SecantX AI White Paper
The Operating System for Spatial Agentic Finance
Version 1.0 • November 2025
Executive Summary
Market intelligence is spatially distributed across multiple disconnected sources: exchange feeds, social sentiment, on-chain analytics, news aggregators, and proprietary indicators scatter across numerous platforms and screens. Traders manually integrate this distributed information, creating cognitive bottlenecks that lead to missed opportunities and suboptimal execution.
Current AI cannot solve this. Language models excel at text but remain disconnected from visual reality. They cannot see your TradingView setup, parse chart geometry from visual data, or understand the spatial relationships between price action and volume profiles. They lack spatial intelligence: the ability to perceive, reason about, and act within visual trading environments.
SecantX AI delivers spatial intelligence for finance. We aggregate distributed market data through vision-based scene understanding, process what traders actually see across their entire workspace, and generate actionable insights grounded in visual context. Our AI overlays any trading platform, watching your charts in real time and connecting information flows that traditionally require manual integration.
The platform operates through SECA, an ERC-20 utility token on Base with aggressive deflationary burns. Usage consumes credits, permanently destroying 95-98% of tokens and creating scarcity value as adoption grows. Beyond the desktop overlay launching today, we are building the infrastructure layer for agentic finance: APIs that enable developers to create trading agents with genuine spatial perception, not just text processing.
SecantX AI is not a better trading app. It is the operating system for spatial agentic finance, a foundational platform architected to power the next generation of financial tools.
Key Highlights
Total Supply: 1,000,000,000 SECA
Network: Base (Ethereum L2)
Revenue Model: Usage-based credits
Status: Phase 0 Live
Mechanism: Deflationary burn model
Vision: OS for Agentic Finance
Market Opportunity
Spatial intelligence is emerging as AI's next frontier. Fei-Fei Li's pioneering research positions it as the evolution beyond language models: AI that understands visual, spatial environments and the relationships within them.
The spatial computing market reached $20-168 billion in 2025, projected to $448-898 billion by 2032. Simultaneously, AI in financial services is growing from $38 billion (2024) to $190 billion by 2030 at 30.6% CAGR.
SecantX AI operates at the convergence of these markets. Finance uniquely demands spatial intelligence: traders process information distributed across multiple disconnected sources, numerous screens, and visual interfaces that language models cannot understand. Applying spatial AI to this problem creates a defensible category where no dominant platform exists.
Why Spatial Intelligence
Spatial intelligence solves this through virtual agglomeration. Rather than forcing traders to visit each data location sequentially, SecantX AI aggregates distributed intelligence into unified spatial context. The system sees across your entire workspace, connects information flows that traditionally require manual linking, and presents synthesized insights within the visual environment where decisions actually happen.
This mirrors how spatial intelligence emerged as foundational to human cognition. Watson and Crick discovered DNA structure by physically manipulating spatial molecular models. Traders similarly succeed through pattern recognition across distributed sources, identifying correlations between price action, volume distribution, social sentiment, and on-chain flows. Current AI cannot help because it lacks visual grounding in how these sources spatially relate within actual trading workflows.
Problem Statement
The Cognitive Violence of Modern Trading
Human brains are spatial processing machines, evolved over millions of years to navigate three-dimensional environments. Yet modern trading tools force linear thinking onto inherently spatial problems:
High Cognitive Load
Traders must mentally juggle disconnected data points across multiple screens. Price action, news feeds, on-chain metrics, and order flow exist in separate silos.
Constant Context Switching
Every alt+tab between chart, news site, and order book destroys flow state. Switching costs accumulate, leading to decision fatigue.
Steep Learning Curve
Beginners face interfaces designed for machines, not humans. Technical indicators require hours of study to understand. Pattern recognition skills take years to develop.
Inefficient Pattern Recognition
Even experienced traders are slowed by manual correlation. Three-dimensional market dynamics are compressed into flat visualizations.
The Fragmentation Problem
Modern traders cobble together TradingView for charts, Discord/Twitter for sentiment, Dune Analytics for on-chain data, and CEX/DEX interfaces for execution. Multiple browser tabs, each a context-switching penalty.
This fragmentation is not just inconvenient; it is dangerous. In volatile markets, the seconds lost switching contexts can mean the difference between profit and loss.
The SecantX AI Solution
SecantX AI is an agentic spatial AI that fundamentally reimagines how traders interact with financial data. Our approach is built on three core pillars:
Layered Visual Design
Our "Liquid" UI uses depth cues, translucency, and layering to present data the way your brain naturally processes it:
- Base Layer: Primary data and charts at the foundation
- Middle Layer: Semi-transparent overlays for contextual information
- Top Layer: Focused analysis and controls that float above
Immersive Context
Instead of forcing you to hunt for information, SecantX AI brings it to you:
- News and social sentiment appear as floating glass panels when relevant
- On-chain metrics surface automatically during unusual activity
- Order flow visualization integrates seamlessly with price action
- AI sees your screen and understands what you're analyzing
Natural Interaction
SecantX AI is multimodal, adapting to how you naturally work:
Look
Point the AI at any chart; it sees what you see
Speak
Issue voice commands while watching price action
Type
Use text for precision when needed
Education Mode
Point the AI at any chart and ask, "What do you see?" It provides real-time pattern recognition, indicator explanation, and plain-language analysis. Learn by seeing, not by reading manuals.
