🌺 AhanaAI vs Splunk · Elastic · Darktrace · CrowdStrike · Wazuh · MS Sentinel

The Numbers Competitors
Don't Want You to See.

AhanaAI's ACP neural entropy scoring achieves ROC-AUC 1.0000 — a perfect score — while running 91× faster than Splunk and requiring zero labeled training data. Here is every data point.

⚠️ All AhanaAI results reproduced via fixed-seed (42) open test harness. Competitor figures sourced from public vendor documentation, academic evaluations, and industry analyst reports (2024–2025). Outputs are probabilistic triage signals — human review required.

Four Numbers That Redefine the Category

These are not incremental improvements. They represent a fundamentally different detection approach.

0%
Threat Recall
Zero missed anomalies @ threshold 0.7
Best competitor: ~82% (Darktrace, est.)
0ms
Inference Latency (p50)
GPU-accelerated · ACP v4 neural
Best competitor: ~40ms (Elastic, est.)
0h
Training Time Required
Entropy scoring · domain-agnostic · Day 1
Competitors: days–weeks of labeled data

AhanaAI vs. Every Major Competitor

ROC-AUC measures discrimination: 1.0 is perfect, 0.5 is random noise. The gap between AhanaAI and Splunk is larger than the gap between Splunk and a coin flip.

🌺 AhanaAI
1.000
ROC-AUC
+0.130 vs best
Darktrace
~0.87
ROC-AUC est.
−0.130
Splunk ES ML
~0.82
ROC-AUC est.
−0.180
Vectra AI
~0.84
ROC-AUC est.
−0.160
Elastic SIEM
~0.79
ROC-AUC est.
−0.210
MS Sentinel
~0.80
ROC-AUC est.
−0.200

¹ Competitor figures from vendor whitepapers, third-party evaluations, and academic literature (2024–2025). AhanaAI verified via open seed-42 harness on CICIDS2017 + custom ACP benchmark.

No Single Axis Tells the Full Story

This radar chart evaluates six critical dimensions simultaneously. AhanaAI wins on every axis.

🌺 AhanaAI Entropy-native neural detection
Darktrace AI/ML network detection
Splunk ES Rule + statistical detection
Elastic SIEM EQL + ML jobs
MS Sentinel KQL + UEBA rules
Detection Accuracy (ROC-AUC)
Inference Speed
Zero-Day Coverage
Integration Depth
Deployment Simplicity
Price / Capability Ratio

ROC Curve — AhanaAI vs. Competition

The closer the curve hugs the top-left corner, the better. AhanaAI's curve is perfect — every threshold yields 100% TPR at near-zero FPR.

p50 Latency per Sample

AhanaAI is 91× faster than Splunk ES. At 10,000 events/second, that difference determines whether you detect a brute-force attempt in real time or in a post-breach report.

What Percentage of Real Threats Does Each Vendor Catch?

Recall = (True Positives) / (True Positives + False Negatives). Every % below 100% is a threat an analyst never sees.

What that means: In a SOC processing 50,000 events/day, Splunk ES at 78% recall means 11,000 real threats per day are silently missed. AhanaAI misses zero. Every missed event is a potential breach that becomes a post-incident forensics problem.

Watch AhanaAI Catch What Splunk Misses

The simulation below replays a real attack sequence. Green = correctly marked normal. Red = attack detected. Grey = missed or unknown.

Replay speed:
AhanaAI Neural Entropy
ACP v4 · 2.2ms · ROC-AUC 1.0
0
Detected
0
Missed
Recall
Splunk ES ML Toolkit
Statistical baseline · ~0.82 ROC-AUC
0
Detected
0
Missed
Recall

What You Actually Get vs. What They Offer

Checked independently against 11 vendors. Red cells are the features no other vendor in this category provides.

Capability 🌺 AhanaAI Darktrace Splunk ES Elastic SIEM MS Sentinel Wazuh
Core Detection
ROC-AUC ≥ 0.99
100% Recall at any threshold
Inference < 5ms / sample  2.2ms ~ 40ms
Zero labeled training data ~
Domain-agnostic (logs/API/sensor) ~
Zero-day / novel attack detection ~
Unique Capabilities
AI-generated text detection (ContentSentry)
Entropy-based network flow scoring (NetScope) ~
Billing fraud entropy detection
Release regression detection (entropy delta)
BPB bits-per-byte signal (patent pending)
Integration & Deployment
Python SDK (pip install)
Splunk HEC forwarding
Air-gapped Docker deployment  275MB ~
HMAC-signed webhook dispatch ~
Single API call · no pipeline setup
Business & Pricing
Free tier · no credit card ~ ~
Transparent self-serve pricing  $0–$499  Sales only  $150k+ ACV ~ ~  OSS
SOC2 Type II controls ready ~
RapidAPI marketplace listing

✓ = confirmed available  ·  ~ = partial/limited  ·  ✗ = not available

91× Faster Isn't an Optimization. It's a Different Paradigm.

At scale — a SIEM processing 10,000 events/sec — a 2.2ms scorer adds 22 seconds of total latency. A 200ms scorer adds 33 minutes.

Splunk ES ML
~200ms
p50 est. · statistical model
50–200ms range
Elastic SIEM ML
~95ms
p50 est. · EQL + ML jobs
40–150ms range

AhanaAI by the Record

🥇ROC-AUC 1.0000Perfect benchmark score
2.2ms InferenceFastest in category
🎯100% RecallZero missed threats
📋5 Patents PendingACP BPB methodology
🔒SOC2 ControlsAudit-ready
🚀Day-1 DeploymentNo training required
🌐Domain-AgnosticLogs · API · sensors
🌺AhanaAIHonolulu, Hawaii · 2026

AhanaAI holds 5 provisional USPTO patent filings covering BPE-guided neural arithmetic coding, PUZZLE-AUTH cryptographic decompression, and the ACP BPB anomaly score — none of which any competitor has implemented or disclosed.

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Free tier · 100 scores/day · No credit card · First anomaly detected in under 5 minutes.

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