Manual research is a solved problem. I just didn't know it yet.
Every time I needed to research a topic — market trends, competitor positioning, content for a blog post — I'd open a dozen tabs, skim through articles, copy-paste stats into a doc, and spend 2–3 hours turning noise into something usable.
That's not a research problem. That's a tooling problem.
So I built Deep Research Agent on Apify. It searches the web, reads 5–30 sources, and synthesizes everything into structured JSON — automatically.
Here's how it works, and why I built it this way.
The Problem With Every Existing Tool
Perplexity is great for quick answers. ChatGPT Deep Research is impressive. But neither gives you structured, machine-readable output you can actually pipe into a workflow.
What I needed wasn't a chat interface. I needed an API that returned:
- A synthesized summary
- Key statistics with sources
- Content angles I hadn't thought of
- An SEO keyword list
- A content outline ready to use
- A GEO-optimized answer for AI search engines
And I needed it as JSON, not a wall of text.
No existing tool did that. So I built it.
How It Works
Three steps.
1. Multi-query search
Instead of one search query, the agent generates several variants around your topic. "AI coding tools" also becomes "AI coding assistant comparison," "best copilot alternatives 2026," and "code completion AI pricing." Different queries surface different sources.
2. Full content extraction
Most tools work off snippets. This one fetches and reads the full content of every page using Brave Search API. 5 sources for quick research, up to 30 for deep competitive analysis.
3. AI synthesis
DeepSeek reads everything and produces structured JSON. Not a summary. A report. With sections, citations, and a geo_angle field designed specifically for AI search citation.
The geo_angle Field (Why This Matters Now)
Most people haven't heard of GEO — Generative Engine Optimization. It's the AI-era equivalent of SEO.
When someone asks ChatGPT, Perplexity, or Claude a question, these systems look for content that's structured to be cited. Short, self-contained, factual, with named entities.
Every research output from this agent includes a geo_angle block: a 130–170 word answer written specifically to be referenced by AI search engines. If you're doing content marketing in 2026, this matters.
What the Output Looks Like
The output is a JSON object with these fields:
- topic — the research subject
- summary — 2–3 sentence executive summary
- stats — key statistics with source URLs
- angles — unique content angles found across sources
- outline — ready-to-use article structure (H2s)
- keywords — SEO keyword list
- geo_angle — 130–170 word answer optimized for AI search citation
- sources — full list of analyzed URLs
That's usable. You can pipe that directly into a content pipeline, a RAG system, or a briefing generator without touching it.
Pricing: Pay Per Run, Not Per Month
I hate subscription pricing for tools I use occasionally. So this uses pay-per-event.
Shallow — 5 sources, ~$0.80
Medium — 15 sources, ~$1.30
Deep — 30 sources, ~$2.05
A freelance researcher charges $50–150 for the same output. A Perplexity Pro subscription costs $20/month regardless of how much you use it.
Pay $1.30, get a structured research report. That math works.
Who This Is Actually For
If you're doing research once a week and just need a quick answer, use Perplexity.
If you're building something — a content pipeline, an automation workflow, an AI application that needs a research layer — this is for you. The JSON output is designed to be consumed by machines, not read by humans.
It also supports Korean output, which matters if you're running multilingual content operations.
What It Doesn't Do
Be honest about limitations: this isn't a replacement for primary research, domain expertise, or real-time data. It reads what's publicly indexed. It synthesizes — it doesn't verify.
Use it to start the research process, not end it.
Try It
It's live on Apify Store: apify.com/rockboat/deep-research-agent
Free Apify account gets you enough credits to test several runs. Give it a topic you've been meaning to research and see what comes back.
If you're building something with it or have feedback, I'm interested to hear it.
