Competitive research that couldn't scale by hand.
Seekho operates across hundreds of content categories, and every category is crowded with competitors. Keeping track of what's working — which ads, which hooks, which formats — meant watching competitor creative by hand. It was slow, and at that breadth, insights kept slipping through.
Building the infrastructure in-house wasn't simple either. Analyzing thousands of videos a day takes serious CPU and heavy parallel processing — the kind of scale that's expensive to stand up and even harder to keep running reliably.
A competitor-ad intelligence pipeline.
We built Seekho an automated pipeline that watches the competition for them — scraping, tagging, ranking, and handing the whole picture to their team through the tools they already use.
Insight ready before the day starts.
Thousands of competitor videos across every category are analyzed overnight — before the team even wakes up. Instead of hunting for creative, the team browses a ranked, tagged library, asks Claude to surface the best-performing ads, and sends them straight to their agency.
The time saved runs to thousands of hours across categories. And because everything runs as batch processing, token and scraping costs come in about 50% lower than an equivalent in-house build — without the CPU and parallelization headaches.