Multi-Agent Research Workflow
Multi-agent research workflow using Proplexity and Open AI to aggregate and synthesize information in minutes instead of hours.
founders and execsfreelancers and consultants
What it does
You get consolidated research insights in minutes instead of hours by letting this workflow automatically pull knowledge from Proplexity and Open AI. It handles the entire aggregation process for you so you can focus on using those findings immediately.
Step by step
- Define the agent roles for data retrieval and synthesis within the workflow configuration.
- Set up API credentials for both Proplexity and Open AI in the environment variables.
- Configure the output schema to ensure structured JSON responses from the final consolidation step.
Where the LLM does the work
- Generate specific system prompts that instruct the LLM on how to synthesize conflicting data points from multiple sources.
- Design the reasoning chain for the synthesis agent to prioritize recent information over historical context.
- Create fallback instructions for handling cases where Proplexity returns insufficient or low-quality search results.
Watch out for
Token limits can truncate long research summaries so implement a chunking strategy for large inputs.
Inconsistent data formats from different tools will break the parser so enforce strict JSON schema validation early in the pipeline.
Circular dependencies between agents can deadlock the workflow so ensure a clear linear or directed acyclic graph structure for agent communication.
Tools that fit
Proplexity Service Knowledge retrieval
Open AAI LLM Knowledge processing
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Multi-Agent Research Workflow: Multi-agent research workflow using Proplexity and Open AI to aggregate and synthesize information in minutes instead of hours. ## Specification - What it does: You get consolidated research insights in minutes instead of hours by letting this workflow automatically pull knowledge from Proplexity and Open AI. It handles the entire aggregation process for you so you can focus on using those findings immediately. - Trigger: Run manually (Manual · on demand) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - Proplexity: Knowledge retrieval - Open AAI: Knowledge processing ## Known pitfalls, handle each one explicitly in your implementation 1. Token limits can truncate long research summaries so implement a chunking strategy for large inputs. 2. Inconsistent data formats from different tools will break the parser so enforce strict JSON schema validation early in the pipeline. 3. Circular dependencies between agents can deadlock the workflow so ensure a clear linear or directed acyclic graph structure for agent communication. ## Reference implementation https://www.youtube.com/watch?v=UIf-SlmMays (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/multi-agent-research-workflow/ via usecasesforagents.com
Frequently asked questions
Can I use a different LLM than Perplexity?
Yes. Perplexity is only the example LLM in this recipe. The same flow works with Anthropic, Cohere, DeepSeek and Google Gemini. Swap the LLM connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for founders and execs who need research handled without hiring for it.
Freelancers and consultants can run this per-client with no changes beyond the source data.