Amit Verma
AI Product InterfacesWebGLGISXREnterpriseVueUnity XRAbu Dhabi

AI / GIS Enterprise Interface

At SenseTime in Abu Dhabi, Amit Verma leads graphics-heavy frontend engineering for AI-assisted enterprise applications built for ADGM, bringing together Vue, WebGL, Unity XR, and GIS so teams can explore complex operational and spatial data without losing sight of clarity, reliability, and production constraints.

Role
Senior Frontend Engineer / Graphics & AI Interface Lead at SenseTime (Abu Dhabi), building the interface layer for ADGM.
Period
Feb 2023 – Present
Stack
Vue · WebGL · Three.js · Unity XR · WebXR · GIS · Machine Learning Integration · TypeScript · Enterprise Frontend Architecture

Problem

ADGM needed advanced machine learning to be usable inside enterprise interfaces that blend AI, GIS mapping, and Unity XR.

Approach

Architect a Vue and WebGL frontend that unifies AI, spatial GIS data, and XR into clear, dependable production interfaces.

Outcome

Enterprise-grade tools where complex operational and spatial data is explored through interfaces that stay usable under real constraints.

Context

SenseTime's Abu Dhabi work serves ADGM, where the demands of a rigorous enterprise environment meet advanced machine learning. The brief sits at an unusual intersection: surface AI capabilities, operational data, and spatial information inside web applications that internal teams and clients can actually use day to day. The hard part is rarely a single technology. It is making machine learning, realtime 3D, GIS, and XR feel like one coherent product rather than a collection of demos, and keeping it dependable under genuine production constraints.

Challenge

AI outputs are probabilistic and often abstract; enterprise users need interfaces that are legible, predictable, and trustworthy. Layered onto that, the data is both operational and spatial, which pulls in GIS for mapping and location context and Unity XR for immersive views, alongside the WebGL graphics work the web layer needs. Each of these stacks has its own runtime model and performance profile. Bringing them together without the interface becoming heavy, confusing, or fragile is the core engineering tension to resolve.

Approach

The work is led from a graphics-heavy frontend architecture built on Vue, so the application has a stable, component-driven backbone that the heavier graphics and AI features can plug into cleanly. WebGL handles the realtime visual layer in the browser, GIS-based interfaces carry the spatial and mapping dimension of the data, and Unity XR experiences are integrated where an immersive view earns its place rather than being added for novelty. Machine learning is treated as a first-class but bounded input: the job is to bridge advanced ML capabilities into product design systems that stay usable, framing model outputs in ways enterprise teams can read at a glance and act on. The consistent priority across every surface is product clarity, presenting complex operational and spatial data so the people relying on it can explore it with confidence.

Engineering decisions

Keeping Vue as the architectural foundation means the AI, WebGL, GIS, and XR pieces each live behind clear boundaries instead of bleeding into one another, which is what keeps a multi-discipline interface maintainable over time. WebGL and Unity XR are used deliberately for the parts of the experience that genuinely benefit from realtime 3D and immersion, while standard enterprise UI patterns carry everything else, so performance and comprehension stay protected. This restraint is informed directly by earlier work on browser graphics at scale and on realtime systems in games, where interaction quality and runtime performance are non-negotiable. Here that instinct is pointed at enterprise reliability: integrate the powerful capability, but only where it makes the product clearer and faster to use.

What it demonstrates

This is senior graphics-heavy frontend and WebGL engineering applied to the AI and enterprise market, in the UAE and Abu Dhabi context specifically. It shows the ability to lead AI-assisted product interfaces end to end on the interface side, to combine Vue, WebGL, Unity XR, and GIS into a single coherent product, and to translate machine learning into design systems that hold up under real production constraints. It is the through-line of a decade-plus of realtime, graphics, and product work, now focused on AI-assisted enterprise interfaces.

Outcomes

  • Leads graphics-heavy AI-assisted enterprise interfaces for ADGM, owning the frontend architecture on Vue.
  • Integrates Unity XR experiences and GIS-based interfaces into complex internal and client-facing platforms.
  • Bridged advanced machine learning into product design systems that remain usable under real production constraints.
  • Unified Vue, WebGL, Unity XR, and GIS into a single coherent interface for exploring operational and spatial data.