I built Scryer to address the problem of data overload in analytics. Small store owners have detailed dashboards filled with charts and tables, but they usually end up tracking one or two metrics they understand and ignore the rest.
So why not use an AI pipeline to collate data from different sources (Shopify API, web pixel, Lighthouse audits, page crawls, etc.) and extract meaningful insights?
I know there's AI fatigue... I wanted to build something different: proactive daily analysis that tracks issues over time instead of one-shot responses. When it finds a problem (like "your mobile speed dropped"), it keeps tracking it until you fix it, then marks it resolved. Not just regenerating the same alert every day.
Hopefully this can be useful enough to justify the price! It would cost way too much and take way too long to do this analysis continuously - that's why it runs daily instead of real-time.
So why not use an AI pipeline to collate data from different sources (Shopify API, web pixel, Lighthouse audits, page crawls, etc.) and extract meaningful insights?
I know there's AI fatigue... I wanted to build something different: proactive daily analysis that tracks issues over time instead of one-shot responses. When it finds a problem (like "your mobile speed dropped"), it keeps tracking it until you fix it, then marks it resolved. Not just regenerating the same alert every day.
Hopefully this can be useful enough to justify the price! It would cost way too much and take way too long to do this analysis continuously - that's why it runs daily instead of real-time.
Check out more of the technical approach here: https://scryerapp.io/blog/building-ai-analyst
Thanks!