876 lines
21 KiB
Markdown
876 lines
21 KiB
Markdown
# Project Velocity Master Bibel
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**Status:** Master source of truth
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**Prepared:** 2026-04-12
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**Scope:** Unified synthesis of Project Velocity markdown documentation across product, architecture, infrastructure, operations, iOS, web, AI workflows, and GTM context
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**Exclusions:** Anything under `Sourik` was intentionally excluded from this synthesis
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**Method:** This document normalizes and reconciles the current documentation corpus. It is not a raw concatenation. Where source docs disagree, this bibel favors the latest operational truth and the more concrete implementation artifact.
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---
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## Chapter Index
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1. Charter and Scope
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2. Source Corpus
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3. Product Thesis
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4. Commercial Model
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5. Customer and User Model
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6. Suite Architecture
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7. Core Product Surfaces
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8. Oracle
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9. Sentinel
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10. Dream Weaver and Catalyst
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11. Web Application
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12. iOS Application
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13. Backend and AI Runtime
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14. Data Model and Core Entities
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15. Infrastructure and Deployment Model
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16. Stable Ingress Layer
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17. Linux AWS Control Surface
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18. Operating Flows
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19. Security, Privacy, and Sovereignty
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20. Current Live Truth
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21. Build Priorities and Open Gaps
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22. Runbooks and Team Usage
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23. Source Lineage Map
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---
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## 1. Charter and Scope
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Project Velocity is not one app. It is a private, on-prem or client-controlled real-estate operating system composed of:
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- a premium web interface
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- a native iPad surface
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- an AI CRM and analytics layer
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- a biometric perception and scoring layer
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- a visual generation layer
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- a durable infrastructure and operator layer
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Velocity is designed around an anti-SaaS principle:
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- client data stays with the client
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- deployments can run on-prem or in client-controlled cloud
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- the product is sold as strategic capability, not seat-based software
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This master bibel exists to collapse scattered markdown artifacts into one normalized document the team can use as the primary reference.
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---
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## 2. Source Corpus
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This bibel synthesizes the key Project Velocity markdown sources, including:
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- core bibles:
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- `velocity_technical_bible.md`
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- `velocity_ios_bible.md`
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- `Project Velocity - The Oracle.md`
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- `The Sentinel Bibel.md`
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- `Desineuron Ops Control Plane Bibel.md`
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- infrastructure:
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- `TEAM_HANDOFF_2026-04-08.md`
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- ingress and ops control plane READMEs
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- Comfy and Dream Weaver:
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- `DREAMWEAVER_TECHNICAL_SPEC.md`
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- `A100_DEPLOYMENT_VALIDATION.md`
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- `comfy_engine/scripts/README.md`
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- operational truth docs:
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- `nemoclaw_setup_truth.md`
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- `velocity_status_report.md`
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- `oracle_development_status.md`
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- strategic and customer docs:
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- Kolkata builder intel
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- Customer 0 strategy
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- customer persona notes
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- sprint and user story docs
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Excluded from synthesis:
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- any path containing `Sourik`
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- vendor or dependency markdown such as `node_modules`
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- non-authoritative third-party readmes unless they directly influenced repo behavior
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---
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## 3. Product Thesis
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Velocity is a real-estate sales acceleration platform for high-value property selling environments.
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Its core promise is:
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- compress sales cycles
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- increase intelligence during sales interactions
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- reduce lead leakage
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- preserve data sovereignty
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- give each property or portfolio a private, premium operating stack
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The product is built around a first-principles model:
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- property-specific intelligence matters
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- portfolio intelligence unlocks when multiple properties are active
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- AI should operate the workflow surface, not just answer questions
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- product delivery must be standardized enough to avoid bespoke installation chaos
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Velocity is therefore best understood as a modular operating system, not a single dashboard.
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---
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## 4. Commercial Model
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The business model reflected in the documentation is:
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- initial setup fee
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- monthly maintenance / bleeding-edge upgrade fee
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- inventory-linked or performance-linked downstream value capture
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The product is not sold primarily by seats. The most important commercial unit is the property, with portfolio behavior unlocking when multiple properties are onboarded.
