Entity-based semantic search that actually knows your organization. Fewer false positives, faster takedowns, and a threat graph that maps entire campaigns instead of chasing single alerts. We keep what's real and know what's not.
High level, that capability is a lot more advanced. You have the edge on the deep dive and the dark web depth. I'll go for the better capability.
On the API-driven automation we need, the other vendor is just not doing this at all. Your platform was the only one that delivered it in the pilot.
The market is three tiers. Keyword monitoring, then AI detection, then fully agentic. You're the agentic one. That's where we want to be.
Legacy tools track keywords. Outtake maps every entity linked to your brand, separating what's authorized versus what isn't.
Legacy DRP tools watch a fixed set of channels, and automation drops off outside it. Outtake indexes 45+ surfaces, including the ones your current tools never reach.
Legacy DRP tools start every case cold, with no accumulated context to build on. Outtake remembers every entity, adversary, and takedown it has ever seen.
Legacy DRP tools stop at the artifact in front of them. Outtake traces it back to the operator and dismantles the network behind it.
Legacy DRP tools route every alert to a person in a queue. Outtake routes itself, and gets sharper with every outcome.
Accuracy in true positive detection. Your team only sees threats that matter.
faster takedowns than legacy DRP, with threat reviews accelerated 3x.
of cases handled by the platform on its own. A person steps in at the moment of action.
A living trust registry across your brands, executives, locations, and products, built on real entities instead of keyword lists.
Benefit: A fake is easy to spot in seconds, even one that never uses your exact name. It also keeps Agentic Search precise, the registry tells the platform what counts as signal, so breadth in search does not turn into noise.
Doppel does not maintain a registry of what you actually own. It watches for known attack patterns, with no system of record to check a fake against.
ZeroFox's coverage runs on known attack patterns and broad surface monitoring. Content that does not match a known pattern, including AI-generated impersonation, can pass through undetected.
Continuously monitors your full digital footprint and closes blind spots on its own. Protects 45+ surfaces at once, including the public and monitored messaging channels most tools never reach, and covers new assets the moment they appear.
Coverage is scoped to social engineering and the channels you flag, and detection leans on outside feeds, the same data other vendors buy. The rest of your footprint is on you to track.
Automation runs on domain takedowns. Everywhere else, detection is keyword and rule based, and multimedia or AI-generated content slips through. Coverage spans social and dark web, but automation depth drops off outside their core surface.
Accumulates context on every entity, suspicious variant, fraudulent asset, adversary, and takedown it has seen. New threats are triaged against that accumulated context instead of starting cold, for faster decisions, and it feeds straight into your SIEM, ServiceNow, or Jira.
Intelligence depends on outside feeds and manual tuning, so each case starts cold and the baseline does not build on itself.
Detection leans on rule sets and manual triage, so each new threat starts cold instead of building on what has already been seen.
Recon Agent turns one alert into the full campaign behind it in minutes. Actor Tracing connects the accounts, domains, and infrastructure to the operator running it, and Threat Graphing maps the adversarial network so the whole operation gets dismantled at the root.
Doppel's model is built around finding and removing the artifact in front of you. In our experience, tracing it back to the operator or the network behind it is a separate problem it is not built to solve.
ZeroFox's model is built around flagging and removing what is in front of it. In our experience, tracing the account, domain, or actor behind an incident back to the wider network is a separate problem it is not built to solve.
Intelligently routes each threat down the right response path on its own, then learns from every outcome to get sharper. Your team steps in at the moment of action, and nothing sits waiting in a shared queue.
A person decides the path on each alert, so throughput is capped by the team and the work does not scale with the attack.
Response runs through an analyst queue, so throughput is capped by headcount and takedowns do not speed up as the attack does.
Tell us what you're up against. We'll show you what Outtake can do, and you decide from there.