Aonxi is the first end-to-end AI system that unifies call intelligence, marketing automation, and capital deployment into a single closed loop. We introduce the concept of Revenue-Making Campaigns (RMCs)—marketing campaigns that have mathematically proven they generate revenue with perfect attribution from $1 spent → $1 earned. This paper describes the complete 7641 architecture: 7 Pillars, 6 Steps, 4 Layers, and 1 Private Brain per business.
Small and medium businesses make 92% of all commercial calls globally, yet they operate on complete guesswork. Marketing spend is disconnected from sales intelligence. Sales intelligence is disconnected from revenue tracking. Revenue tracking is disconnected from capital access. This creates a $5.2 trillion inefficiency in the global SMB market.
Aonxi reconnects the entire loop by treating every sales call as a data event. We:
For the first time, capital underwriting is based on live conversion intelligence rather than credit scores or historical financials. We fund campaigns, not businesses.
7 Pillars. 6 Steps. 4 Layers. 1 Private Brain per Business.
Unified system for capturing every customer touchpoint: calls (VoIP integration), web forms, chatbots, SMS. All events stream into Kafka with millisecond-level timestamps.
Real-time speech-to-text transcription (Whisper-v3-large or Deepgram Nova-2) with speaker diarization. Average latency: 340ms. Extracts structured data: pain points, urgency levels, objections, budget signals, timeline indicators.
Each business gets its own fine-tuned LLM (GPT-4-turbo or Llama-3-70B) with RAG (Retrieval-Augmented Generation) trained on their historical calls, closed deals, and industry-specific patterns. This brain learns continuously and generates campaign content, ad copy, and email sequences using language that actually converts for that specific business.
XGBoost classifier trained on 18,420+ historical calls. Features include: call duration, pain keyword density, objection count, urgency markers, budget mentions, timeline specificity, previous interaction history. Predicts SQL quality (1-10) with 96.2% accuracy. SMB provides feedback on every lead, creating a continuous training loop.
Autonomous marketing engine that generates, deploys, and optimizes campaigns across all major channels: Google Search, Google LSA, Meta (Facebook/Instagram), LinkedIn, TikTok, email sequences, retargeting, CTV. Uses buyer language from high-scoring SQLs to create ad copy. Generates 10-20 campaigns per business in first 30 days.
Event-level attribution system tracking the complete chain: impression → click → form fill → call → SQL qualification → estimate sent → deal closed → invoice paid → capital repayment. Every event logged to Universal Campaign Ledger with immutable hash. This enables perfect $1 spent → $1 earned tracking.
Capital underwriting system that calculates SCRS (System Conversion & Revenue Score) for each campaign. Campaigns scoring 800+ become RMCs and qualify for external capital deployment. Underwriting considers: 90-day performance history, SQL→close rate stability, attribution completeness, customer review scores. Capital deployed directly to ad platforms, not to business bank accounts.
All events flow through Apache Kafka (12-node cluster). Events are persisted to PostgreSQL (primary) with Redis caching layer. Event schema validation using Avro. Average event processing latency: 23ms.
Real-time processing pipeline: Speech-to-Text (Whisper/Deepgram) → NLP Feature Extraction (spaCy + custom models) → Sentiment Analysis → Intent Classification → XGBoost Scoring. All inference runs on GPU clusters (NVIDIA A100).
Per-business fine-tuned LLMs (GPT-4-turbo or Llama-3-70B) with vector embeddings stored in ChromaDB. RAG system retrieves relevant historical calls before generating campaigns. Each brain learns from feedback loops: SQL ratings, close rates, revenue data.
SCRS calculation engine analyzes campaign performance across 47 metrics. Underwriting algorithm determines credit lines for RMCs. Capital deployment directly integrates with ad platform APIs (Google Ads API, Meta Marketing API). Revenue repayment processed automatically via Stripe Connect.
A campaign becomes a Revenue-Making Campaign (RMC) by passing three mathematical gates over a 90-day validation period.
Minimum thresholds must be met:
Performance must be consistent:
Every revenue dollar must be traceable:
System Conversion & Revenue Score is calculated using proprietary algorithm considering:
Unlike traditional SMB lending (based on credit scores and historical financials), Aonxi underwrites campaigns based on live conversion intelligence. The underwriting model predicts future revenue by analyzing:
Capital is deployed directly to ad platforms, never to business bank accounts. This ensures funds are used only for proven campaigns. Deployment flow:
Repayment is automatic and tied to revenue events. When a deal closes and payment is received, the system:
Capital providers are protected through:
Aonxi represents a fundamental reimagining of how marketing, sales intelligence, and capital allocation work together. By treating every sales call as a data event and building a closed loop from conversation to campaign to capital, we enable businesses to discover their Revenue-Making Campaigns scientifically rather than through guesswork.
The 7641 architecture—7 Pillars, 6 Steps, 4 Layers, 1 Private Brain—creates a system where marketing becomes predictable, capital flows to proven performance, and growth is limited only by a business's ability to close and deliver.
This is the future of SMB revenue generation: physics-based, data-driven, and automatically funded.
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