01
Embedded
Lives inside the app. Ships when you ship. No agent. No sidecar. No separate service contract.
Gladius
LoadingAutonomous Web Application Intelligence System
Embedded application-layer defense, self-learning attacker playbooks, active deception, genetically evolving rules, and self-grading intelligence — all running inside the same compute that serves the app. Zero AI-API dependencies. Zero inference cost. Always learning.
What’s new about it
01
Lives inside the app. Ships when you ship. No agent. No sidecar. No separate service contract.
02
Pure statistics — Thompson Sampling, EMA, z-score, linear regression. No AI APIs. No GPUs. No inference bill.
03
Learns defense AND attack patterns. Most products do one. AWAIS evolves both sides every day.
04
Phantom architecture at the application layer — mirage credentials, doppler responses, crawler traps the attacker can't tell from real surface.
05
Generates plain-English findings continuously via template NLG. The operator never reads a stack trace to understand what's happening.
06
IQ score: deterministic, externally benchmarked, never decreasing. The engine can prove it got smarter this week.
07
NSGA-II multi-objective evolution. Defense rules breed, mutate, and get culled by a fitness function tuned for false-positive cost.
08
War games against its own config every 2 hours. If a synthetic adversary breaks through, the rule that should have caught it is logged as a regression.
09
261 root causes, 281 fix steps, stack-specific to Supabase, Vercel, Next.js, and Clerk. No 'check your logs' answers.
10
One brain watches 5 products simultaneously: CRM, BDC, Turf, Stone, Detail. Patterns learned in one vertical hardens the others.
The architecture
AWAIS is what you get when a reliability engine and a security engine share the same memory, the same compute, and the same feedback loop.
Reliability Engine
Diagnoses, predicts, narrates, grades itself.
Security Engine
Learns attackers, plants deception, evolves its own rules.
Why existing products can’t replicate this
Their category
What they do
What they don’t
Datadog / New Relic / Dynatrace
Bolt-on APM
Don't live inside the app. Don't know your stack-specific incidents.
Cloudflare WAF / AWS WAF / Imperva
Signature-based defense
Don't learn attacker playbooks. Don't plant deception. Static rules age fast.
Attivo / Illusive
Network-layer deception
Not application-layer. Can't lie inside your own routes.
Darktrace / SentinelOne
ML-based detection
Need GPUs and training pipelines. Bolt-on, not embedded. Inference bill scales with traffic.
Gladius AWAIS
Embedded, dual-sided, $0 inference, $0 GPUs, self-grading, self-evolving, application-native. No existing product runs all 10 properties in one engine.
What’s not (yet) perfect
The same scoreboard that grades AWAIS up also flags where it isn’t done yet. We publish both.
See it live
Founders demo
See the SOC dashboard, watch the threat-level gauge respond to live traffic, see Sentinel catch a synthetic regression in real time, watch Defense plant a phantom credential and fingerprint the attacker who bites.
Read the source
All 28 modules — Sentinel + Defense — open to operator review under NDA. Every algorithm, every rule, every IQ benchmark, every synthetic-adversary scorecard.
Coined by Ricardo Gamon · Gladius Technologies LLC · 2026