Low Code, No Code

Low code, no code tools and platforms effectively accelerate the digital transformation of organizations. These platforms employ visual tools to define data, logic, flows, forms, and other application artifacts without writing codes. This enables users with little to no technical knowledge build customer and enterprise applications. Organizations achieve business agility and cost optimization through citizen development.

Evolution across the three horizons (H1 to H3)

Show all horizons


Experience Design

Digital Experience & Application Platforms

Digital process automation and Operations

Enterprise productivity

Data Science & AI

  • Hyperpersonalization designs
  • Omni channel and AI augmented design
  • Out of box intelligence and prediction
  • AI assisted development
  • Headless application development
  • FLUID DPA with capabilities to sense, analyze, respond, and intelligently evolve
  • Intelligent decisioning augmenting
  • Citizen development - with remote collaboration and cognitive apps
  • Interaction-based workflow generation
  • Drag and drop graph API
  • Machines doing machine learning (ML)
  • Machine generated code based on human instructions
  • Pair programming


  • Collaborative cloud-based design
  • Data-based designs
  • RAD with flexibiity, extensibility, and standardization
  • Enriched cloud services integrations
  • Process automation augmented by RPA and AI
  • Advanced process intelligence
  • Team productivity
  • Integrated, collaborative, and always on
  • Marketplace of prebuilt templates, workflows for repetitive tasks
  • Citizen development - with remote collaboration and cognitive apps
  • Interaction-based workflow generation
  • Drag and drop graph API


Traditional, Individual User Design

  • Rapid application development
  • Static HTML/CSS-based WYSIWYG editors
  • Traditional Business Process Management
  • Rule engine-based solutions
  • Personal productivity in silos
  • Unification of unstructured data
  • Apps to improve operational efficiency
  • Traditional do-it-yourself (DIY) and take forward the learning
  • Supervised, semi supervised, and unsupervised learning

LCNC key trends across technology domains

Experience Design

Trend 1

From single user to collaborative models and design platforms

As the experience shifts from the web to mobile, voice, and other forms, there is a need to integrate different strands of expertise from design, tech, and business. Today's applications demand closer collaboration between stakeholders across businesses, technologies, designs, and end users.

Trend 2

AI and ML drive hyperpersonalization

LCNC platforms help create integrated, omnichannel experiences across voice, mobile, and web. These platforms automatically create UI with end-to-end API and data integrations. We can now generate screens based on images leveraging AI.

Digital Experience and Application Platform

Trend 3

Intelligent and integrated experiences enhance applications

Solving problems today involves a close collaboration of engagement, intelligence, and records systems. Multiexperience horizontal platforms like Outsystems, Mendix, and Microsoft PowerApps create seamless integrations between AI and intelligence in their LC application development strategies.

Trend 4

AI co-development boosts productivity

AI-based co-development is a significant trend in multiexperience horizontal platforms. Examples of critical accelerations are in areas where the experience metadata and properties are auto-filled, development suggestions and recommendations are combined with integrated development environments, and alerts are created during development stages.

Digital Process Automation

Trend 5

Cloud provides a force multiplier for LC development

Cloud hyperscalers and market leaders invest heavily in pushing the boundaries of innovation in cognitive AI services such as vision, speech, language, and document interpretation. LCNC DPA platforms are in an ideal position to take advantage of the cloud as the enabler for the ease and speed of developing such functionalities.

Trend 6

Process mining and optimization

In a complex modern landscape, any end-to-end process typically spans across multiple systems, steps, and people. This is especially true in the backdrop of multiple ERPs and diverse teams. Before optimizing the end-to-end experience or delivering business efficiency outcomes, one must first understand the issues that impact the experience.

Enterprise Productivity

Trend 7

More focus on Enterprise productivity and collaboration

With hyperpersonalized experience, drag-and-drop UI build capability and ease of integration, LC platforms boost productivity by accessing data anytime, anywhere. LCNC platforms also offer LC bot build capabilities that employees can use for self-service applications.

Trend 8

Remote collaboration gains prominence

Enterprises rethink their ways of doing business post pandemic. While essential staff still work on site, almost 88% of the global workforce work remotely. Prior to the pandemic, only 20% worked remotely.

Data Science and AI

Trend 9

AI and ML find significant usage in cloud services

Analyzing massive amounts of unstructured data like images, transcripts, and recorded speeches is a top requirement for enterprises. It necessitates significant upfront investments in the compute and storage infrastructure to collect, cleanse, and tag the data for training and model building.

Trend 10

Enterprise-level AI shifts from fragmented to integrated and managed activities

Platforms and services that perform all the functions of a typical AI/ML implementation lifecycle help businesses move toward a more standard, managed, integrated and collaborative environment. Platforms like H2O Driverless AI, Azure ML, and Amazon SageMaker bring citizen data scientists and CSPs together.

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Ashok Kumar CS

Ashok Kumar CS

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Deepak PN


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Syed Ahmed

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