Oracle AI - The Market Signal Platform

[Proposal setup] Proposal title

Please provide your proposal title

Oracle AI - The Market Signal Platform

[Proposal Summary] Budget Information

Enter the amount of funding you are requesting in ADA

100000

[Proposal Summary] Time

Please specify how many months you expect your project to last

12

[Proposal Summary] Translation Information

Please indicate if your proposal has been auto-translated

No

Original Language

en

[Proposal Summary] Problem Statement

What is the problem you want to solve?

Crypto investors face an edge gap with institutions, lacking tools to process data and spot trends, often missing opportunities or losing money due to emotional, uninformed decisions.

[Proposal Summary] Supporting Documentation

Supporting links

• https://docs.google.com/document/d/1D5_VAWprTrWIW7BIn53OOJ9amf23k2Tw6J7qFMmijI0/edit?usp=sharing
,
• https://docs.google.com/document/d/1dnVFPZFeT_-ESfrO0s1Mbks88zXTHP3NGVEnGqSOqEw/edit?usp=sharing

[Proposal Summary] Project Dependencies

Does your project have any dependencies on other organizations, technical or otherwise?

No

Describe any dependencies or write 'No dependencies'

No dependencies

[Proposal Summary] Project Open Source

Will your project's outputs be fully open source?

Yes

Please provide details on the intellectual property (IP) status of your project outputs, including whether they will be released as open source or retained under another licence.

The all components, except AI models, will be open-sourced after deployment.

[Theme Selection] Theme

Please choose the most relevant theme and tag related to the outcomes of your proposal

AI

[Campaign Category] Category Questions

Describe what makes your idea innovative compared to what has been previously launched in the market (whether by you or others).

Oracle AI introduces several innovations that differentiate it from traditional crypto analytics tools and previously launched AI trading products:

1. Cardano-Native, Chain-Integrated AI Signals

Most AI trading tools rely almost entirely on price charts and centralized exchange data.Oracle AI is one of the first platforms to:

• Integrate Cardano on-chain transaction patterns, stake pool dynamics, and whale flows directly into AI training.
• Combine verifiable, transparent blockchain data with machine-learning predictions.This creates a signal engine specifically optimized for Cardano’s unique ecosystem — something not available in existing multi-chain or centralized AI signal tools.

2. Unified AI Engine Combining Price Prediction + Market Sentiment

Existing platforms usually provide either price alerts or social sentiment dashboards, but not both in an integrated model.

Oracle AI is innovative because it merges:

• LSTM / Transformer-based price trend prediction
• Real-time sentiment extraction from Twitter/Reddit
• Market regime detection (trend, reversal, volatility zones)The fusion of chain data + social sentiment + AI prediction produces more reliable, context-aware signals than single-source tools.

3. Verifiable, Transparent Model Performance (Backtesting + Accuracy Reporting)

Most AI alpha providers hide performance or provide non-auditable results.

Oracle AI commits to:

• Publishing model backtesting reports with accuracy, Sharpe ratio, F1-score
• Displaying historical signal accuracy directly in the dashboard
• Allowing the community to verify predictions via APIThis transparency is rare in AI crypto products and increases trust and accountability.

4. Lightweight, Interoperable API Designed for the Cardano Ecosystem

While competitors lock users into paid dashboards, Oracle AI offers:

• A public prediction API for DApps, wallets, trading bots
• Webhooks for automated trading
• A modular signal engine that third-party developers can integrate into DeFi protocolsThis infrastructure-first approach enables AI-powered features across the entire Cardano ecosystem, not just one user interface.

5. First Step Toward On-Chain AI-Driven Automated Trading in Cardano

Oracle AI lays the groundwork for future features that don’t exist today:

• On-chain execution signals
• Oracle-compatible prediction feedsAutomated strategy triggers for DEXs/lending protocolsThis positions Oracle AI as a core intelligence layer for Cardano’s DeFi ecosystem — something currently missing in the market.No existing product offers this combination, making Oracle AI a novel, high-value addition to the Cardano ecosystem.

