AI Research Pipeline

How AI agents transform research requests into comprehensive dossiers

Overview

The AI Research Pipeline is the heart of Elusiv's research generation system. It transforms user queries into comprehensive, well-researched dossiers through a sophisticated orchestration of AI agents, tools, and validation processes.

The AI pipeline operates off-chain for flexibility and cost efficiency, while maintaining on-chain provenance and integrity guarantees.

How AI Agents Work

Agent Architecture

Elusiv uses a multi-agent system where specialized AI agents collaborate to produce research:

Retrieval Agents

Gather relevant information from curated datasets and external sources.

Reasoning Agents

Analyze information, synthesize findings, and construct coherent arguments.

Domain Specialists

Specialized agents for specific domains (physics, economics, history, etc.).

Validation Agents

Verify facts, check citations, and ensure quality standards.

Agent Orchestration

The Agent Orchestrator coordinates the research process:

Request Routing

Routes requests to appropriate agent ensembles based on topic, domain, and complexity.

Versioned Prompts

Maintains versioned prompts and runbooks for reproducibility and consistency.

Tool Integration

Integrates domain-specific tools (simulations, models, databases) as needed.

Research Generation Process

Step-by-Step Pipeline

1

Request Assignment

Orchestrator receives on-chain event, analyzes query, and assigns to appropriate agent ensemble.

2

Information Retrieval

Retrieval agents gather relevant data from curated corpora, external sources, and user-supplied datasets.

3

Analysis & Synthesis

Reasoning agents analyze information, identify patterns, and synthesize findings into coherent narratives.

4

Document Generation

Agents generate research outputs ranging from brief memos (3-10 pages) to comprehensive dossiers (30-70+ pages), with executive summaries, detailed analysis, citations, and visualizations.

5

Quality Validation

Validation agents and reviewers check quality, verify citations, and ensure standards are met.

Retrieval-Augmented Generation

Elusiv uses Retrieval-Augmented Generation (RAG) to enhance research quality:

  • Curated Corpora: High-quality datasets tagged with provenance and license metadata
  • User-Supplied Data: Requesters can provide additional datasets for context
  • Source Diversity: Agents pull from multiple sources to ensure balanced perspectives
  • Citation Tracking: All sources are tracked and included in final dossiers

Quality Assurance and Validation

Automated Checks

Before publication, research undergoes automated validation:

Hallucination Detection

Checks for unsupported claims and factual errors

Source Diversity

Ensures multiple sources are cited, avoiding single-source bias

Policy Conformance

Verifies compliance with safety and governance policies

Structure Validation

Ensures proper formatting, citations, and document structure

Human Review

For complex or sensitive topics, human reviewers may:

  • Verify factual accuracy
  • Check source quality and relevance
  • Assess argument coherence
  • Provide attestations linked to dossier hashes

Agent Orchestration

Orchestrator Responsibilities

The Agent Orchestrator manages the entire research lifecycle:

Request Routing

Analyzes queries and routes to appropriate agent ensembles based on domain and complexity.

Workflow Management

Coordinates multi-step research processes, managing dependencies between agents.

Tool Integration

Integrates domain-specific tools (physics engines, econometric models, simulations) as needed.

Logging & Audit

Maintains structured logs of prompts, model versions, tool calls, and evaluation scores.

Observability & Reproducibility

Structured Logging

All research processes are logged for:

  • Reproducibility: Versioned prompts and runbooks enable recreating research
  • Audit Trail: Complete record of inputs, processes, and outputs
  • Quality Monitoring: Detect drift, regressions, or prompt injection attempts
  • Dispute Resolution: Verifiable lineage from query to final dossier

Attestation Layer

The attestation layer provides:

  • Signed metadata binding inputs to outputs
  • Verifiable lineage for dispute resolution
  • Reviewer attestations linked to dossier hashes
  • Model version and tool call tracking

Future Enhancements

Planned Improvements

  • Multi-model ensembles for improved accuracy
  • Specialized domain agents for niche topics
  • Interactive research outputs (notebook-style artifacts)
  • Real-time collaboration between agents
  • Advanced simulation capabilities

Continue Learning

Explore other technical aspects of the Elusiv protocol.