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Working internal segmentation:
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- **Tier 3 / city-channel model**
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- CP or channel-heavy deployment
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- one city per install
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- can cover many builders in that city
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- user count can still be high
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- **Tier 2 / project-builder model**
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- per-project deployment for a builder
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- narrower operational scope
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- property-specific generation and sales workflows
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- **Tier 1 / enterprise portfolio model**
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- multi-property or multi-portfolio controls
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- monitoring and interaction layers across properties
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- governance and deeper integrations
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Commercially, the strongest internal framing is:
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- first property gets full setup
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- second property unlocks portfolio features
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- enterprise control grows with property count and operational complexity
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---
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## 5. Customer and User Model
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### Customer Types
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- developers / builders
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- brokerages and CPs
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- city-channel sales operators
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- enterprise portfolio operators
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### Internal User Types
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- junior broker
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- senior broker
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- sales director
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- marketing operator
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- data steward
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- compliance reviewer
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- platform admin
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- operator / infra admin
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### Team Reality
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The current docs imply two simultaneous realities:
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- product reality for future customers
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- internal Desineuron operating reality used to build, demo, and run the system
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This bibel captures both, but prefers the operational truth when implementation details matter.
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---
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## 6. Suite Architecture
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```mermaid
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flowchart TD
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A[Velocity User Surface] --> B[Web App]
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A --> C[iPad App]
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B --> D[FastAPI Neural Core]
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C --> D
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D --> E[Oracle]
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D --> F[Sentinel]
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D --> G[Inventory]
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D --> H[Dream Weaver / Catalyst]
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E --> I[PostgreSQL]
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F --> I
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G --> I
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D --> J[NemoClaw / Reasoning Layer]
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H --> K[ComfyUI / GPU Workloads]
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L[Linux Control Surface] --> M[AWS GPU Nodes]
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L --> N[S3 Canonical Asset Store]
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O[t4g Stable Ingress] --> B
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O --> C
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O --> L
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O --> M
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```
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Velocity has four major planes:
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- **experience plane**
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- web app
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- iPad app
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- **intelligence plane**
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- Oracle
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- Sentinel
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- NemoClaw
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- Dream Weaver / Catalyst
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- **data plane**
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- PostgreSQL
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- asset storage
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- S3 model store
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- **operations plane**
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- Linux control surface
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- stable ingress
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- AWS GPU workers
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---
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## 7. Core Product Surfaces
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The currently documented product surfaces are:
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- **Dashboard**
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- KPIs, health, activity, sentiment, velocity
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- **Oracle**
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- AI CRM and analytical canvas
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- **Sentinel**
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- biometric and attention-scoring engine
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- **Inventory**
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- unit and property availability tracking
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- **Dream Weaver / Catalyst**
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- visual generation and asset transformation
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- **Settings / operator surfaces**
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- system configuration, connectivity, route control, infra control
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---
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## 8. Oracle
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Oracle is the AI operating surface of Velocity. It is not a simple chatbot.
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### What Oracle Is
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- a prompt-driven CRM intelligence surface
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- a persistent vertical canvas
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- a branchable and mergeable analytical workspace
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- a controlled data access gateway mediated by Nemoclaw and policy
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### Core Oracle Principles
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- natural-language intent becomes typed execution
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- durable page revisions replace ephemeral AI replies
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- collaboration uses forks and merge requests
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- provenance and auditability are mandatory
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- AI planning must remain policy-constrained
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### Oracle Architecture
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```mermaid
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flowchart LR
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A[User Prompt] --> B[Prompt Execution]
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B --> C[NemoClaw Planning]
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C --> D[Policy Validation]
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D --> E[Data Access Gateway]
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E --> F[PostgreSQL / Tenant Data]
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F --> G[Visualization Resolver]
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G --> H[Canvas Component]
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H --> I[Revisioned Oracle Canvas]
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I --> J[Fork / Merge Workflow]
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```
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### Core Oracle Behaviors
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- prompt authoring with context
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- retrieval planning through semantic mapping
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- policy-validated data access
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- component synthesis or template selection
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- append/insert/replace on a vertically scrolling canvas
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- fork and merge semantics for shared work
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### Oracle Truth in Repo
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The repo has:
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- a styled Oracle shell
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- temporary mock-oriented UI behavior
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- placeholder backend Oracle route files
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The repo does not yet have:
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- the full production Oracle runtime mounted and wired end to end
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So Oracle is conceptually mature, but partially implemented.
