Disclaimer: I used AI for rephrasing complex concepts and area where I had no clue of what was the standards
1. Applicant & Project Overview
Project Name: Signal-Finder
Team / Individual Name(s): Maxime Blanc (solo community builder)
Links:
Website: https://signal-finder.intuition.box/
GitHub: https://github.com/intuition-box/signal-finder
100-Word Summary: Signal-Finder is an InfoFi dashboard that helps investors discover and economically engage with signals (atoms/triples) on Intuition by staking $TRUST tokens. Features three investment lenses: Heavyweight (safe, institutional signals), Trending (narrative/hype signals), and Emerging (fresh, early-stage insights). Users can uses different metrics: capital commitment, community participation, and later by reputation. Planned automation will enable AI agents to execute investment strategies and collaborate on shared goals through MCP integration. A live activity feed shows real-time signal creation for instant $TRUST allocation decisions.
Project Category: InfoFi / Knowledge Graph / Dashboard
Elevator pitch: Signal-Finder transforms Intuition’s knowledge graph into an easy-to-access investment tool, insight indicator where users stake $TRUST on signals they believe in, with AI automation and collaborative agents coming next. Aiming long-term potential to combat misinformation and inaccuracies while extending and reinforcing the trust network.
Origin story: As a retail crypto participant since 2021, I witnessed many scams, soft rugs also coupled to fake information, inaccurate signal. I came to a conclusion: the challenge of finding reliable signals in the data chaos was real, that’s why I was attracted to Intuition. That’s why I think Intuition’s knowledge graph provides the perfect foundation to create economic incentives around truth-seeking, Information Finance development and signal validation.
Current users/early testers: Zet, Jade Michel, me
2. What You’re Building
Problem Statement: Nowadays, the information market seems saturated and investors face an enormous quantity of noise thus struggling to isolate valuable signals. Current tools lack incentives for validating signals through the usage of decentralized community consensus, Reputation and economic incentives and knowledge graph indexing.
But I have also realized, building a reliable network will take time and track misinformation, inaccuracies can be tedious and tricky in a vast, flourishing decentralized network.
Proposed Solution:
That’s why I want to contribute and accelerate the establishment of a chain of trust and help sport misinformation through the building of a comprehensive InfoFi dashboard that:
- Categorizes signals by investment risk profile (Heavyweight/Trending/Emerging)
- Enables direct $TRUST staking on atoms and supporting/opposing on triples
- Provides live signal discovery with instant investment capability
Spots misinformation with the LiveActivityFeed through serendipity of expert inside the community - Detects inaccurate and noisy trends/signals and allow direct community consensus review
- Plans AI automation for strategy execution
- Future MCP integration for agent collaboration
- Stage of Development: Prototype
Technical architecture overview: Web-based dashboard interfacing with Intuition’s knowledge graph coupled with a Live Activity Feed, planned on-chain staking mechanisms, reputational metric, future integration with AI agents and MCP servers for automated strategy execution.
Integrations or dependencies: Intuition Network, $TRUST token, planned MCP integration, AI agent frameworks
3. Team & Execution Ability
Team backgrounds: Solo vibecoder with Python and Arduino education, crypto ecosystem participant since 2017, retail investor since 2021. Strong interest in AI, its training methods and the latest developments despite no professional experience in the field.
Execution proof: You can find the prototype at signal-finder.intuition.box with GitHub repository where you have all the commits and the code deployed.
Commitment level: Part-time
Advisors: Zet, Saulo
Prior crypto / AI experience: 3+ years crypto experience, academic courses on Python and school projects on Arduino (Portable weather station crafting), self-taught development skills, continuous learning in AI breakthrough
4. Grant Request & Milestones
Amount requested: $20,000 USD equivalent in TRUST and 35,000 USD
Budget breakdown:
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Phase 1 (Feb 2026): On-chain staking mechanism - $1,000
Phase 2 (May 2026): New analysis tool to improve dashboard accuracy - $2,500
Phase 3 (August 2026): AI automation system - $20,000Phase 4 (Dec 2026): MCP integration - $10,000
Phase 5 (Apr 2027): Collaborative platform - $2,500
Phase 6 (Dec 2027): Implementation of the reputation metric - $2,000
Phase 7 (Dec 2028): Misinformation detection - $5,000Social budget - $2,000
Incentives campaign - $10,000
Timeline milestones:
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February 2026: Complete staking, supporting/opposing mechanisms
April 2026: Release of tools offering new InfoFi perspectives and better insightsAugust 2026: Launch automated signal investment with AI agents
December 2026: Deploy MCP server integration
April 2027: Release collaborative agent platform
December 2027: Equally gauge signals based on reputation in addition to capital and community
December 2028: Detect risk of misinformation/inaccuracies with a risk factor and a given error rate
Success criteria:
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Functional on-chain staking with measurable $TRUST volume
Proven relevancy and accuracy of the freshly integrated dashboard tools
Working AI automation with user-defined strategies
MCP integration enabling agent collaboration
Active user base engaging with all three lenses and three metrics
Low misinformation detection error rate
5. Intuition Ecosystem Alignment
Why Intuition: Signal-Finder directly leverages Intuition’s knowledge graph structure, using atoms and triples as investable signals. The project creates economic incentives that increase network activity and knowledge density through $TRUST staking. Also, it aims to help strengthening the network’s reliability and how fast we discover misinformation/inaccuracies inside it, leading to both a signal finder and a trust accelerator.
