1. Executive Summary

The internet was built for browsing; it was not natively architected for buying. Today's "E-Commerce" is a patchwork of friction-heavy interfaces requiring human manual input. We are witnessing a paradigm shift toward i-Commerce (Intelligent Commerce), where AI Agents—not humans—discover, negotiate, and transact value.

flexi.now is the B2B infrastructure layer that enables this shift. By harmonizing Google’s Universal Commerce Protocol (UCP) and OpenAI’s Agentic Commerce Protocol (ACP), we provide the "rails" for autonomous negotiation across any industry—from HR datasets to automotive inventory.

Crucially, flexi.now solves the "adoption gap" by integrating with KREA.Digital’s enterprise-grade retention engine. We use Google BigQuery as a real-time logic processor to autonomously recover failed agent negotiations via human channels (SMS/Email/Push).

2. The Problem: The "Friction Tax"

Current commerce relies on synchronous human presence. If a human isn't looking at the screen, the deal stops. This creates a "Friction Tax" on the global economy.

2.1 The Data Gap

• E-Commerce (Old): Reactive. Logs are stored but rarely activated in real-time.
• Agent Commerce (New): Fast, but brittle. If an agent hits an error, the transaction usually dies.

3. The Solution: flexi.now Architecture

flexi.now is not a marketplace; it is a Protocol Switch. It translates inventory data into agent-readable formats and manages the negotiation lifecycle.

3.1 The System Flow

The architecture leverages a "Hybrid Intelligence" model. High-speed negotiations happen in the Agent Layer; logic and retention happen in the Data Layer.

3.2 Technical Stack

• Compute: Google Cloud Run (Serverless Agent scaling).
• Database: Google BigQuery (Data Warehouse & Logic Engine).
• Protocol: JSON-LD structure compliant with UCP.
• Retention: KREA.Digital Omnichannel API.

4. Google Integration: "Autonomous Logic"

This is the core innovation justifying the Google Cloud partnership. We do not use BigQuery merely for storage; we use it for Active Logic.

4.1 The Loop

1. Ingest: flexi.now streams 100M+ daily negotiation logs into BigQuery.
2. Analyze: Scheduled SQL queries run every minute to identify specific patterns (e.g., "Negotiation stalled > $500").
3. Act: Results are pushed as JSON payloads to KREA.Digital.
4. Recover: KREA triggers the appropriate channel (SMS/Push) to bring the human back into the loop.

5. Market Analysis: The 9-Point Grid

flexi.now is industry-agnostic. Our Total Addressable Market (TAM) includes all digital and physical exchange.

6. SWOT Analysis

STRENGTHS (Internal)	WEAKNESSES (Internal)
• Proven Scale: 100M+ daily events. • Hybrid Infra: 99.9% uptime. • Data Loop: Proprietary SQL-to-Action engine.	• UCP Dependency: Relies on Google standard adoption. • Compute Cost: High GPU requirement for agents.
OPPORTUNITIES (External)	THREATS (External)
• Google Alignment: Fits "Agentic Web" vision. • First Mover: Only infra with Retention built-in. • Data Monetization: Prediction markets.	• Walled Gardens: Closed proprietary protocols (Apple/Amazon). • Regulation: AI liability laws.

7. Strategic Roadmap

Seeking Seed investment to transition prototype to global standard.

Phase 1: Infrastructure Migration (Months 1-3)
Migrating the KREA event stream (100M logs/day) to Google BigQuery.

Phase 2: The Logic Engine (Months 4-6)
Building the "Natural Language Rules" interface using Vertex AI.

Phase 3: Global Pilot (Months 7-12)
Launching "Universal Inventory" pilot with Auto/Real Estate partners. Goal: 1M autonomous transactions.