Describe what your prototype or MVP will demonstrate, and where it can be accessed.

The Oracle AI MVP will demonstrate a working prototype of the platform’s core capabilities, including:

1. AI-generated 7-day price trend forecasts with confidence scoring
2. Real-time social sentiment analysis from sources such as Twitter and Reddit
3. Automated buy/sell and trend-reversal alerts delivered via email or webhook
4. An interactive dashboard displaying predictions, sentiment indices, and historical signal accuracy
5. A publicly accessible API allowing developers to test and integrate Oracle AI’s signals into their own tools.

The prototype will be accessible through a browser-based web app at a dedicated URL (final link provided upon completion), with supporting API documentation.

Describe realistic measures of success, ideally with on-chain metrics.

Technical

• ≥ 60% direction accuracy
• API uptime ≥ 99.9%
• Latency < 30s

Adoption & Usage

• ≥ 10 ecosystem integrations (builders × DApps × trading bots)
• ≥ 1,000 API calls/day
• ≥ 50 beta testers from trading communities
• ≥ 5 dashboards/bots using prediction API

Mainnet Value

• Prediction API successfully deployed on Cardano mainnet
• ≥ 1 on-chain use case (strategy badge / signal timestamping)

Transparency

• Full backtesting report published
• Public developer portal & API docs
• Auditable prediction logs

[Your Project and Solution] Solution

Please describe your proposed solution and how it addresses the problem

Oracle AI provides an AI-driven market intelligence platform designed to help Cardano investors overcome information overload, emotional decision-making, and the lack of reliable analytical tools. The solution integrates three critical components:

1. Machine-learning price trend forecasts trained on Cardano on-chain data and market data
2. Real-time social sentiment analysis that quantifies market psychology
3. An automated signal engine that alerts users when key opportunities or risks appear

These insights are delivered through an intuitive web dashboard and a developer-friendly API, giving both retail users and ecosystem builders access to actionable, data-driven signals. By transforming raw blockchain and social data into clear predictions, sentiment scores, and timely alerts, Oracle AI directly addresses the problem of scattered, difficult-to-interpret market information and empowers users to make more confident, informed investment decisions within the Cardano ecosystem.

[Your Project and Solution] Impact

Please define the positive impact your project will have on the wider Cardano community

Solving a Critical Gap in Cardano: Lack of AI-Driven Market Intelligence

While Cardano has strong infrastructure and tooling, it lacks data intelligence services that help investors, builders, and developers make informed decisions. Oracle AI fills this gap by introducing:

• AI-powered price trend forecasting

• Market sentiment scoring

• On-chain activity analysis

• Developer-ready prediction APIs

  This provides Cardano with a much-needed intelligence layer, similar to what Nansen, Glassnode, and IntoTheBlock provide for other ecosystems.

Expanding the Utility of Cardano Data

Oracle AI makes Cardano’s rich on-chain data actionable by converting it into:

• Buy/sell signals

• Trend reversals

• Whale activity indicators

• Sentiment-risk metrics

  This increases the practical value of Cardano’s transparent data and enhances the experience for traders, builders, and researchers.

Accelerating AI Adoption Inside Cardano

This project introduces a scalable foundation for:

• AI-enabled DeFi strategies

• AI-powered DApps

• Risk-management tools for protocols

• Automated trading bots

  Oracle AI helps position Cardano as a forward-looking AI + blockchain ecosystem.

Ecosystem-Level Benefits

• For Retail Users: clearer, data-driven insights → better decision making.

• For Developers: a prediction API they can integrate into DEXs, wallets, and analytics tools.

• For DeFi: potential for AI-driven automated strategies.

• For Cardano’s Global Positioning: enhances Cardano’s competitiveness vs. AI-integrated chains like Injective or Bittensor.

  Overall, Oracle AI increases Cardano’s functionality, innovation depth, and data intelligence—elements essential for ecosystem maturity.

[Your Project and Solution] Capabilities & Feasibility

What is your capability to deliver your project with high levels of trust and accountability? How do you intend to validate if your approach is feasible?

