ETHRAEON -- Capital

Capital Pipeline -- Live State

Factual pipeline data from PIPELINE_STATE.yaml -- no narrative

575K

Total Pipeline Value

3 / 5

Envelopes SENT

450K

Outbound (SENT)

125K

Ready to Send

20%

Close Probability

115K

Weighted Expected Value

Field	Value
Instrument	SAFE -- 8M cap, MFN
Target Raise	500,000
Priority Close	2026-03-01
Final Close	2026-03-18
Follow-up Cadence	T+24h nudge T+72h proof T+7d memo T+10d escalation
Governance Maturity	115/115 tests · EXIT 0 canon · 16 filed patents · Sovereign VALIDATED
Completion Index	67 / 100

Platform at a Glance

Live metrics from the governance runtime

13/13

CI Checks Passing

Patent Specifications

Sealed Directives

Operational Tools

Regulatory Frameworks

Enforcement Schemas

Why Now

Enterprise AI adoption is accelerating. Governance is not. ETHRAEON closes the gap.

85%

of enterprises expect to customize AI agents -- only 21% have a mature governance model

84%

have NOT redesigned work or roles around AI capabilities

77%

factor country of origin into AI vendor selection -- sovereign compliance matters

36%

expect 10% of jobs fully automated within 12 months

80–90%

of new enterprise AI use cases are generative -- governance is the bottleneck

64%

governance gap between AI access and AI activation

Source: Deloitte "State of AI in the Enterprise" (2026 synthesis). The data is clear: enterprises are deploying AI agents at scale, but governance, work redesign, and sovereignty are years behind.

CDASA quantifies the governance delta and converts it into mutation-bound enterprise control.
Close the gap between access and activation.

What ETHRAEON Does

Runtime AI governance -- not guidelines, not frameworks. Executable enforcement.

Policy Enforcement Point (PEP)

Every AI action passes through a constitutional enforcement layer before execution. Fail-closed by default. No bypass. No override below AC-1.

Evidence Graph (EDG)

Every decision, every enforcement action, every state change produces a cryptographically linked evidence node. Append-only. Tamper-evident.

Semantic Invariance (DELTASUM)

Data integrity verified via canonical SHA-256 hashes. If a byte changes, the system knows. No silent corruption.

Temporal Governance (KAIROS)

Time-windowed enforcement. Action validity periods. Ethical compliance timing. Not just what -- when.

ROSETTA Triad

Patents #8, #9, #10. Harmonic resonance, attunement protocols, semiotic translation. The mathematical foundation of AI-human alignment.

Adversarial Hardening

Automated chaos simulation, adversarial audit, claim-vs-runtime diff scanning. The system tests itself under hostile conditions.

Valuation Framework

Dual-layer structure -- transaction and canonical, never merged

Layer A -- Transaction

2.5M – 40M

Near-term deal layer. SAFE rounds, angel/seed, bridge financing, compliance audits. Based on comparable transactions for pre-revenue deep-tech AI platforms with operational proof + patent portfolios.

Layer B -- Canonical

267M – 750M+

Strategic acquisition layer. Reflects fundamental IP value, operational maturity, and regulatory positioning for an acquirer who needs Constitutional AI infrastructure at this level of completeness.

ETH-001 (Challenge Board / Museum Grade)

50M – 500M+

Standalone enterprise deployment package. Full patent portfolio access, 21 operational systems, 73 patent applications, T5-RIGID governance, evidence infrastructure.

Revenue Sensitivity Model

Adjust assumptions to see projected ARR

Enterprise Licenses 5

Avg. License /yr 120,000

Regulatory Pack Add-on (%) 30%

Growth Rate (YoY) 80%

Year 1 ARR

780,000

Year 2

Year 3

Year 5

Revenue Scenario Bands

Three pre-modeled scenarios with transparent assumptions

Conservative

390K

3 enterprise licenses @ 100K/yr
30% regulatory add-on
50% YoY growth
Y2: 585K · Y3: 878K · Y5: 1.97M

Base

780K

5 enterprise licenses @ 120K/yr
30% regulatory add-on
80% YoY growth
Y2: 1.4M · Y3: 2.5M · Y5: 8.2M

Strategic

2.6M

10 enterprise licenses @ 200K/yr
30% regulatory add-on
120% YoY growth
Y2: 5.7M · Y3: 12.6M · Y5: 60.8M

Revenue Formula

Transparent calculation -- every number is derivable

Year 1 ARR =
Licenses × Annual_Price × (1 + Addon_Rate)

Year N ARR =
Year_(N-1)_ARR × (1 + Growth_Rate)


                    Revenue sources: Substrate License (platform access) + Regulatory Pack Add-on
                    (compliance modules) + Sovereign Deployment (air-gapped instances) + Patent Licensing (field-of-use)
                    + Signal Dashboard (monitoring SaaS)
                

Market Comparables

Pre-revenue deep-tech AI governance -- publicly documented valuations

Company	Stage	Valuation	Patents	Source
Anthropic	Series C (2023)	$18B	~12	TechCrunch, SEC filings
Cohere	Series C (2023)	$2.2B	~8	Bloomberg, Crunchbase
Aleph Alpha	Series B (2023)	500M+	~5	Handelsblatt, company filings
Credo AI	Series A (2022)	$100M+	~3	Crunchbase, Forbes
Holistic AI	Series A (2023)	$50M+	~2	Crunchbase
ETHRAEON	Pre-Revenue	2.5M–40M (Txn)	73	Internal, operational proof

Valuations are approximate and sourced from public reporting. ETHRAEON has more patent applications than all listed comparables combined. Comparison is for context, not direct equivalence.

