TRA-CE.ai
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Know what happened.
Prove .

Verified causal chains from your security events. Every link evidence-graded. Every finding traced to source.

FIPS 203/204 · Post-quantum encrypted
See the proof →
Built on
Formal pattern algebra
Evidence-graded causal graphs
FIPS 203/204 post-quantum crypto
PostgreSQL row-level isolation
MITRE ATT&CK mapping

Your SIEM tells you what.
It never tells you why.

Security teams spend hours correlating alerts that were never designed to be connected. The SIEM shows temporal proximity. The analyst assumes causation. The board gets a summary that sounds confident but cannot be verified.

TRA-CE sits beside your SIEM and constructs the causal chain that your existing tools cannot. Every link is evidence-graded. When the chain is provable, you know it. When it is not, you know that too.

11,000+
Average daily alerts in an enterprise SOC. Fewer than 5% are real threats.
277 days
Average time to identify and contain a breach. Most of that is spent reconstructing what happened.
4 heuristics
Explicit evidence, artifact correlation, MITRE technique progression, and temporal analysis. Each edge is graded independently.

From alert chaos
to causal order

One collector. Three steps. No agents on endpoints.

01 INGEST

Deploy the collector

A lightweight Docker container inside your network. All data encrypted end-to-end via Avon — our post-quantum transport layer using ML-KEM-768 + X25519 hybrid key exchange with 30-second session rotation. Connects to your SIEM, EDR, identity provider, or cloud platform.

02 CHAIN

Build causal chains

Events are linked into directed causal graphs using four inference heuristics. Each link carries a confidence grade: PROVABLE, MIXED, or INFERRED.

03 ACT

Investigate with evidence

AI investigation agents produce a WHY stack: what failed, what should have caught it, what to fix, and who owns it. Analysts decide. TRA-CE provides the proof.

What's under
the hood

Seven capabilities. One platform. Every link in the chain graded, traceable, and court-ready.

Core Engine
01

Causal Chain Building

Four inference heuristics construct directed evidence graphs from event streams. Explicit system evidence, artifact correlation, MITRE technique progression, and temporal proximity. Each edge is graded independently.

Detection
02

Campaign Scoring

4+ stages = confirmed campaign

MITRE stage progression scoring detects multi-stage attacks. Two stages create a seed. Three trigger an alert. Four or more confirm an active campaign.

Intelligence
03

Behavioral Baselines

Per-entity profiling learns what normal looks like for your environment. Deviations surface as anomalies with context. No signatures required. TRA-CE catches what your rules never anticipated.

Investigation
04

Autonomous AI Triage

AI investigation agents run a three-stage pipeline: gather evidence, build the WHY stack, map interventions. Every conclusion is graded with the same evidence framework as the chain.

Feeds
05

Threat Intelligence

Live feeds from CISA KEV, NVD, GitHub Advisory, and CISA Advisories. Automatically correlated with active chains. Known exploited vulnerabilities flagged in context.

Security
06

Post-Quantum Transport

30s key rotation

ML-KEM-768 + X25519 hybrid key exchange. ML-DSA-65 signatures. AES-256-GCM encryption. FIPS 203/204 compliant today.

Operations
07

Evidence-Ready Output

Every finding traces to source events with full lineage. Export chains as structured evidence for compliance audits, incident reports, or board presentations.

Stop correlating.
Start proving.

Request access and our team will walk you through a demo tailored to your stack and your threat model.

Request Access →