 3
Agent X
Reports on previously suspected activity
Update the rules

Network monitoring agents

A large number of network monitoring agents are performing flows and packets monitoring

Aggregated signals from agents

The stream of signals from monitoring agents


DataRefiner constantly learns on a data stream and produces activity patterns

A data analyst reports suspicious patterns

An analyst identifies suspicious network behaviour and marks it

Cyber security system

DataRefiner reports finding to an internal cyber security system used by security analysts.

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