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---
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## 9. Sentinel
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Sentinel is the biometric, session-intelligence, and attention-scoring engine.
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### Core Principles
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- local-first perception
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- no raw webcam stream to remote backend
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- PostgreSQL as source of truth
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- real-time broker-facing intelligence
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- infrastructure truth over nostalgic planning
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### Sentinel Inputs
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- browser-side facial blendshape data
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- scene timing
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- CRM context
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- asset opens
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- CCTV enrichment
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- auto-mode session evidence
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### Sentinel Outputs
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- QD score
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- lead tags
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- live notifications
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- session intelligence
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- vault-open intelligence
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- auto-mode lead linkage
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### Sentinel Modes
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- **Assigned Mode**
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- tied to existing lead
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- **Auto Mode**
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- no pre-bound lead
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- CCTV and session evidence reconcile later
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### Sentinel Flow
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```mermaid
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flowchart TD
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A[Browser Webcam + MediaPipe] --> B[Biometric Packets]
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B --> C[/api/sentinel/ws/perception]
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C --> D[Scene Lookup]
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D --> E[NemoClaw Scoring]
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E --> F[perception_sessions]
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E --> G[omnichannel_logs]
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E --> H[Live QD Broadcast]
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I[CCTV OCR/Event] --> J[/api/cctv/event]
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J --> K[Auto Mode Matcher]
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K --> L[Lead Link or Lead Create]
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```
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### Active Truth
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The docs are explicit that:
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- NVIDIA-hosted completions are the active primary path
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- Ollama/OpenShell exist but are not the production-first scoring path
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That distinction should remain explicit in team communication.
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---
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## 10. Dream Weaver and Catalyst
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Dream Weaver is the structural-preservation visual restyling system. Catalyst is the broader generation and asset automation layer.
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### Dream Weaver Objective
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Restyle interiors while preserving:
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- geometry
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- window placement
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- vanishing points
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- architectural truth
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### Technical Strategy
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- RealVisXL V5.0 Lightning as core model family in the historical design docs
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- stacked ControlNet approach
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- depth + line preservation
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- SAM-based masking
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- workflow portability through ComfyUI API JSON
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### Operational Direction
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The later infra work also shows Qwen-based image edit/generation workflows entering the stack. So the project now contains two overlapping visual-generation realities:
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- Dream Weaver spec centered on SDXL / RealVisXL / ControlNet / SAM
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- operational AWS generation work centered on Qwen image models and ComfyUI / GPU orchestration
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These should be treated as parallel capabilities, not contradictions.
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### Dream Weaver Pipeline
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```mermaid
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flowchart LR
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A[Reference / Room Image] --> B[Preprocess]
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B --> C[M-LSD]
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B --> D[Depth]
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B --> E[SAM / Masking]
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C --> F[Control Stack]
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D --> F
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E --> F
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F --> G[Sampler / Restyler]
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G --> H[Styled Output]
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H --> I[API / iPad / Batch Workflow]
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```
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### Operational Purpose
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- interior restyling
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- marketing posters
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- cinematic video
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- mobile-triggered asset generation
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- broker-facing wow factor
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---
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## 11. Web Application
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The web app is a React + TypeScript + Vite application.
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### Frontend Stack
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- React 19
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- TypeScript
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- Vite
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- Zustand
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- Tailwind CSS
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- shadcn/ui
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- Radix UI
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- Framer Motion
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- Recharts
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- React Hook Form
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- Zod
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### Core Web Modules
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- Dashboard
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- Oracle
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- Sentinel
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- Inventory
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- Settings
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### State Model
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The docs describe Zustand-backed state slices for:
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- auth
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- navigation
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- Oracle
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- Sentinel
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- Dashboard
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- Inventory
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- system state
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### Current Truth
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The web app appears stronger as a polished shell than as a fully integrated production data surface. It carries much of the premium experience language and component structure the rest of the system is meant to converge toward.
