How is Research different from a search engine?

Research doesn't just list links; it generates structured reports with executive summaries, multi-dimensional analysis, different viewpoints, data sources, and actionable next steps.

Can I export research results?

Yes. Export to PDF or DOCX format for sharing, printing, or further editing.

What can I do after completing research?

Extract options from your research and launch a decision analysis directly, turning information into action.

How to Generate In-Depth Research Reports with AI

Core Summary: Judiciv Research offers three depth levels backed by different strategies: Quick Scan (keyword clustering), Deep Research (structured summarization), and Comprehensive Analysis (multi-perspective meta-analysis). All reports export to PDF or DOCX and can launch decision analysis directly.

This came out of a real work task. Last week I needed to research "Southeast Asian electric two-wheeler market 2026", a 30-page PDF for Friday's investment committee meeting. I gave myself three days. From opening Research to exporting the final PDF, it took under two hours. Not because I read fast. Because I didn't have to read.

How Research Works

Unlike a search engine, which gives you links and makes you filter, read, and synthesize yourself, Research produces structured reports. It uses a phased strategy:

Query decomposition: Breaks your question into sub-topics

Parallel collection: Gathers information on each sub-topic

Synthesis: Identifies themes, contradictions, and gaps

Structured output: Organizes by your chosen depth level

Three Depth Levels

1. Quick Scan (30 seconds)

Backend strategy: Keyword clustering + source relevance scoring

When to use: Fast topic assessment: decide whether to go deeper

Example query: "Electric vehicle market trends 2026"

Output: Key trends summary, major players, market sizing data points. Roughly 500 words. Just enough to decide "dig deeper" or "not relevant."

2. Deep Research (5 minutes)

Backend strategy: Structured summarization + source triangulation

When to use: Reliable, structured information for decision support

Example query: "Impact of remote work on software engineer productivity"

Output:

Executive summary (~200 words)

Multi-dimensional analysis (productivity, collaboration, innovation, career growth)

Data sources with publication dates and source quality assessments

Differing academic viewpoints

Actionable recommendations

Last month I used Deep Research to prepare a brief on "AI impact on junior developers", exported to PDF and handed it to my team as the basis for a discussion.

3. Comprehensive Analysis (15 minutes)

Backend strategy: Multi-perspective meta-analysis + argument mapping

When to use: Full understanding of a complex topic

Example query: "Current state, challenges, and future of AI in medical diagnosis"

Output:

Full multi-chapter report (technical landscape, regulatory environment, ethical considerations, market forecasts, stakeholder perspectives)

Debate map (key points of contention with evidence on both sides)

Scenario analysis

Reference list

Ready to export as the basis for an article or whitepaper

From Research to Decision

Research's integration with Judiciv's other tools is its killer feature. After completing research, extract options and launch Ranker or Judgment with one click.

My process last week: Research → extracted 4 options → Ranker comparison → Judgment deep dive → final decision. From zero to decision in under an afternoon.

Try Research and experience a new way of gathering information.