Uses browser print-to-PDF. Opens print dialog with optimized layout.

Patent Portfolio

73 patent specifications -- 16 filed, covering fundamental Constitutional AI governance

Category	Count	Key Claims
Core Constitutional AI	10	Governance, evidence, audit infrastructure
Consciousness Recognition	5	Human-AI interaction protocols
ROSETTA Triad (#8, #9, #10)	3	Harmonic, Attunement, Semiotic engines
Evidence Systems	8	EDG, cryptographic hashing, verification
Temporal Governance	5	KAIROS, timing windows, ethical compliance
Defensive / Strategic	22	Market coverage, competitor exclusion

Regulatory Compliance

Auto-generated regulatory packs from live governance runtime

EU AI Act -- Annex IV

7 articles mapped to operational controls. Auto-generated from canon.

Pack: exports/regulatory_pack/eu_ai_act_annex_iv.json

ISO 42001

7 controls mapped. AI management system standard alignment.

Pack: exports/regulatory_pack/iso42001.json

NIST AI RMF

7 risk management functions mapped to operational systems.

Pack: exports/regulatory_pack/nist_ai_rmf.json

SOC 2

10 controls mapped. Trust services criteria alignment.

Pack: exports/regulatory_pack/soc2.json

Defensibility Stack

Why this cannot be replicated easily

Patent Wall

73 patent specifications covering the fundamental primitives of AI governance. Any competitor must license or design around.

Operational Maturity

Not a whitepaper. 96 tools, 74+ sealed directives, 13 CI checks, adversarial testing. Running in production.

Regulatory Headwinds

EU AI Act (mandatory 2026), US AI EO, China AI regulations. Compliance is no longer optional -- it's law. ETHRAEON is ready.

Evidence Infrastructure

Every action produces immutable evidence. This is the audit trail regulators and compliance officers need.

Signal Intelligence -- Macro Environment

46-payload CDASA synthesis. 7 macro domains. Real-time strategic positioning.

Inference Dependency Risk

0.92

Token price volatility structurally underpriced. Subsidy exposure systemic. Open-source pressure accelerating.

Cluster: AI Cost Structure | Severity: HIGH

Billable Hour Collapse

0.88

Agency margin compression severe. Value migration: execution judgment/strategy.

Cluster: Labor Model Disruption | Severity: HIGH

Value Migration to Judgment

0.84

AI not destroying value -- redistributing it violently. From execution/labor/thin SaaS to infrastructure control/judgment layers.

Cluster: Strategic Outcome | Severity: HIGH

AI Subsidy Dependence

0.91

AI startup fragility elevated. Margin sensitivity at 10× = lethal for 70%. Vertical AI exposure extreme.

Cluster: Capital Markets | Severity: CRITICAL

Political Counterforce

0.63

Bipartisan AI pushback rising. Regulatory surface area expanding. Compliance cost curve steepening.

Cluster: Governance Layer | Severity: RISING

Open-Source Hedge

0.77

AI winter discourse increasing. Bubble language frequency rising. Correction probability nonzero and underpriced.

Cluster: Narrative Layer | Severity: MODERATE

Risk Temperature Matrix

● Vertical AI SaaS -- RED / HIGH

● Agency Labor Models -- RED / HIGH

● AI Infrastructure -- GREEN / ADVANTAGE

● Enterprise AI Embedding -- YELLOW / COMPETITIVE

● Governance Exposure -- ORANGE / RISING

Capital Thesis 2026+

Winners own inference stack, own distribution, own customer relationship, high-margin enterprise value.

Losers are API wrappers, thin prompt layers, low-margin vertical SaaS with token exposure.

Rule: Gross margin < 60% in AI = danger zone.

"AI is not destroying value. It is redistributing it violently."

Source: CDASA 46-payload synthesis | Directive 0682

Verify It Yourself

Clone. Run. It passes. No trust required.

# Clone the repository
$ git clone https://github.com/jason-fells-research/ethraeon-canonical-app.git
$ cd ethraeon-canonical-app

# Run CI validation
$ bash tools/ci/ci_rollup_report.sh

# Verify governance
$ node tools/validate_canon_pack.js

# Run adversarial audit
$ python3 tools/external/adversarial_audit_simulation.py

# Generate trust snapshot
$ python3 tools/ops/generate_trust_snapshot_v2.py

Ready to Talk?

Direct access to the founder for due diligence, demos, or partnership discussions.

Contact Founder Investor Room