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---
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## 12. iOS Application
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Velocity iOS is the native mobile counterpart for Apple devices, especially the showroom iPad surface.
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### iOS Stack
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- Swift
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- SwiftUI
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- Combine / Observation
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- Alamofire for networking
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- native animation and glassmorphism
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### iOS Modules
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- Dashboard
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- Oracle
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- Sentinel
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- Inventory
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- Settings
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### Strategic Role
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The iPad app is not just a companion. It is central to the product’s premium physical-sales-gallery positioning.
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Important documented capabilities:
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- portable sales intelligence
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- native presentation surface
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- AI generation triggering
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- AR sun-path overlay
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- inventory and lead interaction on the floor
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### Design Direction
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- native fluidity
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- battery efficiency
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- premium dark/glass aesthetic
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- parity with web where needed, but not web-in-a-wrapper
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---
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## 13. Backend and AI Runtime
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The backend is a FastAPI neural core with PostgreSQL, auth, websockets, and AI orchestration.
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### Key Responsibilities
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- API routing
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- auth and RBAC
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- CRM and lead operations
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- Sentinel perception processing
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- Oracle execution path
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- websockets and notifications
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- video and scene catalog access
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- NemoClaw integration
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### NemoClaw Role
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NemoClaw is the reasoning layer used across:
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- lead tagging
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- CCTV profiling
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- QD scoring
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- future Oracle planning and data access interpretation
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### Prompt Truth in Repo
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The repo contains explicit prompt artifacts for:
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- `cctv_profiler`
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- `lead_tagger`
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- `qd_calculator`
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These are concrete prompt contracts, not vague intentions. They should be treated as product logic.
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### Runtime Reality
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The system documentation repeatedly shows a hybrid runtime model:
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- hosted NVIDIA-compatible reasoning path as primary
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- private / local alternatives possible
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- runtime abstraction should outlive vendor choice
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---
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## 14. Data Model and Core Entities
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The major persistent entities reflected across the docs are:
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- users and roles
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- leads and lead intelligence
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- inventory and project data
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- perception sessions
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- CCTV events
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- vault assets and opens
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- omnichannel logs
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- page revisions and canvas components
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- model catalog and hydration state
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- machine sessions and cost records
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### Persistent Truth
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PostgreSQL is the primary source of truth for operational data.
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S3 is becoming the canonical store for large model and asset artifacts.
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AWS GPU NVMe is treated as fast ephemeral runtime cache, not authoritative storage.
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---
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## 15. Infrastructure and Deployment Model
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Project Velocity now has a clear split between:
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- **stable control surfaces**
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- **ephemeral compute workers**
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- **canonical storage**
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### Current Deployment Pattern
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- Linux box:
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- long-lived control surface
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- private origin services
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- operator tooling
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- AWS t4g ingress:
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- stable public edge
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- route manager
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- AWS GPU instances:
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- disposable compute nodes
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- ComfyUI and model workloads
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- S3:
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- canonical model / workflow / asset store
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### Architectural Principle
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This is not “one giant computer.”
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It is:
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- one control plane
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- one ingress plane
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- one durable asset plane
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- many disposable compute workers
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That is the correct model.
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---
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## 16. Stable Ingress Layer
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The stable ingress layer is the permanent public front door.