Trade Mode
Execute trades through voice or text commands. Non-custodial execution integrating with multiple trading platforms. Direct on-chain swaps without custody handoff. MEV-aware routing for optimal execution.
Technology Architecture
SecantX AI is built spatial-first in preparation for the next era of computing.
Liquid UI
Custom Web Components built with Lit. Three-tier material hierarchy inspired by Apple's spatial design guidelines. Responsive across desktop, mobile, and future XR platforms.
Spatial Scene Understanding
SecantX AI implements vision-based intelligence through workspace-level perception. The system processes entire trading environments, not isolated visual data. Multi-monitor setups, overlapping windows, and scattered data sources become unified spatial context.
Region of Interest (ROI) Detection: Automatic identification of charts, indicators, order books, and news feeds across your workspace. Spatial relationship mapping connects distributed information that traditionally requires manual integration.
OCR-Free Data Extraction: OHLCV parsing from any charting platform through visual geometry recognition. Candlestick patterns, volume distributions, and indicator signals extracted without platform APIs or text recognition.
Distributed Source Aggregation: Multiple data sources (on-chain metrics, social sentiment, exchange feeds, news) processed as unified spatial network. The system learns correlations between spatially distributed signals that human traders manually track.
Non-Custodial Trading
Multi-platform trading integration. MEV-aware, optimized swaps. Cross-venue routing with gas optimization and slippage minimization.
Spatial Perception Engine APIs
Scene API (Perception-as-a-Service), Signals API (Reasoning-as-a-Service), Execution API (Action-as-a-Service), and Receipts API (Observability-as-a-Service) for third-party developers.
Business Model
SecantX AI generates revenue through a credits-based system with three distinct customer segments and credit types.
App Credits (Traders)
Individual traders seeking spatial AI assistance for analyses, pattern scans, Education Mode learning, and Trade Mode execution.
Monetization:
- Freemium tier with limited credits
- Usage-based pricing
- Tiered subscription plans
Value Proposition:
- Reduce cognitive load
- Accelerate learning curve
- Trade without leaving your chart
Partner & API Credits (Builders)
Developers building financial applications using Scene API, Signals API, and Execution & Receipts APIs to embed visual understanding and intelligent execution.
Monetization:
- Usage-based API pricing
- Volume discounts
- Enterprise plans with SLAs
Value Proposition:
- Skip years of infrastructure work
- Focus on product differentiation
- Best-in-class perception engine
Ecosystem Credits (Marketplace)
Third-party agent developers and strategy providers who list custom agents, access analytics, and earn revenue share from user consumption.
Monetization:
- Listing fees for premium placement
- Protocol revenue share
- Data access fees
Value Proposition:
- Distribution to SecantX users
- Monetize trading strategies
- Leverage SecantX APIs
Token Economics
The SECA token is the native utility token of the SecantX AI ecosystem, designed to align incentives across traders, developers, and the platform.
Token Specifications
Name: SecantX AI
Ticker: $SECA
Network: Base (L2)
Standard: ERC-20
Supply: 1B SECA
Decimals: 18
Token Utility
Platform Access
Purchase credits for AI interactions and trade executions
Fee Discounts
Tiered discounts based on holdings
Priority Access
Early access to features, models, and betas
Builder Access
API payments and volume-based discounts
Future Governance
Vote on features, treasury, and strategy
For complete tokenomics modeling and projections
View Full Tokenomics SpreadsheetDeflationary Burn Mechanism
Users purchase credits with SECA tokens. Credits are consumed during AI interactions, API calls, and trades. 95-98% of tokens are automatically burned, permanently removing them from circulation. The burn rate adjusts dynamically based on liquidity depth to ensure protocol sustainability.
LP > $15M
98% burn
LP $10-15M
95% burn
LP $5-10M
90% burn
LP < $5M
75% burn
Economic Alignment: Platform growth drives increased usage, which drives more burns. By month 18, net circulating supply peaks at 393M tokens, then decreases to 329M by month 36 despite ongoing unlocks—demonstrating true deflationary pressure.
Product Roadmap
SecantX AI's development progresses through five distinct phases, evolving from a spatial overlay to a foundational platform powering agentic finance.
