Become a Composable Business and accelerate digital transformation
Organisations have been undertaking digital transformation initiatives for the last decade, and this has enabled them to make progress on monetising data assets and optimising business processes. However, since then, progress has plateaued.
In order to meet business requirements that are changing faster than ever, and remain competitive, firms are seeking to tap into emerging technologies in an intuitive way that is focused specifically on their core areas of business. They also want to be able to make the most of their existing digital transformation initiatives, and of their existing data sources – regardless of the data and organisational silos that exist.
There is therefore a clamour for customisable enterprise applications with AI and data capabilities that can be developed with ease. Organisations can be in control of developing these applications and becoming Composable Businesses. They can then subsequently reuse components of their existing applications to quickly create new applications and adapt swiftly to market changes.
Why Innovate with ELEMENT™?
Business users can leverage ELEMENT™’s low/no-code interface to drag and drop application components and create complete, AI-powered enterprise applications for a wide range of business domains.
ELEMENT has composability at its core, enabling enterprises to seamlessly become Composable Businesses. This shifts departments’ emphasis from building applications from scratch to reusing components – what we call Atoms, Molecules and Substances – to create a wide range of business applications.
The power of ELEMENT does not just lie in the development stage; the core technology within the platform enables enterprises to continue to progress on their digital transformation journeys.
A Data Fabric approach is at the heart of ELEMENT, decentralising data discovery from internal and external sources, allowing structured and unstructured data to be readily accessible from where it resides. This ensures enterprises can retain their existing data lakes, warehouses and other infrastructure but bypass data silos. It also ensures that the information is always up-to-date – and ensures better data quality and governance.
The data can then be processed by our award-winning knowledge graphs, machine learning algorithms, and Gartner-recognised Composite AI technologies. ELEMENT comes with configurable workflows, dashboards, and rule engines; and powerful analytic capabilities that generate expert-level insights for specific business domains.
Below are further reasons why you should innovate with ELEMENT:
Leverage a wide array of best-in-class AI technologies including machine learning, natural language processing, entity extraction, contextual analytics, data visualisation, predictive modelling, hypothesis testing and more.
Empower non-technical staff to build and customise AI applications self-sufficiently; and modify existing systems to adapt to changing business and technological requirements via an interactive drag-and-drop interface.
Seamless System Integration
Augment existing technology assets with minimal impact on business continuity through a robust software development kit (SDK) that exposes ELEMENT’s system capabilities using industry-standard software integration methods.
Innovation at Scale
Build self-learning enterprise AI applications in weeks, with the ability to scale over time by configuring data sources, functions, and algorithms; using a Bring Your Own Schema (BYOS) approach that supports all data formats.
Low Total Cost of Ownership
Reduce your Total Cost of Ownership (TCO) through cloud infrastructure and PaaS by shifting from an upfront CapEx model to an ongoing OpEx model, and accelerating application design, development, and deployment.
ELEMENT in Action
Step 1: Inception
Envision a new enterprise application idea and build a demonstrable prototype.
Step 2: Elaboration
Define all relevant internal and external data sources and utilise ELEMENT’s schemaless design to configure data fusion using any predefined data model.
Step 3: Construction
Customise data science and AI algorithm templates, then embed them into your business processes and apply the relevant business policies.
Step 4: Transition
Use an extensive set of visualisation tools to design user experience and define where to feed data into your existing systems, then publish your application.
Step 5: Composability
Reuse components of your application, and add new components using our product catalogue to create another application.