Constructed DataSwitch Website
An end-to-end design and development case study for DataSwitch.co.
- Role
- UX Design Engineer
- Scope
- Visual design, UX architecture, component system & deployment
- Stack
- Antigravity, GitHub, Vercel
The Challenge
A platform too complex to explain, sold to buyers who trust nothing.
High-tech complexity
A dense engineering capability set that resists any single, simple explanation.
Multi-agent platform
Several autonomous agents and engine capabilities, each needing a distinct and obvious job.
Buyer trust
Enterprise decision-makers arrive sceptical and need governance and compliance shown, not claimed.
The Solution
Precision as a visual language, built at agentic speed.
Dark-mode precision
A deep dark canvas with restrained accents, reading as high-precision rather than decorative.
Agentic design workflow
Design intent taken straight to production components, removing the traditional handoff entirely.
Clear metrics
Structured proof points carrying the hierarchy, so the value lands before the copy is read.
Agentic Workflow
Four steps, no handoff.
- 01
Ideation & Conceptual UX Structure
Information architecture, page hierarchy and the narrative order a buyer moves through.
- 02
Antigravity AI Code Synthesis
Layout intent converted directly into production-ready modular React components and design tokens.
- 03
GitHub Code Governance & Versioning
Atomic component structure under automated branch workflows, with linting and quality checks on every pull request.
- 04
Vercel Automated Edge Deployment
Preview builds on every commit and zero-downtime production releases on the edge network.
Product Ecosystem & Logo Design
Five products, one family.
DS Migrate
Automated migration of legacy data estates.
DS Srishti
The core engine orchestrating every agent.
DS DataMaps
Visual source-to-target lineage and mapping.
DS DataCitizen
Self-service data access for non-technical teams.
DS InsightCitizen
Guided analytics over governed enterprise data.
Each product carries a custom mark rendered in a shared green palette and lighting treatment, so the family reads as one system while every agent stays individually identifiable.
Technical SEO Architecture
Semantic data & crawl optimization.
Engineered a high-performance SEO pipeline designed to maximize discoverability, establish machine-readable entity authority, and optimize search engine indexation efficiency across modern search engines.
Semantic Entity Graph (
JSON-LD)Implemented Schema.org structured data to explicitly define site entities —
Person,WebSite,CreativeWorkandTechArticle. IntegratedsameAsauthority mapping andknowsAbouttaxonomy arrays, making the application fully eligible for search rich snippets and Knowledge Graph recognition.Crawl Budget & Indexation Governance (
robots.txt)Configured bot-level crawler routing to preserve crawl bandwidth. Explicitly isolated internal API endpoints and staging routes —
/api/,/admin/,/drafts/— while allowing rendering bots full access to essential visual assets and static binaries.Rendering & Asset Accessibility
Ensured web crawlers can accurately render interactive layouts and WebGL assets by whitelisting asset pipelines without compromising private application infrastructure.
Automated Sitemap Discovery
Integrated dynamic sitemap declaration directly within crawler headers, accelerating new content discovery and reducing time-to-index.
See the finished product in the wild.
Visit the site