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### Purpose
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- stable public IP
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- DNS target for public routes
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- TLS termination
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- hostname-based routing
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- forwarding to Linux or AWS backends
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### Current Public Surfaces
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||
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The handoff documents establish these public hostnames as part of the route model:
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- `office.desineuron.in`
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- `git.desineuron.in`
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- `cloud.desineuron.in`
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- `projects.desineuron.in`
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- `talk.desineuron.in`
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- `vpn.desineuron.in`
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- `comfy.desineuron.in`
|
||
- `ops.desineuron.in`
|
||
|
||
### Key Design Principle
|
||
|
||
Backends may change. Public identity should not.
|
||
|
||
That is why:
|
||
|
||
- GPU workers should not own the stable Elastic IP
|
||
- the ingress box should stay alive and route based on managed config
|
||
|
||
---
|
||
|
||
## 17. Linux AWS Control Surface
|
||
|
||
The Linux box is now the operational control surface for AWS.
|
||
|
||
### Responsibilities
|
||
|
||
- machine lifecycle management
|
||
- preferred instance selection
|
||
- spot/on-demand visibility
|
||
- session and cost tracking
|
||
- route management through ingress
|
||
- model ingest and hydration orchestration
|
||
- operator UI and CLI
|
||
|
||
### Canonical Asset Strategy
|
||
|
||
The documentation evolution shows a strong convergence:
|
||
|
||
- Linux can store local copies
|
||
- but S3 should be the canonical large-model source for ephemeral AWS hydration
|
||
|
||
That is the right direction because S3 is:
|
||
|
||
- durable
|
||
- AWS-native
|
||
- fast to hydrate with `s5cmd`
|
||
- not dependent on home network conditions
|
||
|
||
### Control Plane Flow
|
||
|
||
```mermaid
|
||
flowchart TD
|
||
A[Operator UI / CLI on Linux] --> B[Launch AWS Worker]
|
||
B --> C[Worker Bootstrap]
|
||
C --> D[Hydrate from S3]
|
||
D --> E[Verify Manifest]
|
||
E --> F[Start Workload]
|
||
F --> G[Map Route Through Ingress]
|
||
G --> H[Track Runtime / Cost / Logs]
|
||
```
|
||
|
||
---
|
||
|
||
## 18. Operating Flows
|
||
|
||
### Lead Intelligence Flow
|
||
|
||
- lead enters through channel
|
||
- Oracle / backend receives it
|
||
- tagging and enrichment happen
|
||
- lead lands in CRM operating surface
|
||
|
||
### Sentinel Session Flow
|
||
|
||
- broker runs session
|
||
- MediaPipe emits perception packets
|
||
- backend computes QD and updates lead/session state
|
||
- notifications stream back in real time
|
||
|
||
### Dream Weaver / Comfy Flow
|
||
|
||
- operator or app triggers generation
|
||
- GPU worker receives workflow
|
||
- model hydrates if missing
|
||
- ComfyUI or pipeline runs
|
||
- output is returned or archived
|
||
|
||
### Infra Control Flow
|
||
|
||
- operator selects profile
|
||
- Linux control surface launches worker
|
||
- route gets mapped through ingress
|
||
- workload is exposed without changing public identity
|
||
|
||
---
|
||
|
||
## 19. Security, Privacy, and Sovereignty
|
||
|
||
Project Velocity’s strongest recurring architectural doctrine is data sovereignty.
|
||
|
||
### Security Principles
|
||
|
||
- client data belongs to client
|
||
- on-prem or client-controlled cloud must be supported
|
||
- zero-trust between services
|
||
- least privilege for machine roles
|
||
- no hidden production dependencies on developer laptops
|
||
- auditability matters for both operations and business decisions
|
||
|
||
### Privacy Positioning
|
||
|
||
Velocity is explicitly positioned as anti-SaaS in the strategic docs.
|
||
|
||
That means product delivery should support:
|
||
|
||
- on-prem deployment
|
||
- client-owned cloud
|
||
- local or sovereign runtime options
|
||
- explicit consent and audit around biometric flows
|
||
|
||
This is not just a compliance detail. It is a core selling argument.
