ABOUT / MKLAB
Experiments with
context in view.
MKLab is a collection of 37 public browser demos maintained by Mohammad Rezwan Khan.
Explore energy, learning, civic information, research and everyday planning through synthetic examples. Each app has a factual overview, instructions, limitations and a runnable browser edition.
How the apps are presented
Every overview describes the features in its published browser edition. Where a server or Python engine is required for additional functionality, the page explains that boundary. Public source links are included for HelioForge Energy Lab and ZephyrTrade.
Development and writing use AI assistance. The release is checked for browser rendering, public asset access, metadata consistency and source-file exclusions. These maintainer checks do not establish professional validation, rights over third-party content or independent external review.
Data and local saves
The demos use fictional or synthetic records. There is no shared account, payment, dispatch or external AI service. Use fictional information in forms. Apps with local storage save on the current browser and device.
Browser storage belongs to an origin. Saves made on khanlab.co.technology do not automatically transfer to mklab.co.technology. Public access does not grant a new license to private source or third-party material; available notices accompany each app.
SCOPE
A demo is a place to explore.
These pages are not live directories, emergency services, medical tools, financial services or official educational products. Review each app’s visible limits before interpreting its outputs.
Datacenter Twin Lab, its course and evidence remain at khanlab.co.technology. MKLab hosts the separate browser app collection.
Inspect and reference an app
Use an app’s canonical overview when sharing or citing it. The overview provides the source revision, runtime checksum, available notices, a public facts JSON file and a plain-text summary. The collection index and sitemap provide discovery links.
Content updated . Search and AI systems decide whether to index, rank or cite a page; these public references do not guarantee placement.