Timeflow SaaS is our low-code software platform which makes it easy to ingest, process, analyse and respond to your business data in real time.

It allows you to connect to various websites, databases, enterprise applications and other data sources, collect that information in real time, and make it available to your business users, data analysts and data scientists so they can operate on real time data.  

Why Is This Needed?

Most business intelligence and analytics initiatives are based on

Why It’s Different


The data and analytics market is very crowded, with all kinds of tools for capturing, processing, storing and analysing data.  Understanding which tools and platforms you need can be overwhelming, and managing and operating all of them can be an expensive undertaking.  For this reason, it’s important to only introduce new tools where they add new capabilities and business value.

We believe that the Timeflow meets this bar, standing on its own as a new class of data analytics solution which focuses on processing real time data intelligently, and putting the powerful tools to do so directly into the hands of citizen developers and power users.

1)

Processes real time data feeds so we can identify insights as soon as they happen when they are most valuable.

Have a delay whilst data travels from a source application into a centralised reporting database, perhaps of a day or more.

2)

Processes data as it happens and whilst it is “in flight” before it gets to a database.

Are oriented around storing or ad-hoc reporting on data within a large database after it has happened.

3)

Allows complex statistical and machine learning models to be applied to real time data feeds.

Are generally about filtering, querying and aggregating relational data in simple visual ways.

4)

Processes data from all kinds of business scenarios such as orders, customer interactions or IOT devices.

Are often focussed on IT event data such as high volume log files or security scenarios.

5)

Allows you to identify the specific situations of interest that you can act upon in the moment.

Are all about ingesting very large volumes of data for ad-hoc analysis after the fact.

6)

Allows citizen developers and power users to experiment with data feeds and build powerful analytics scenarios

Are often focussed at specialists or IT staff to be able to configure and use.