When video tagging operations are small, manual workflows can work.
But once you scale to hundreds of videos and taggers, manual processes start breaking down:
1. Videos need to be assigned every day.
2. Progress needs to be tracked continuously.
3. Completed data needs to be collected and used immediately.
4. Reports need to be generated without delay.
At this stage, operations become the bottleneck - not the tagging itself.
A client was using SPAN with a team of over 100 data taggers. Their videos were stored in their own cloud infrastructure, and tagging work was assigned on a daily basis. They needed clear visibility into who was working on what, continuous tracking of progress, immediate access to completed tagging data, and automated pipelines to generate reports for their end customers.
When this workflow was handled manually, it required significant operational effort. Someone had to upload videos into SPAN, assign files to each tagger, track completion status, and then download the tagged data to push it into reports. As the scale increased, this approach started to break down. It introduced delays, increased the chances of human error, led to missed files, and resulted in inconsistent tracking. Over time, the operational overhead became a bigger problem than the tagging itself.
How APIs solved this in SPAN
SPAN APIs allowed this client to automate the entire workflow end-to-end.
1. Videos were pushed from the client's system directly into SPAN using APIs, removing the need for any manual uploads and eliminating dependency on operations teams.
2. Each tagger was assigned work through unique access links generated from the client's system. Taggers moved seamlessly from the client’s platform to the SPAN interface, without requiring any manual coordination.
3. The client used APIs to continuously track progress. They were able to monitor which videos were in progress, which tagger was working on each file, and how much of the work had been completed. This created real-time visibility without the need for manual follow-ups.
4. SPAN also triggered webhook notifications as soon as tagging was completed. This removed the need to repeatedly check the status of files.
5. Once tagging was done, the client's system automatically fetched the tagged data using APIs. This data was directly used in reports, dashboards, and customer deliverables, completing the workflow without any manual intervention.
What API Automation Achieved
By integrating SPAN APIs into their workflow, the client achieved a fully automated system with minimal operational overhead. There was no longer any need for manual assignment of videos, and the process did not depend on human intervention at any stage. Files were not missed or delayed, and the entire operation became predictable and reliable. The client had real-time visibility into ongoing work, and the turnaround time for delivering data to end customers improved significantly. Most importantly, this removed operational friction. The team was able to focus on data quality and insights, instead of spending time managing processes.
Final Thought
If your workflow involves multiple taggers, daily assignments, and continuous use of data, automation is not optional. APIs transform SPAN from a standalone tool into a fully integrated part of your production pipeline.