Project case study
Ekathvam-OmniSwarm
An MCP-native self-healing multi-agent orchestration swarm on Gemma 4 31B via Cerebras, with live performance telemetry.
Problem
Coordinating specialist AI agents without a single point of failure, and proving the coordination actually worked rather than asserting it.
Context
An MCP-native self-healing multi-agent orchestration swarm on Gemma 4 31B via Cerebras, with live performance telemetry.
My Role
AI/ML Engineer, Data Systems Builder & Motion UI Developer
Contribution
Contribution details are not documented in the current source archive.
Architecture
Engineering Decisions
Engineering decisions are not documented in the current source archive.
Outcomes
Built an MCP-native self-healing agent swarm on Gemma 4 31B running on Cerebras WSE-3, with a twin-engine architecture: a Next.js swarm visualiser with a throughput HUD plus a standalone Python CLI for local verification, client-side encryption and a DPDP Act 2023 aligned erasure path.
Sources: cert-21
Limitations
Limitations are not documented in the current source archive.
Stack
- Next.js
- Python
- Gemma 4 31B
- Cerebras Cloud
- MCP