Phase 1-3 Roadmap

MindGrid’s 12-month roadmap outlines the evolution of our software ecosystem, from foundational modules and early deployments to full-scale, production-ready intelligence stacks deployed across diverse robotic platforms. This roadmap reflects both our technical milestones and community engagement strategy, building toward a scalable, measurable, and decentralized robotics intelligence layer.

Phase 1: Foundation & Early Deployments

• Release open-source LLM and TTS/STT beta modules for prototyping and early developer adoption.

• Expand smolVLM capabilities for lightweight vision and scene understanding.

• Launch ROS2 integration alpha, enabling robotic developers to connect MindGrid intelligence directly to physical hardware.

• Begin pilot RWA/Staking hybrid deployments to validate real-world performance, telemetry, and reward distribution mechanisms.

• Implement the initial staking participation framework for OSS contributors and early ecosystem members, linking measurable software performance to on-chain incentives.

Phase 2: Multi-Modal Intelligence & Enterprise Readiness

• Develop multi-modal LLM+Vision planning modules for advanced task decomposition, reasoning, and adaptive behavior.

• Introduce manipulation and motion APIs for complex grasping, control, and multi-agent coordination.

• Launch enterprise-grade on-prem solutions with SLAs, performance monitoring, and compliance support.

• Deploy the full staking-enabled ecosystem, connecting community contributions, real-world deployments, and RWA performance to proportional rewards.

• Release expanded evaluation and benchmarking tools for continuous performance tracking across robotic platforms and environments.

Phase 3: Scaling & Ecosystem Expansion

• Integrate multi-agent and fleet coordination systems, enabling distributed robotic collaboration at scale.

• Expand the premium API suite, including Vision+, LLM+, and TTS+ endpoints for enterprise clients and OEMs.

• Grow the MindGrid partner network, integrating robotics startups, research labs, and industrial fleets.

• Launch Data-as-a-Service and Benchmarking-as-a-Service offerings, further monetizing ecosystem telemetry and analytics.

• Strengthen community governance, enhancing transparency, contributor incentives, and decentralized roadmap alignment.

Ongoing Initiatives

• Continuous safety upgrades, red-teaming, and verification pipeline enhancements.

• Transparent, reproducible benchmarking via mindgrid-eval, ensuring staking reward accuracy and accountability.

• Expansion of open-source repositories under the MindGrid-x1 organization, covering perception, motion planning, and evaluation tooling.

• Iterative optimization of edge-cloud hybrid deployments, reducing latency and maximizing real-time performance.