Mindkosh labels sensor data; $1.5K a month, self-reported in 2022: AI-assisted tools

Mindkosh is a data labeling platform for RGB, thermal, depth, and lidar sensor data. Its $1.5K a month was founder-reported on the Indie Hackers product page (not independently verified), as of February 2022.

What it actually sells

Mindkosh is the data labeling platform for all your sensors including Lidar, Thermal, Depth and RGB cameras. It serves machine learning teams developing autonomous driving and other autonomous systems.

The platform includes multi-camera annotation for RGB, thermal, and depth images, sensor fusion annotation for point clouds and camera images, and object tracking across multiple frames. Its AI-assisted tools include segmentation, mask propagation, pre-annotation, OCR, and cuboid annotation.

How it charges

The pages we read show no price. The site offers free sign-up, and it also provides a product-demo scheduling option.

Where customers come from

The site shows a Discord community, a Mindkosh Python SDK for uploading data directly to its servers, free sign-up, and a demo-scheduling option. The site also identifies machine learning teams developing autonomous driving and other autonomous systems.

What stands out

Mindkosh supports segmentation and polyline annotations across thousands of aerial images. Its object tracking works across multiple frames in point clouds and images, backed by powerful interpolation and dimension locking.

The PII Removal API detects and removes personally identifiable information from images and videos with industry-leading accuracy.

From the official site

Powering the Machine Learning teams at

Easily track objects across multiple frames in both 3D point clouds and images, backed by powerful interpolation and dimension locking.

Excerpts from the official website, fetched October 1, 2026.

Where it sits in the data

Mindkosh's $1.5K a month is higher than 46% of the 6,604 projects with founder-reported monthly revenue in our dataset; the median across them is $2K. Snapshot: 2026-09-30. The dataset only covers founders who chose to publish their numbers, so it leans toward businesses that work; use it for scale, not as an average.

Currency

All figures are in US dollars as published. A rough yuan or euro conversion is not applied here because prices, taxes and acquisition costs differ by country.

Could you build something like this?

In my view, this would need a clearly defined buyer among machine learning teams working with sensor data for autonomous systems. Demand would depend on the need to label RGB, thermal, depth, and lidar data across individual images, multiple cameras, point clouds, and video frames.

Distribution would need to reach those teams through developer communities, direct sales, demos, and useful technical content. The hard parts would include reliable annotation workflows, handling varied data formats, maintaining labeling quality, managing support requests, protecting uploaded data, and competing with established annotation tools.

Verdict: Hard to replicate.

One thing to take from it

My view is that Mindkosh’s clearest lesson is the breadth of the labeling workflow: multi-camera images, sensor fusion, object tracking, AI-assisted annotation, and PII removal are presented as parts of one platform. A founder could study how tightly these workflow pieces are connected for machine learning teams.

Sources

Mindkosh official website, fetched October 1, 2026
Indie Hackers product page: revenue founder-reported on the Indie Hackers product page (not independently verified), as of February 2022

Revenue, team and start-cost figures are what the founder reported at the interview date, not current figures and not a prediction of what you will earn. Product and pricing facts come from the business's own website as checked on 30 September 2026. Method & sources · Disclosure