ProspectML

Your AI Research Strategist

Skip the search. ProspectML explores research directions, evaluates tradeoffs, and delivers implementation-ready experiments—so you can move fast on the ideas that matter.

TRUSTED BY RESEARCHERS AT
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What ProspectML Can Do

ProspectML helps researchers generate insights and code to accelerate AI research.

Research Landscape Scanning

Explore trends across the ML literature

ProspectML parses arXiv, conferences, and journals to uncover patterns, gaps, and emerging opportunities.

  • Analyze papers across arXiv, conferences, and journals
  • Generate comprehensive literature reviews
  • Identify key trends and research gaps
Example of Research Synthesis
Strategic Tradeoff Analysis

Weigh options before you code

ProspectML proposes and scores multiple directions, each with rationale and implementation paths..

  • Understand cost, risk, novelty, and reliability/li>
  • Compare approaches side-by-side
  • Focus your effort on what's most promising
Example of Solution Mapping
Experiment Acceleration

Go from idea to prototype — fast

Each proposed direction comes with code suggestions, design rationale, and citations to back it up.

  • Generate and test hypotheses quickly
  • Auto-generate experimental code
  • Document and share experiments with collaborators
Example of Research Synthesis

Who Uses ProspectML

Used by Researchers Across Academia and Industry

Research Teams

Coordinate strategy, literature reviews, and code testing in one place.

ML Engineers

Avoid boilerplate and experiment with focused implementations.

Academic Researchers

Let ProspectML handle the literature and scaffolding while you chase novel ideas.

How ProspectML Works

From Problem Statement to Working Plan

1

Define Your Research Goal

Describe your objective or research question. ProspectML adapts to your domain..

Set clear research objectives
Explore research gaps
Customize your research parameters
2

ProspectML Thinks, Plans, and Builds

The agent explores the literature, surfaces trends, and proposes viable directions.

Scans thousands of papers for signals, not summaries
Analyze patterns and connections
Produces experiments to test proposed directions
3

You Review & Select

Evaluate tradeoffs with visual summaries. Choose what to pursue.

Review research trends
Explore experimental code
Share findings with collaborators
4

Receive Actionable Outputs

Get structured rationales, papers, and implementation-ready experimental code.

Curated literature directly tied to your needs
Detailed reasoning behind each recommendation
Ready-to-run experiment code with documentation

Ready to transform your research workflow?

Start Your Research Journey

Tool Comparison

See how ProspectML compares to other research tools

ProspectML vs DeepResearch vs Elicit

Feature
ProspectML
DeepResearch
Elicit
Optimized for AI/ML R&D
Research paper summarization
Semantic Scholar + ArXiv integration
Cited references with context
Accuarate Paper Information Extraction
Searches across all of ArXiv
Generate pseudocode for novel ideas
Suggest hypotheses based on findings
Email or Slack-based prompt interface