Case Study
Low-Latency Multi-Agent Intelligence System
Designed and deployed a production multi-agent intelligence system using a mixture-of-experts setup, with speculative parallel execution and shared memory for faster, deeper reasoning.
Challenge
Perfusion Mind needed an AI system capable of handling complex, multi-step user requests without sacrificing response time. Single-agent designs were causing latency spikes on difficult prompts, while naive multi-agent orchestration created redundant tool calls, rising inference cost, and inconsistent context continuity between turns.
Solution
Helios engineered a mixture-of-experts multi-agent architecture with specialized agents for web research, scientific retrieval, and computation. The orchestration layer introduced speculative parallel execution, triggering likely specialist agents before final routing decisions to reduce tail latency. A shared conversational memory layer preserved cross-agent context and reduced repeated retrieval. Cost-aware routing logic balanced model quality, execution path depth, and response-time targets under variable workloads.
Technical Responsibilities
- Architected a multi-agent system with specialist agents for web, scientific, and computational tasks
- Designed speculative parallel execution to reduce end-to-end latency on complex queries
- Built orchestration policies for cost-aware and latency-aware routing
- Implemented shared conversational memory across agent boundaries
- Integrated external tools and APIs with retry-safe execution controls
- Designed evaluation pipelines for response quality, latency, and cost per interaction
- Deployed production monitoring for agent path selection and failure diagnostics
Outcomes
- Lower p95 response time on complex multi-step queries through speculative execution
- Improved reasoning depth without forcing all traffic through the heaviest execution path
- More consistent conversational continuity across turns via shared memory design
- Production visibility into cost, latency, and agent route quality