Primitives used: Atoms, triples, $TRUST token, knowledge graph queries, planned agent registry integration, future MCP implementation
Why it must be built on Intuition: The project fundamentally relies on Intuition’s semantic triple structure and $TRUST economic model to create meaningful signal validation markets.
TRUST integration: Core mechanism for staking on atoms, supporting/opposing triples, funding AI strategies, and incentivizing collaboration between agents.
6. Sustainability & Long-Term Vision
Long-term vision: Become the primary interface for InfoFi signal discovery and investment on Intuition, with a thriving ecosystem of collaborative AI agents executing sophisticated information strategies. While strengthening and enlarging the trust of the network through enhanced misinformation detection and inaccuracy spotting directly by agentic entities or sophisticated tools. Primarily, the Dashboard would give a way to the community to spot false narrative or made-up trends while the LiveActivityFeed will allow vigilant experts belonging to the community to witness incorrect signals created by serendipity when watching time to time the Feed, this could be later automated to avoid 24H/7D human watchers and, the bigger the community, the bigger, the amount of expert using the app. Indeed, researchers showed that we could model information networks with a thermodynamics analogy and that my Signal-Finder project could possibly help reduce trust «latency» and improve the pace at which we spot misinformation/inaccuracies (thesis summarized by AI):
Core Innovation - The “Warm Wire” Network:
- Existing Trust = Thermal Energy: Your positions in trustworthiness and other verified concepts act as “warm nodes”
- New Signals = Cold Metal: Unverified information enters at “absolute zero” trust
- Low Friction Discovery: AI-powered relevance matching reduces “thermal resistance”
- Rapid Verification: Expert attention flows instantly to new signals, either integrating them (truth) or rejecting them (misinformation)
Strengthened Intuition Ecosystem Alignment
Why This Must Be Built on Intuition: Signal-Finder leverages Intuition’s semantic triple structure to create what network scientists call “Small-World Rewiring” - where a few strategic connections (your serendipitous signal matching, through LiveActivityFeed) dramatically reduce the network diameter, making truth propagation nearly instantaneous across domains.
Enhanced Success Metrics
Quantifiable Thermodynamic Metrics:
- Verification Velocity: Time from signal creation to expert engagement
- Cross-Domain Bridge Rate: Frequency of serendipitous expert connections across different knowledge clusters
- Signal-to-Noise Improvement: Ratio of validated vs. rejected signals over time
- Network Conductivity: Measure of how quickly trust/distrust propagates through the knowledge graph
Key papers:
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Brandes & Fleischer (2005) on Current-Flow Betweenness Centrality-
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Burt (2004) on Structural Holes and Good Ideas-
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Ecker et al. (2022) on cognitive drivers of misinformation belief-
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Watts-Strogatz Small-World Network Model
Post-grant sustainability: Transaction fees from automated strategies, premium features for institutional users, potential revenue sharing with successful AI agents, additional bounties for spotting misinformation, race contest regarding inaccuracy discovery.
Business model: Freemium model with basic signal access free, premium automation features, and institutional-grade tools as paid tiers.
7. Additional Materials
Figure_1: Signal-Finder architecture
Figure_2: Screenshot of the Signal-Finder prototype
Figure_3: Screenshot of another version of the Signal-Finder prototype
Demo link: same as website
Contact email: c0mbineharvester@protonmail(dot)com
Wallet address (#5): 0x0eBE9046d9f5492828beF03277A0DC4bBceCAD62
8. Applicant Attestation
I confirm that all information submitted is accurate and that I intend to deliver the listed milestones.
Budget Justification: The $55K request covers development costs, AI model access fees, infrastructure, social management and incentives for early adoption. This should provide sufficient fundings for the roadmap created while triggering interest, expanding trust and harnessing the protocol usage in the Intuition ecosystem.
Name: Maxime Blanc
Wallet address : 0x0eBE9046d9f5492828beF03277A0DC4bBceCAD62
Date: 05/12/2025