To watch your data move, most tools first ship the record of that movement to someone else. Your EDR streams process execution to a US cloud. Your DLP forwards file hashes through a vendor instance in Frankfurt. Your SIEM lands everything in a shared tenant in us-east-1. The telemetry that describes your firm now lives on infrastructure your firm does not run.
A web shop can live with that. A bank under data residency rules, client confidentiality clauses, and cross-border transfer restrictions cannot, because each hop out is the regulated act, not the breach that might follow it. A regulator does not ask whether the vendor was eventually compromised. The transfer already happened.
There is a sharper problem under the residency one. Your most valuable data leaves on access you granted on purpose. Every move is permitted, so every tool you own lets it through, correctly. The breach is the pattern across moves, and the only place to read the pattern is at runtime, while the data is moving. Most security architecture assumes you will send that record outside your perimeter to be read. For a regulated firm, the record itself is the thing you are not allowed to send.
The telemetry is the regulated data
The standard build is an agent on the host or a tap in the path, telemetry streamed to vendor compute, analysis there, alerts back. That trade buys you a vendor who tunes the model and correlates signals across their whole customer base. It costs you control of where the record sits.
The record is not anonymous. Process arguments carry account numbers. File paths spell out trading-strategy naming conventions. Network destinations name the counterparties you are negotiating with. A proprietary trading system that spawns Python with ticker symbols as command-line flags writes alpha into its own execution trace. A credit model that loads specific files before quarterly earnings writes a calendar into its file paths. Connection attempts read at the kernel, before the application encrypts anything, expose which market-data feeds you pay for and which internal systems talk to which.
Encryption in transit does not fix this, and a vendor SOC 2 report does not fix this. GDPR, FINRA, and SEC cyber rules do not care how well the transfer was secured. They care that it occurred. "It is only metadata" is not a defense when the metadata reconstructs your trading desk.
Hilt reads the pattern where the data already is
Eliminate the transfer and the transfer problem disappears. That is the model Hilt runs.
One lightweight collector watches data movement at the kernel, metadata only by default, off the path. Process activity, file operations, network connections, observed before application-layer encryption or logging hides them. The analysis runs on the same compute, single-tenant, in your own cloud: AWS, GCP, Azure, or Ali Cloud, under your own keys. Hilt resolves each move to a probabilistic, source-dependent identity and the job behind it, then surfaces the dangerous pattern across moves instead of scoring events one at a time. Baselines build from your own infrastructure: which roles touch which systems, which workloads normally talk to which destinations. The events never leave your account.
So the operational metadata that exposes your trading patterns and deployment schedule never reaches a vendor, because there is no vendor in the path. You operate the infrastructure. In return you stop negotiating data processing addendums and stop filing cross-border transfer assessments for telemetry that, under this model, never crosses a border.
Why the kernel, and not the application
Bank infrastructure is not one stack. Trading platforms mix Java, C++, and Python. Risk engines run R into compiled libraries. Pipelines move data between S3, Snowflake, and internal compute. An application-layer tool sees only what the application chose to log. A WAF sees HTTP. EDR sees file writes and process starts. Predictive tools guess ahead of the move and miss the permitted one. Detection and response tells you once the data is gone.
The kernel sees the move itself, before application code can obfuscate or encrypt it: which data moves, where it goes, and the job behind it. That is the vantage that catches an exfiltration riding a permitted access path around your application logs, or sensitive movement tunneled inside a sanctioned remote-access tool. Hilt surfaces the anomalous move as it forms, on the same compute where it happened, and writes the case. When a pattern crosses the line, the response is host-level network isolation, quarantine from the control plane. The collector never sits inline and never blocks, drops, or alters traffic.
The footprint a trading desk will accept
A trading-platform team rejects any instrumentation that shows up in a latency budget. Hilt clears that bar because the collector sits off the path. It watches movement rather than mediating it.
The collector runs at negligible overhead, on the order of 0.1% of a single core and roughly 4 to 8 MB of memory, and it holds that footprint flat per host. Run a thousand hosts and the cost does not compound into an argument against governance. The same collector unit covers a cloud workload or a user endpoint, so cloud and endpoint stay one model rather than two stacks to reconcile. For a team already drowning in alerts from four other tools, the output is a finished case, not another queue. The pattern across moves, not noise.
Where this sits next to what you already run
Keep your SaaS stack for the coverage that never touches regulated telemetry. CrowdStrike for endpoint malware where the indicators carry no process arguments. Zscaler for web filtering where the URLs are not client-specific. Proofpoint for email scanned before it reaches internal systems. Hilt is additive to each. It replaces none of them.
What it adds is the layer those tools cannot place inside your perimeter: the runtime view of where your most valuable data actually goes, resolved to identity and job, processed entirely in your own cloud, baselined on your own roles and workloads, with the response staying inside the control plane and no event data ever leaving. That is the one gap a SaaS security model cannot reach inside a regulated bank, and it is the gap a 30-minute technical call is built to walk through against your own residency constraints.