Roadmap

Q1 2025

MVP Scope, Technical Analysis & Risk Assessment

Define MVP versus long-term features; Develop analysis models with VC partner; Analyse API integrations, Solana staking protocols and governance tools; Refine risk metrics and composite scoring.

Q1 2025

Prototyping

Map out key user flows for conversational interface and staking; Complete wireframes, and begin v1 of UI & UX.

Q1 2025

Architecture

Finalise cognitive blueprint; Document interfaces between sub-agents and external systems.

Q1 2025

Infrastructure Design

Architect the auto-scaling, containerised infrastructure; Design an audit logging mechanism.

Q1 2025

Staking & Tiered Access

Finalise the dynamic USD value system, wallet limit calculations, and reflection reward mechanism; Define metrics and user benefits for MVP and future premium tiers. Leverage Solana protocols to implement staking, dynamic trading wallet limits, and the reflection reward mechanism.

Q2 2025

MVP Development

Build aggregation layer to fetch, validate, and normalise data for MVP APIs; Develop Brain STEM, Temporal and Parietal sub-agents for detailed analysis; Code the aggregation module that consolidates insights. Integrate a basic user interface for staking, token management, and tier access.

Q2 2025

Testing, Validation & Iteration

Validate each LLM module individually, end-to-end Testing; Stress-test cloud infrastructure for auto-scaling and high availability; penetration tests and smart contract audits.

Q2 2025

Governance & UAT

Gather user feedback on chatbot UI and analyses; Test the process for external community votes.

Q2 2025

MVP Deployment & Scaling

Launch the containerised MVP on a cloud-native platform with auto-scaling capabilities; Activate audit logging systems and monitoring dashboards; Roll out the staking mechanism; Publish internal docs for system architecture, API integrations, and operational procedures.

Q3 2025

Autonomous Investing

Develop algorithms for autonomous investments. Build monitoring tools for tracking investment performance with feedback loop provided by DMN LLM.