Stop blocking data.Start understanding it.
TriNetraa is a new category — Cognitive Data Intent Intelligence. It reads data by what it actually is: the content, the intent, the identity and the workflow behind every movement — and stops classified information the instant it heads for an AI prompt, a local app, or the door. Airtight protection your people never feel.
Legacy DLP tags files. TriNetraa understands content.
For twenty years, data security meant file types, regex and rules — and a tag someone in IT applied once and forgot. It frustrated employees, buried teams in false positives, and still missed the leaks that mattered. We didn't build a better rulebook. We built comprehension.
Block, frustrate, repeat
- —Classifies by file type and a manual label — blind to what the content actually is
- —One label per file; misses the confidential table buried in a "public" document
- —Classification lives with IT, not the people who created the work
- —Blind the moment content is pasted, fragmented, or sent to a local AI app
Understand, permit, protect
- +Micro-classifiers read meaning at the chunk level — content, not containers
- +Many classifications in one document; each chunk judged on its own merits
- +Classification in the user's hands, with policy guardrails — not an IT backlog
- +Detects & blocks classified chunks in any AI prompt — cloud copilots and local apps
Three lines of understanding, one verdict.
TriNetraa doesn't ask "what is this file?" It asks "what is happening here, and should it?" Three streams of comprehension resolve into a single real-time decision — explainable, with the reasoning attached.
The why behind the move
Content-level comprehension that survives paraphrase, reformatting and fragmentation — the meaning of data is understood, not just its shape.
The who, in context
Role, history and trust posture, evaluated continuously. The same action is fine from one person and a red flag from another — TriNetraa knows the difference.
The where it belongs
The business process the data lives in — sanctioned path, approved destination, normal rhythm, or an anomaly worth a closer look. Context decides.
Hundreds of micro-classifiers, reading content the way a person would.
At TriNetraa's core is an array of purpose-built micro-classifiers — each one expert in a single kind of sensitive content. Together they classify data by what it actually is, at the chunk level, never by file type or a label someone forgot to apply. Try it below.
A single file carries a public cover page, a confidential table, a regulated record and a fragment of source — all at once. TriNetraa classifies each chunk on its own merits, simultaneously.
Content-based classification
Driven by what the content means — not extension, location, or a stale label. A renamed file, a screenshot, a pasted paragraph: all understood the same way.
Multi-classification per document
The same document can be public, confidential, regulated and IP — chunk by chunk, evaluated in parallel and protected independently.
Auto-classify with industry models
Industry-tuned LLMs and domain-trained models classify automatically for finance, pharma, legal, semiconductor and more — so TriNetraa understands your data on day one.
Classification in the user's hands
Classification belongs to the people who create the work — not a central IT backlog. Fast, in-the-moment classification inside policy guardrails: accurate, owned, and fully audited.
Classified content, caught chunk-by-chunk — in any prompt.
TriNetraa detects classified information chunk by chunk and blocks it inline in any AI prompt — cloud copilots and local desktop apps alike — even when it's fragmented across a paste. Pick a scenario and watch it evaluate intent, identity and workflow before anything leaves.
Comprehension at the edge. Your content never leaves the endpoint.
A single lightweight agent classifies and decides on-device. The control plane only ever sees verdicts and metadata — never the data itself. That is the architecture that lets regulated enterprises adopt AI without surrendering their data to a third-party model.
Classification and the allow / coach / block decision happen entirely on the device, in under a quarter-second, online or offline.
Raw content stays on the endpoint. Only verdicts, scores and operational metadata reach the control plane — by design.
On-device enforcement keeps working independent of cloud availability. Fail-open by default; fail-closed where policy elects.
Every OS. Every app. Every prompt.
One lightweight agent on the endpoint, watching the surfaces that matter — and your content never leaves the device to be inspected.
The same engine, tuned to your regulated world.
Industry-trained models mean TriNetraa recognises what matters in your sector on day one — and the highest-stakes leak path in each is the AI prompt.
Financial Services
MNPI, deal terms, customer PII and trade data understood in context — and stopped before it reaches a copilot or a personal account.
Pharma & Biotech
Trial data, formulations and IND/NDA records classified at the chunk level — protected across research collaboration and AI tools.
Semiconductor
Mask data, process recipes and design files — the crown-jewel IP — recognised and held back from local and cloud AI alike.
Legal
Privileged matter content, client PII and settlement terms understood and protected — without slowing the people doing the work.