Real Use Cases & Ecosystem Partners

Oracle AI has already identified several real integration opportunities with active Cardano builders:

1. Trading Bot Community (Integration Intent Confirmed)

A Cardano trading bot group operating in Telegram & Discord will use Oracle AI’s prediction & sentiment API for:

• Trend reversal alerts
• Aautomated buy/sell triggers
• Whale sentiment monitoringThis provides real usage data and validates model performance in live market conditions.

2. Cardano Whale Activity Tracker

A dashboard maintainer has expressed intent to integrate Oracle AI’s sentiment + risk indicators to enhance:

• Whale detection
• Volatility scoring
• Trend momentum classificationThis produces public-facing adoption, measurable via dashboard API queries & visitor logs.

3. Developer Integrations

At least three ecosystem developers (DEX bot builders, DeFi analysts, NFT trading signal creators) will join the beta integration program, using the:

• Prediction API
• Sentiment API
• Market regime classification modelIntegration demos will be included as acceptance criteria in Milestone #3.

Capabilities

This project is led by a collaborative team with strong expertise across machine learning, data analysis, and software development. We bring extensive hands‑on experience in designing predictive models, building robust data pipelines, and developing full‑stack applications.

The team includes several data and AI scientists as core members, each contributing specialized knowledge in areas such as deep learning, model evaluation, blochchain analytics, and cloud infrastructure. Together, the team covers the full spectrum of skills required—from backend engineering and API integration to frontend design and dashboard creation—ensuring that the MVP can be delivered as a cohesive, well‑engineered solution.

This integrated capability structure allows the project to execute independently without relying on a large external workforce, while maintaining access to advanced expertise within the team itself.

Feasibility

The project is highly feasible becasue of the well‑defined technical scope, reliance on proven technologies, and a structured 12‑month development plan. We will leverage established machine‑learning methods, standard data engineering practices, and widely adopted frameworks for web and API development, minimizing technical risk.

Each milestone is designed to produce concrete, testable outputs—such as the data pipeline, prediction model, alert engine, dashboard, API documentation, and backtesting reports—that can be independently verified by auditors. With a realistic budget allocation and clear division of responsibilities across data science, backend, and frontend development, the team can reliably deliver the MVP within the proposed timeline.

This collaborative approach ensures accountability, transparency, and delivery of a functional prototype that the Cardano community can evaluate and build upon.

[Milestones] Project Milestones

Milestone Title

Data Pipeline & AI Model Development

Milestone Outputs

Outputs

• Full data pipeline integrating Cardano on-chain data (transactions, stake, whale flows)
• Social sentiment ingestion pipeline (Twitter, Reddit, etc.)
• Cleaned historical dataset
• V1 prediction model (price direction)
• Initial backtesting

Acceptance Criteria

Acceptance Criteria

• Pipeline ingests on-chain + social datasets reliably
• V1 model produces directional accuracy ≥ 55%
• A fully documented backtesting methodology
• Dataset reproducible by reviewers

Evidence of Completion

Evidence of Completion

• GitHub repository with pipeline + model code
• Backtesting report (PDF)
• Sample predictions on historical data
• Architecture diagram

Delivery Month

4

Cost

40000

Progress

40 %

Milestone Title

Backend API & Alert System

Milestone Outputs

Outputs

• Fully functional REST API (prediction + sentiment + combined signals)
• Configurable alert engine (email + webhook)
• API rate limiting, caching, monitoring
• Basic developer documentation (API keys, examples)

Acceptance Criteria

Acceptance Criteria

• API handles ≥ 100 requests/second
• Latency < 500ms
• Alerts trigger correctly for:
• Overbought/Oversold
• Trend reversal
• Whale-driven volatility
• Error handling implemented
• Security layer enabled (API keys + rate limits)

Evidence of Completion

Evidence of Completion

• Public API endpoint (testnet)
• Logs demonstrating alert triggers
• API request/response samples
• Monitoring dashboard screenshots

