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.
Four Numbers That Redefine the Category
These are not incremental improvements. They represent a fundamentally different detection approach.
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.
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.
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.
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.
AhanaAI by the Record
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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