Proofpoint asks one question of every action: did this move carry content we recognize as sensitive, and was it allowed? That question catches a lot. It does not catch the move that was allowed on purpose, where only the pattern is wrong. These are not the same kind of tool, and putting Hilt next to Proofpoint is not a swap. Proofpoint watches the channels people use to send things out. Hilt watches the movement itself, at the kernel, and resolves it to the identity and the job behind it.
What Proofpoint is built for
Proofpoint grew up on email, and the lineage shows. Its Insider Risk Management and Information Protection products work at the application and content layer. They watch what users do in the channels that carry data out: email, web uploads, removable media, cloud sync to consumer accounts, file activity on managed endpoints.
That is real coverage. Someone attaches a customer list to a personal Gmail thread. Someone copies a contract folder to a USB drive on their second-to-last day. Someone uploads source files to a personal Dropbox. Proofpoint sees the channel, classifies the content, ties it to a user, and hands the security team an event with context. For content-defined exfiltration over channels it monitors, it does the job. Add a console tuned for investigators and a content library refined over years, and a team that has built its insider-risk workflow around Proofpoint has something worth keeping. If the threat is sensitive content leaving through a watched channel, Proofpoint is the right tool.
Where the question runs out
The limit is structural, not a knock on the product. An application-layer tool evaluates permission one action at a time. It has no place to hold the shape of behavior across a month.
Your most valuable data leaves on access you granted on purpose. The credential is valid. The channel is approved. The role is correct. Each action sits inside policy, so every tool you own correctly lets it through. The danger is the pattern across moves.
A researcher pulls a proprietary repository over two weeks. Small chunks, off-hours, through an approved transfer connection that exists for legitimate data movement. No content rule fires, because the volume per action looks ordinary. No policy breaks, because she is allowed to use that connection. The console stays quiet. The stack was expensive and nothing triggered. The tool was never designed to ask whether this identity, at this hour, through this job, is moving data the way it normally moves it. It cannot ask, so it does not.
What Hilt sees that the channel does not
Hilt stands somewhere else and asks something else. It watches data movement at the kernel, metadata only by default, off the path. It runs single-tenant inside your own cloud. It never sits inline, never blocks, drops, or alters traffic.
From there, Hilt resolves each move to a probabilistic, source-dependent identity: which user, which job, which destination, and whether this fits what that identity normally does. The unit is the movement, scored against months of how data actually moves in your environment, not a lone action checked against a rule.
When the researcher pulls the repository, the deviation lands across layers at once. The job is unusual for her identity. The access is a sustained read of high-value paths in short off-hours windows. The volume drifts from her baseline even though the channel is approved. Any one signal alone is noise. Together they are a pattern. A pattern is a case, not an alert. Hilt writes the case with the narrative behind it and, when the situation warrants, responds with host-level network isolation (quarantine) from the control plane.
That is the third option. Predictive tools guess ahead of time, bury the team in false alarms, and still miss the permitted move. Forensics tell you after the data is gone. Hilt reads the pattern at runtime, while the data moves, in time to act.
Two things matter to a team weighing the layer. Hilt does not have to read your data to see that a pattern is wrong; metadata is the default vantage, and content-aware inspection is there when you want it, not the cost of entry. And the collector stays off the path, on the order of 0.1% of one core and 4 to 8 MB of memory per host, so infrastructure that cannot carry a heavy inline agent still sees the pattern.
Where Hilt does not replace Proofpoint
Hilt is additive. There are jobs Proofpoint does that Hilt does not.
Email security and content classification are Proofpoint's core. If your priority is inbound threats, phishing, and message-level data loss prevention on email, that is its home ground and Hilt does not cover it. Hilt watches data movement at the kernel. It is not a secure email gateway and does not classify message content the way a content engine does.
Proofpoint's console and its years of content tuning are an asset on their own. A team with investigation workflows built around them keeps that value. Hilt produces a written case from the movement; it does not reproduce Proofpoint's content library or its email-native tooling.
So: Proofpoint covers content leaving through the channels it knows. Hilt covers the pattern of movement across permitted actions, at the kernel, where no application-layer tool was built to look. Teams that run both keep Proofpoint where it is strong and add Hilt underneath it.
How to decide
Gap is content leaving over email and known egress channels? Proofpoint is built for that. Hilt is not the tool to swap in.
Gap is the slow, permitted, low-volume movement that no single action flags, run through approved channels by legitimate identities? That sits in the blind spot application-layer tooling was never built to cover. That is what Hilt adds.
Test your own stack with one question: can it answer what this identity's data actually did, resolved to the job behind it and scored against how it normally moves, between 11pm and 2am on these three dates? If the answer comes from permission checks taken one action at a time, the pattern is invisible to it.
If that is the question you cannot answer today, the quickest way to see the difference is engineer to engineer. Thirty minutes walks the vantage, the metadata-only default, and how a case gets written, against your own environment.