Energy & Utilities
Grid, SCADA and critical-infrastructure data classified on-device, with comprehension that never relies on a cloud round-trip.
Public Sector
Classified and citizen data protected at the edge with full audit, satisfying data-residency and sovereignty requirements.
Built for the leak path that legacy DLP can't see.
Rule-and-regex DLP was designed for email and USB sticks. The AI prompt — especially the local desktop app — is the blind spot. Here is how the approaches compare.
| Capability | Legacy DLP | TriNetraa |
|---|---|---|
| Unit of classification | Whole file | Chunk-level, many classes per file |
| What it reads | File type, regex, manual label | Content & meaning, via micro-classifiers |
| Survives paraphrase & reformatting | No | Yes |
| Blocks inside AI prompts | Rarely | Cloud & local apps |
| Local / offline desktop AI coverage | No | Yes |
| Where decisions run | Cloud / gateway | On-device, <250 ms |
| Content sent off-device to inspect | Often | Never |
| Who classifies | Central IT backlog | Creator, inside guardrails |
| Response to risk | Block & frustrate | Allow · coach · block, with reasons |
Comparison reflects TriNetraa's design approach versus the common characteristics of rule-and-regex DLP; capabilities vary by specific vendor and configuration.
Designed for speed people never feel.
Latency and friction are design targets validated per deployment during proof of concept against agreed success criteria.
CISO to CISO.
TriNetraa is built by a practicing CISO. We work with a small group of design partners under NDA — quotes below are placeholders to be replaced with named, approved references.
"[Placeholder — design-partner quote on closing the AI prompt blind spot without slowing the team.]"
"[Placeholder — quote on chunk-level classification catching what file-level DLP missed.]"
"[Placeholder — quote on content never leaving the endpoint satisfying the regulator.]"
Defensive and protective — in its DNA.
TriNetraa was engineered from first principles to protect, and to satisfy the world's data-protection regimes — comprehension happens at the edge, and your regulated content never enters a third-party model. Compliance isn't bolted on; it's the architecture.
A method no one else has.
TriNetraa's real-time, content-level classification and detection method is a patent application published with the USPTO. Comprehension runs at the endpoint; the control plane sees decisions and metadata — never your content.
Start with a proof of concept on your own data.
Per-endpoint subscription, sized to your environment. Every engagement begins with agreed success criteria — accuracy, latency and zero user friction — before anything goes live.
- Chunk-level classification
- AI-prompt & egress coverage
- macOS · Windows · Linux agent
- On-device decisioning
- Standard support
- Everything in Base
- Industry-tuned classifier models
- Local / desktop AI app coverage
- Coaching & policy guardrails
- Full audit & dashboards
- Priority support
- Everything in Advanced
- Data residency by region
- On-prem / private control plane
- Custom model tuning
- SSO, SCIM & SIEM integration
- Named TAM & SLAs
The honest answers.
Legacy DLP classifies whole files by type, location or a manual label, and lives at the cloud or network gateway. TriNetraa classifies content at the chunk level by what it means — surviving paraphrase, reformatting and fragmentation — and decides on the endpoint, including inside local AI apps that never touch your network. It complements rather than rips out existing controls.
No. Classification and decisioning run on-device. The control plane receives verdicts, scores and operational metadata only — never the underlying content. That architecture is what allows regulated enterprises to adopt AI without exposing their data to a third-party model.
Yes — that is the blind spot we were built for. A single endpoint agent watches browser copilots, native and local AI apps, desktop apps, cloud storage and outbound egress, and holds classified chunks at the prompt before they leave, even when fragmented across a paste.
The agent is lightweight and decisions are designed to complete on-device in under 250 ms — fast enough that users don't feel it. Exact latency and the zero-friction target are validated against agreed success criteria during your proof of concept.
TriNetraa's real-time, content-level classification and detection method is the subject of a patent application published with the USPTO. It is a published application, not yet a granted patent — we state that accurately rather than overclaiming.
The architecture is designed around GDPR, India DPDP and UAE PDPL, with HIPAA support, EU AI Act assessment, ISO 27001 alignment, SOC 2 Type II in progress, and data residency by region. Because content stays on the endpoint, many cross-border transfer concerns simply don't arise.
See TriNetraa classify and stop a live leak — in your environment.
A 30-minute technical briefing, CISO to CISO. We'll classify and evaluate a real movement on your own data and agree the success criteria before we begin: accuracy, latency, and zero user friction.