Token Pruning & Value Banked
0.2ms P95 Engine
1,428,500 tokens
▲ 92.4% reduction vs raw context collector baseline
Auditable WITNESS Ledger
Fail-Closed
48 receipts
100% verified zero prompt contamination detected
Code Health Invariant
Grade A
94/100
0 God Files AST skeletons maintained cleanly
13-Layer Context OS Architecture Matrix
The 13 canonical operational layers governing context selection, zero-loss recovery, cryptographic receipts, gateway proxy, and multi-agent coordination.
L10Session Intelligence & Enterprise Model Arbitrage
Token reduction accounting, cross-model margin expansion, and bounded burn trajectory.
Projected Annual Savings
$171,420
Modeled at 25-engineer agent fleet scale ($14.28/day current)
Context Compression Ratio
3.8x (73.4%)
Mean tokens pruned before remote LLM ingress
IP Leakage & Poisoning Risk
0.00%
Cryptographically sealed via fail-closed SHA-256 WITNESS
Fleet Developer Velocity
+42% Faster
Eliminates context limit truncations and agent retry loops
Enterprise Model Arbitrage & Margin Expansion
Input Token Rate| Frontier Model | List Price / 1M | Uncompressed Monthly | Entroly Compressed | Net Savings |
|---|---|---|---|---|
| Claude 3.7 Sonnet | $3.00 | $14,400 | $1,440 | +$12,960/mo |
| GPT-4o | $2.50 | $12,000 | $1,200 | +$10,800/mo |
| Gemini 2.5 Pro | $1.25 | $6,000 | $600 | +$5,400/mo |
| DeepSeek R1 | $0.55 | $2,640 | $264 | +$2,376/mo |
Token Burn Trajectory
Uncompressed agent spend vs Entroly governed ceiling
Day 1
Day 30
Day 60
90-Day Run Rate
Context Compression & AST Scaffold Workbench
Real-time side-by-side verification: raw intercepted context vs reversible CSE scaffold. Type or paste your own code below to test live!
Raw Input Context
184,200 tokens
Reversibly Compressed Scaffold
12,450 tokens
93.2% saved
Frontier Model Cost Arbitrage
Claude 3.7 Sonnet
$0.5526
→
$0.0373
+$0.5153 saved per prompt
GPT-4o
$0.4605
→
$0.0311
+$0.4294 saved per prompt
DeepSeek R1
$0.1013
→
$0.0068
+$0.0945 saved per prompt
Cryptographic WITNESS Receipts Ledger
SHA-256 Verifiable ChainEvery context reduction decision is signed into an auditable ledger, guaranteeing zero prompt poisoning and complete recoverable lineage.
| Receipt ID | Agent | Query Target | Original | Optimized | Reduction | Integrity | Time |
|---|
PRISM Reinforcement Learning Weight Radar
Adaptive TopologyCurrent Learned Heuristics
0.30
0.25
0.25
0.20
0.15
Security Tripwires & Repository Health Matrix
RAVS ActivePrompt Injection Scans
0 Detected
Zero malicious instruction injection in intercepted prompts
Context Poisoning Trips
0 Failures
WITNESS verification checksums match across all receipts
God Files & Bloat
2 Pruned
Files over 1,500 LOC automatically converted to CSE scaffolds