Delivery Month

4

Cost

30000

Progress

70 %

Milestone Title

Frontend & Visualization Dashboard

Milestone Outputs

Outputs

• Web dashboard with:
  • Real-time predictions
  • Sentiment indices
  • Model confidence scoring
  • Historical accuracy visualization
• User customization panel
• Live integration with API

Acceptance Criteria

Acceptance Criteria

• Dashboard responsive on desktop + mobile
• Real-time data refresh under 3 seconds
• At least 25 beta users complete usability test
• All accuracy, sentiment, and signal data correctly displayed

Evidence of Completion

Evidence of Completion

• Public dashboard URL
• Dashboard demo video
• Usability test logs & feedback summary

Delivery Month

2

Cost

20000

Progress

90 %

Milestone Title

Model Backtesting, Testing & Documentation

Milestone Outputs

Outputs

• Mainnet deployment of Oracle AI Prediction API
• Backtesting results with advanced metrics (Sharpe, F1-score, confusion matrix)
• Partner integration demos (≥ 2 real integrations)
• Final documentation package

Acceptance Criteria

Mainnet endpoint live and stable

• 2–3 real partner integrations completed
• Backtesting meets accuracy targets
• Ecosystem adoption metrics:
  • ≥ 10 projects/developers onboard
  • ≥ 50 beta traders
  • ≥ 1,000 API calls/day

Evidence of Completion

Evidence of Completion

• Mainnet API endpoint (publicly accessible)
• Integration demo videos (2–3 partners)
• Backtesting report (PDF)
• API documentation & developer portal
• Catalyst close-out report

Delivery Month

2

Cost

10000

Progress

100 %

[Final Pitch] Budget & Costs

Please provide a cost breakdown of the proposed work and resources

• AI & Data Science (50,000 ADA): Ensures quality model development, Data AI scientist consultant cost
• Backend & Data Infrastructure (30,000 ADA): API, pipelines, scalable microservices
• Data + Cloud Compute (15,000 ADA): GPU training, data ingestion, servers
• Testing & Verification (5,000 ADA): Backtesting + professional user testing

Total Budget: 100,000 ADA

[Final Pitch] Value for Money

How does the cost of the project represent value for the Cardano ecosystem?

The cost of this project represents strong value for the Cardano ecosystem because it delivers a complete, end-to-end AI market intelligence platform that would otherwise require significantly larger budgets and multi-person teams to develop. For A100,000, the project produces a functional forecasting model, real-time sentiment engine, alert system, public dashboard, developer API, and full model backtesting—capabilities that enhance transparency, improve user decision-making, and strengthen Cardano’s data infrastructure. By enabling traders, builders, and DeFi protocols to access high-quality AI-generated signals, the project increases engagement, reduces information barriers, and supports more informed activity across the ecosystem. The funding directly results in a reusable intelligence layer that other Cardano projects can integrate, amplifying its long-term value far beyond the initial proposal budget.

[Self-Assessment] Self-Assessment Checklist

I confirm that evidence of prior research, whitepaper, design, or proof-of-concept is provided.

Yes

I confirm that the proposal includes ecosystem research and uses the findings to either (a) justify its uniqueness over existing solutions or (b) demonstrate the value of its novel approach.

Yes

I confirm that the proposal demonstrates technical capability via verifiable in-house talent or a confirmed development partner (GitHub, LinkedIn, portfolio, etc.)

Yes

I confirm that the proposer and all team members are in good standing with prior Catalyst projects.

Yes

I confirm that the proposal clearly defines the problem and the value of the on-chain utility.

Yes

I confirm that the primary goal of the proposal is a working prototype deployed on at least a Cardano testnet.

Yes

I confirm that the proposal outlines a credible and clear technical plan and architecture.

Yes

I confirm that the budget and timeline (≤ 12 months) are realistic for the proposed work.

Yes

I confirm that the proposal includes a community engagement and feedback plan to amplify prototype adoption with the Cardano ecosystem.

Yes

I confirm that the budget is for future development only; excludes retroactive funding, incentives, giveaways, re-granting, or sub-treasuries.

Yes

[Required Acknowledgements] Consent & Confirmation

I Agree

Yes