|
||
|
||
---
|
||
|
||
## 20. Current Live Truth
|
||
|
||
Based on the most recent infrastructure handoff and operational truth docs, the current live picture is:
|
||
|
||
- stable ingress is running on AWS `t4g.micro`
|
||
- Linux box is the long-lived origin and control surface
|
||
- ComfyUI is exposed through managed ingress routing
|
||
- auto-heal exists for:
|
||
- home IP sync
|
||
- Comfy route sync
|
||
- ops control plane is live on Linux
|
||
- S3 is in place as the canonical control-plane bucket
|
||
|
||
Important operational truths that should not be lost:
|
||
|
||
- GPU nodes are ephemeral and should be treated that way
|
||
- route management should be dynamic, not hardcoded
|
||
- NVMe is for speed, not truth
|
||
- Linux and S3 together are the operational backbone
|
||
|
||
---
|
||
|
||
## 21. Build Priorities and Open Gaps
|
||
|
||
The documentation implies this priority order:
|
||
|
||
1. stabilize control plane and ingress
|
||
2. stabilize model hydration and GPU orchestration
|
||
3. finish Oracle backend/runtime implementation
|
||
4. continue iOS and web convergence
|
||
5. standardize packaging for on-prem delivery
|
||
|
||
### Open Gaps
|
||
|
||
- Oracle production runtime is not fully wired yet
|
||
- several frontend surfaces still rely on mock or transitional behavior
|
||
- deployment packaging for customer installs is not yet standardized enough
|
||
- multi-property / portfolio product packaging needs formalization in product artifacts
|
||
- some business docs are strong on thesis but still need conversion into installable product contracts
|
||
|
||
---
|
||
|
||
## 22. Runbooks and Team Usage
|
||
|
||
### What the team should point to for truth
|
||
|
||
- **this master bibel** for unified product and architecture truth
|
||
- **ingress handoff** for current infra routing truth
|
||
- **ops control plane bibel** for operator workflows
|
||
|
||
### When a new service is added
|
||
|
||
The team should define:
|
||
|
||
- what plane it belongs to
|
||
- whether it is stable or ephemeral
|
||
- where its truth is stored
|
||
- how it is routed publicly
|
||
- which system owns its startup, health, and recovery
|
||
|
||
### Operational Rule
|
||
|
||
If a workflow depends on a developer’s Windows laptop staying alive, it is not production-ready.
|
||
|
||
---
|
||
|
||
## 23. Source Lineage Map
|
||
|
||
This master bibel draws primarily from these source families:
|
||
|
||
### Product and architecture
|
||
|
||
- `Project Velocity - The Oracle.md`
|
||
- `The Sentinel Bibel.md`
|
||
- `velocity_technical_bible.md`
|
||
- `velocity_ios_bible.md`
|
||
- `oracle_development_status.md`
|
||
|
||
### Visual generation
|
||
|
||
- `DREAMWEAVER_TECHNICAL_SPEC.md`
|
||
- `A100_DEPLOYMENT_VALIDATION.md`
|
||
- `comfy_engine/scripts/README.md`
|
||
- `Project Velocity_ Dream Weaver.md`
|
||
|
||
### Infra and operations
|
||
|
||
- `TEAM_HANDOFF_2026-04-08.md`
|
||
- `Desineuron Ops Control Plane Bibel.md`
|
||
- `nemoclaw_setup_truth.md`
|
||
- `infrastructure_deployment_manifest.md`
|
||
- ingress and ops READMEs
|
||
|
||
### Business and GTM context
|
||
|
||
- `Velocity Kolkata Customer 0 Strategy - Get My Ghar.md`
|
||
- `Kolkata Builder Intel and Meeting Map - April 2026.md`
|
||
- `Customer Personas for Abu Dhabi and Dubai...md`
|
||
- sprint user story docs
|
||
|
||
### Prompt and AI behavior contracts
|
||
|
||
- `backend/nemoclaw_prompts/*.md`
|
||
|
||
---
|
||
|
||
## Final Position
|
||
|
||
Project Velocity is best understood as a sovereign, modular real-estate operating system with:
|
||
|
||
- premium user surfaces
|
||
- AI-driven CRM and perception intelligence
|
||
- property-linked generation workflows
|
||
- a private operational backbone
|
||
- a route-stable ingress layer
|
||
- a Linux-hosted control plane
|
||
- S3-backed canonical model and asset strategy
|
||
|
||
That is the coherent architecture the scattered docs were already converging toward.
|