Advanced Research AI Agent Development

IWe are building a high-performance AI agent ecosystem designed to automate and enhance research, marketing, legal analysis, and strategic decision-making. This is not a chatbot project. We are looking for someone who can design and deploy a structured, multi-agent system capable of performing deep, iterative online research and producing decision-ready outputs. The objective is to replace fragmented workflows with a coordinated system of AI agents that can independently investigate topics, validate information, and generate high-quality insights in real time. Scope of Work You will design and implement a system of specialized AI agents, including: 1. Research Agent (Core Component) This is the most critical part of the system. The agent must be capable of: * Performing multi-step, iterative online research (not single queries) * Autonomously refining search queries based on findings * Extracting and synthesizing information from multiple independent sources * Identifying contradictions, gaps, and inconsistencies * Evaluating source credibility and reliability * Producing structured, decision-grade insights (not summaries) 2. Marketing & SEO Agent * Analyze competitors, search intent, and content gaps * Generate high-ranking content strategies * Optimize for both: * Traditional search (Google) * AI/LLM discovery (ChatGPT, Perplexity, etc.) * Continuously improve outputs based on performance signals 3. Legal & Compliance Agent * Perform cross-jurisdictional legal research * Analyze regulations, frameworks, and obligations * Structure legal arguments and risk assessments * Compare legal interpretations across countries 4. Strategy & Decision Agent * Combine outputs from all agents * Identify highest-impact actions * Prioritize execution based on ROI and risk * Deliver clear, structured recommendations Data the System Will Process The agents will work with a combination of: Deep Online Research Data (Primary) * Official legal and regulatory sources * Competitor websites and market data * Search engine results and SEO signals * Industry publications and authoritative sources Agents must perform iterative research loops: Search → Extract → Analyze → Refine → Re-search Internal & Text Data * Documents, policies, and internal materials * Marketing and SEO content * Research reports Structured Data * Analytics (conversion, funnels, performance) * SEO datasets (keywords, rankings) * Operational data System-Generated Intelligence * Research chains and query iterations * Source validation scoring * Cross-agent insights and outputs * Memory and feedback loops Technical Requirements You must have strong experience with: * Multi-agent system design or orchestration frameworks * LLM integration (OpenAI, Claude, or similar) * Building iterative research systems (agentic workflows) * Data extraction, structuring, and synthesis * Backend/API integration (any modern stack; Laravel experience is a plus) Strong advantage if you have built: * Autonomous research agents * SEO/content automation systems * Legal analysis tools * Decision-support systems Non-Negotiable Requirements * This is not a basic chatbot or single-prompt system * Must support deep, multi-step research workflows * Must include source validation and credibility scoring * Must reduce hallucinations and ensure output reliability * Must produce consistent, high-quality outputs at scale Deliverables * Full system architecture (agents, workflows, memory, validation) * Implementation of all agents * Research loop and orchestration logic * Output validation and scoring system * Documentation for internal use * Scalable foundation for future expansion How to Apply To be considered, you must: 1. Explain how you would design a multi-agent system with deep online research capability 2. Describe how you would implement: * Iterative search loops * Source validation * Contradiction detection 3. Provide examples of similar systems you’ve built Generic or vague applications will be ignored.

Project ID: 40402779