Rastock AI is a metadata and distribution tool for stock photography and video contributors. It combines AI metadata generation, per-agency policy enforcement, bulk FTP delivery to 10 or more agencies, and per-destination status tracking in one workflow.
The commercial model is deliberately plain: a flat subscription, no revenue share, no ownership claim over uploaded work, and free export of metadata as IPTC, XMP or CSV.
Rastock AI was founded by stock contributors for stock contributors. We know the pain of spending hours in spreadsheets instead of behind the camera.
Built for the Reality of Modern Stock Creation
By 2025, the stock content industry had reached a critical scale challenge. Marketplaces were receiving unprecedented volumes of images and videos, yet the tools used to describe, structure, and prepare that content remained largely manual, fragmented, and outdated.
Metadata workflows had not evolved at the same pace as content creation, and every
wanted the same information in a different shape.
Rastock AI was founded to solve this exact problem.
We saw a growing disconnect between how stock content is produced today and how it is prepared for distribution. Creators were spending more time managing
than creating content, while agencies struggled to scale operations efficiently.
Instead of building another generic tagging tool, we focused on understanding commercial stock context — how images and videos are actually evaluated, categorized, and surfaced across major marketplaces.
Rastock AI is built around a purpose-designed AI engine developed to support high-volume stock workflows. Our system analyzes visual content with a focus on:
This allows creators and teams to generate structured, usable metadata that aligns with
— not just surface-level object detection.
Where Rastock AI Is Today
Rastock AI now works in two places. The dashboard processes files and delivers them to agencies over FTP in the shape each one asks for. A browser extension, published on the Chrome Web Store, writes metadata straight into the contributor upload pages of Adobe Stock, Shutterstock, Freepik and Depositphotos — no export, no copy and paste.
Rastock AI is supported by Microsoft for Startups, with the backing of Azerbaijan’s Innovation and Digital Development Agency.
Today, Rastock AI supports photographers, videographers, creative teams, and agencies who work at scale and need reliable automation to keep up with growing demand. Our platform is designed to help users:
Rastock AI is built for creators who treat stock production as a serious business — not a side task.
We believe metadata should never slow creativity down. Our mission is to remove operational friction from stock workflows and help creators focus on what they do best: producing valuable, market-ready content.
Rastock AI continues to evolve alongside the industry, guided by real-world contributor needs and practical automation — not hype.
The values that guide our AI
Technology without ethics is just code. We build with a clear moral compass.
The Minds Behind the Engine
A small team of engineers, designers and stock contributors.
Ready to scale your business?
Join thousands of contributors who have already reclaimed their time with Rastock AI.
We build tools that empower human creativity, not replace it. Our AI handles the chores so you can focus on the art.
Your data is yours. We never use your private portfolio to train models without explicit permission — the full policy is on our privacy page.
t enough. Metadata is written against each agency
Balash founded Rastock AI after years of running a stock portfolio himself, where the bottleneck was never shooting or editing — it was writing metadata and getting files to each agency in the format that agency expects. He leads product and company direction, and works directly on the parts of the system contributors touch every day.
Elchin leads engineering and infrastructure. His focus is the part of the platform contributors never see and always depend on: the pipeline that processes files, the delivery layer that reaches each agency over FTP, and the deployment path that lets fixes ship the same day they are written.
Yamen designs the interface contributors work in. Her focus is the workflow around volume — reviewing hundreds of files without losing track, understanding what each agency will accept before submitting, and keeping the product legible when the library grows.
Alyssa looks after how Rastock AI presents itself — the positioning, the campaigns and the language used across the site, the blog and social channels. Her work is keeping one consistent voice in front of contributors, from the first ad they see to the product they end up working in every day.
Victor leads the models behind the metadata. His work is evaluation more than generation: measuring output against each agency’s published rules, tracking where descriptions drift from what is actually in the frame, and improving accuracy on the file types contributors upload most.