Multi-Agentic Pipeline

Architecture and agent registry of the Qubitz AI multi-agent research pipeline.

Pipeline Architecture

The Deep Analysis engine is a multi-agent orchestration system that coordinates specialized AI agents through a sequential-parallel execution pipeline. The system processes business context through six distinct phases, each handled by one or more agent types.

The pipeline follows this high-level flow:

SYSTEM (init)
  → AGENT: RESEARCH (strategy + initial research, ~2 min)
  → AGENT: RESEARCH (parallel subtopic research, ~2 min)
  → AGENT: WRITER (parallel report generation, ~2.5 min)
  → AGENT: DUAL_PUBLISHER (publishing, ~30s)
  → STEP: REVIEW → Use Case Generator (streaming, ~1 min)

Total wall-clock time: approximately 6-8 minutes.

Agent Registry

The pipeline employs 5 distinct agent types. Each agent has a specific role, operates within a defined phase, and produces measurable output.

Agent IdentifierTypePhaseRoleOutput
SYSTEMInfrastructure1, 2, 5Connection management, status updates, pipeline coordination between phasesStatus messages, connection state
AGENT: RESEARCHWorker1, 2, 3Plans the research strategy, conducts web research -- crawls company website, gathers market intelligence, investigates subtopics in parallelResearch plan, raw research data, market analysis, competitive intelligence
AGENT: WRITERWorker4Generates both the AI Discovery Report (structured template with decision matrices, architecture diagrams, risk heatmaps) and the Deep Research Report (narrative sections, data tables, citations, strategic recommendations)AI Discovery Report PDF (~16 pages), Deep Research Report PDF (~25+ pages)
AGENT: DUAL_PUBLISHERPublisher5Publishes both reports in their final formats -- standard (Deep Research) and structured (AI Discovery)Published PDF artifacts with version tracking
STEP: REVIEWController5, 6Reviews all compiled research, validates completeness, triggers the use case generation phaseValidated research package, use case generation trigger