Every action in your business leaves a trace — in your ERP, your ticketing system, your infrastructure metrics. Scrape uses LLMs and ML to correlate those traces, turning isolated records into a connected picture of what actually happened and why — surfacing cause-and-effect relationships across systems that were never designed to talk to each other.
Scrape ingests data from your ERP, ticketing systems, infrastructure metrics, and other operational sources.
Scrape's models identify relationships between disparate events that no single system could surface on its own.
Your team gets a connected picture of what happened, what triggered it, and what to do next.
Which upstream ERP event or ticket triggered this infrastructure alert?
What business processes were affected by this system event?
How do changes in one system ripple across teams and tools?
What sequences of events consistently precede the outcomes you care about?
Scrape is not a SaaS product. Every deployment is custom-built for your ecosystem by Oberth Systems engineers.
Engagements begin with a discovery phase to map your data sources and define the cause-and-effect relationships that matter to your business.