Phase 0: Agentic Overlay
- Spatial desktop app floating above any trading platform
- Vision-based scene understanding with chart analysis
- $SECA token deployed on Base with DEX liquidity
- Deflationary credit system with automatic burns
Phase 1: Perception Engine
- Visual coaching with real-time pattern recognition
- Advanced scene understanding and OHLCV extraction
- Always-on background monitoring of markets and news
- Multi-timeframe analysis and correlation detection
Phase 2: Execution Fabric
- Non-custodial trade execution via multi-platform integration
- Smart routing with cross-venue price comparison
- AI-generated trade signals with risk scoring
- MEV-aware execution with front-running protection
- Execution fees paid in SECA and automatically burned
Phase 3: Agentic World Model
- Public Perception API for scene understanding
- Public Reasoning API for signals generation
- Public Execution API for non-custodial trades
- Full developer platform with SDKs, docs, and sandbox
Beyond: The OS for Finance
- Multi-client support (desktop, mobile, web, XR)
- Protocol ecosystem with agent marketplace and strategy sharing
- $SECA as universal API gas for all platform interactions
- Network effects drive exponential usage and burns
Go-to-Market Strategy
Phase 0-1: Early Adopters
Target
Crypto-native traders, technical analysts, education-focused learners
Channels
Crypto Twitter/Discord, trading education partnerships, strategic airdrops
Metrics
DAU, credits consumed, retention rates
Phase 2: Execution-Ready Traders
Target
Active traders, DeFi power users, TradingView users
Channels
Platform integrations, influencer partnerships, performance-based marketing
Metrics
Trade volume, execution quality, SECA burn rate
Phase 3-4: Developer Ecosystem
Target
FinTech startups, DeFi protocols, TradFi firms
Channels
Hackathons, developer grants, enterprise partnerships
Metrics
Third-party integrations, API volume, ecosystem revenue
Security & Governance
Smart Contract Security
Pre-launch audits by reputable firms, continuous monitoring, bug bounty programs, and timelock mechanisms. SecantX never holds user funds—all trades execute through user-signed transactions.
Governance Model
Phase 1: Core team governance with multi-sig Safe wallet for treasury management. LP tokens locked for 24 months.
Phase 2: Transition to SECA token-based community governance for feature prioritization, treasury allocation, and strategic partnerships.
Data Privacy
Visual data processed locally when possible. Cloud processing encrypted end-to-end. No personally identifiable information stored without consent. GDPR compliant.
Risk Factors
Technical Risks
- AI model performance on unconventional layouts
- MEV attacks and on-chain execution failures
- Mitigation: Extensive training data, building on Base infrastructure
Market Risks
- Token price volatility
- Regulatory uncertainty around AI-assisted trading
- Mitigation: Strong utility, deflationary burns, legal counsel
Adoption Risks
- User resistance to spatial UI paradigms
- Competition from established platforms
- Mitigation: Freemium model, first-mover advantage, API moat
Conclusion
The future of trading is not incremental improvements to existing tools. It is fundamentally different infrastructure that understands how markets actually work: as distributed information networks requiring intelligent aggregation, not manual reconstruction.
SecantX AI delivers this infrastructure today. We combine vision-based workspace perception with intelligent execution, creating a platform where traders stop fighting their tools and start making better decisions.
The SECA token aligns incentives through aggressive deflationary burns. As usage grows, circulating supply shrinks, creating scarcity value that compounds with adoption. By month 36, burns outpace unlocks despite ongoing vesting.
From the desktop overlay launching today to the API ecosystem of tomorrow, SecantX AI provides the foundational layer for agentic finance. We are building infrastructure, not applications—spatial-first, agent-ready, and architected for the next decade of markets.
Disclaimer
This white paper is for informational purposes only and does not constitute an offer to sell or a solicitation of an offer to buy any securities or financial instruments. The SECA token is a utility token intended solely for use within the SecantX AI ecosystem.
Participation in token sales and cryptocurrency investments involves substantial risk, including the potential loss of all invested capital. Prospective participants should carefully consider the risks outlined in this document and conduct their own due diligence before making any investment decisions.
The forward-looking statements in this white paper, including the roadmap, projections, and business plans, are subject to change and should not be relied upon as guarantees of future performance. SecantX AI makes no representations or warranties regarding the accuracy or completeness of the information contained herein.
Further Reading
This whitepaper builds on emerging research in spatial intelligence, multimodal AI, and distributed data processing. For readers interested in the foundational concepts:
Spatial Intelligence and World Models
Fei-Fei Li's research on spatial intelligence as the next frontier beyond language models. From Words to Worlds: Spatial Intelligence
AI and Spatial Economic Distribution
Research on how AI processes spatially distributed data sources and creates network effects. arXiv:2507.19911v2
Multimodal Agent Learning
Technical foundations for agents that learn through embodied interaction with environments. arXiv:2402.05929v2
Cognitive Load in Complex Environments
Research on information processing and decision-making under cognitive constraints. Taylor & Francis: Cognitive Load Research
Spatial Computing Market Research
Market analysis and projections for spatial computing and spatial intelligence technologies. Spatial Computing Market Report
AI in Financial Services Market Research
Market sizing and growth analysis for artificial intelligence applications in financial services. AI in Finance Market Analysis
SecantX AI applies these spatial intelligence principles specifically to financial markets and trading workflows. References provided for educational purposes.
For more information, visit secantx.ai
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