Update README.md

README.md

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-title: FinC2E — Financial Cognitive Compliance Engine
+title: FinC2E-Governance
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-## FinC2E — Governance-First Financial AI
+# FinC2E — Governance Gateway (Space)
 
-**FinC2E (Financial Cognitive Compliance Engine)** is a governance-first, human-in-the-loop AI system designed for **regulated financial environments** where decision legitimacy, auditability, and accountability are mandatory.
+This Space is the **governance-first interface** for FinC2E (Financial Cognitive Compliance Engine) under **BPM RED Academy — HumAI MightHub**.
 
-FinC2E does **not** automate enforcement.  
-It structures, validates, and documents decisions.
+## What this Space is
+- A **Governance & Evaluation UI** (public-facing)
+- A **product card** for enterprise stakeholders
+- A **controlled onboarding gateway** to FinC2E capabilities
 
----
-
-## What FinC2E Is
-
-FinC2E is a **non-autonomous cognitive engine** supporting:
-
-- AML / KYC / CDD triage
-- Financial risk classification
-- Compliance decision support
-- Audit-ready reasoning output
-- Policy-referenced assessments
-
-Every output is:
-- deterministic
-- explainable
-- traceable
-- human-approved
-
----
-
-## Core Design Principles
-
-- **Governance-first architecture**
-- **Human-in-the-loop by design**
-- **No black-box scoring**
-- **No autonomous decisions**
-- **Policy-referenced reasoning**
-- **Audit-before-action logic**
-
-FinC2E is built to operate **above models**, not inside them.
-
----
-
-## What FinC2E Is NOT
-
-- ❌ Not an autonomous decision-maker  
-- ❌ Not a credit scoring engine  
-- ❌ Not a replacement for compliance officers  
-- ❌ Not an enforcement system  
-
-FinC2E structures responsibility — it does not remove it.
-
----
+## What this Space is NOT
+- Not an inference endpoint
+- Not an automated compliance system
+- Not a legal or regulatory authority
 
-## Deployment Modes
+## Model of record
+The canonical model card lives here:
 
-FinC2E can be deployed as:
+- **Model:** `MightHubHumAI/FinC2E`
 
-- Enterprise SaaS (End-to-End)
-- Private inference service
-- On-premise / regulated cloud
-- Advisory layer above existing AI models
-- Compliance & governance middleware
+This Space communicates scope, principles, and evaluation posture. The model card defines the system’s intended use, constraints, and governance rules.
 
-Deployment is tailored to regulatory, jurisdictional, and institutional constraints.
-
----
-
-## Monetization Models (Indicative)
-
-FinC2E supports multiple monetization paths:
-
-- Subscription-based access
-- Usage-based inference
-- Per-decision governance validation
-- Enterprise licensing
-- Regulated private deployments
-
-**Pricing is risk-, value-, and compliance-adjusted at contract time.**
-
----
-
-## Target Users
-
-- Financial institutions
-- Regulated enterprises
-- Compliance & risk teams
-- Audit & governance functions
-- AI governance stakeholders
-
----
-
-## Governance Commitment
-
-FinC2E operates under strict governance constraints:
-
-- No opaque inference
-- No untraceable outputs
-- No automated enforcement
-- Full audit trail by default
-
----
+## Access & Engagement
+FinC2E is deployed under **human-in-the-loop** constraints and is intended for regulated, high-stakes environments.
 
-## Status
+Engagement modes:
+- Pilot / PoC (controlled evaluation)
+- Enterprise onboarding (contractual access)
+- Private deployment paths (as applicable)
 
-🔒 **Preview / Governance Artifact**  
-📩 Enterprise & institutional inquiries via official channels only.
+## Links
+- BPM RED Academy: https://www.bpm.ba
+- Contact: via official BPM channels
 
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 © BPM RED Academy — HumAI MightHub  
-Human-Centered AI for Decision Legitimacy
+Engineering legitimacy into AI systems.