OpenClaw for Researchers

Why Researchers Need an AI Agent

Literature reviews are overwhelming. Hundreds of papers to find, read, categorize, and synthesize. You spend weeks on literature review before the actual research begins.

Data analysis requires iteration. You try one approach, check the results, adjust parameters, try again. Each iteration involves writing code, debugging, and interpreting results. The cycle is slow.

Administrative work creeps in. Grant applications, progress reports, collaboration emails, conference submissions — the paperwork of academia takes time away from actual research.

What Your Agent Can Do

Literature search and summarization — The agent browses Google Scholar, arXiv, university pages, and open-access journals for papers on your topic. It summarizes each paper's key findings, methodology, and relevance to your work.

Data analysis — Upload datasets and describe what you want to know. The agent writes and executes Python code with pandas, numpy, scipy, matplotlib, and other libraries. See data analysis use cases.

Writing assistance — The agent drafts literature review sections, methodology descriptions, results summaries, and grant proposal sections. It references sources you provide and maintains academic tone.

Web data collection — Scrape public data from websites, government databases, and open datasets. The agent can browse and extract structured information programmatically.

Code execution — Run statistical tests, data transformations, and simulations in the sandboxed Python environment. See code execution use cases.

Recommended Skills

• Coding Agent — Advanced Python code generation for analysis
• Summarize — Condense papers and reports into key findings
• Nano PDF — Generate formatted PDF reports and summaries
• Obsidian — Research notes and knowledge management
• Notion — Collaborative research documentation

Recommended Channels

The KiwiClaw dashboard chat is the best interface for research work. It provides a focused, distraction-free environment for iterative analysis sessions. For quick queries on the go, Telegram lets you ask questions and get answers from anywhere.

Example Workflows

Workflow 1: Literature review acceleration

1. Ask: "Find the 20 most cited papers on [your topic] from the last 5 years. For each, summarize the key findings, methodology, and limitations in 2-3 sentences."
2. The agent browses Google Scholar, arXiv, and academic databases. It compiles a table of papers with summaries, citation counts, and links.
3. You review the list, identify the most relevant papers, and follow up: "For these 8 papers, write a literature review section that synthesizes their findings and identifies gaps."

Workflow 2: Statistical analysis of survey data

1. Upload a CSV of survey responses. Ask: "Run descriptive statistics on all numeric columns. Then test for significant differences between Group A and Group B using appropriate statistical tests."
2. The agent writes pandas and scipy code, runs it, and returns tables of results with p-values and effect sizes.
3. Follow up: "Create publication-ready charts for the significant findings." The agent generates matplotlib figures with proper labels and formatting.

Self-Hosting vs KiwiClaw for Researchers

Some researchers have the technical skills to self-host. But your time is better spent on research, not infrastructure. KiwiClaw gives you a running agent with code execution in 60 seconds. BYOK at $15/mo keeps costs low on an academic budget. See self-hosting vs KiwiClaw.

Pricing

BYOK — $15/mo. Bring your own API keys. Budget-friendly for academics. All features included.

Standard — $39/mo. Managed LLM access included. No keys to manage. View full pricing details.

FAQ

Can the agent do literature reviews?

The agent browses the web for academic papers, research summaries, and publications on your topic. It cannot access paywalled journals directly, but it can find open-access papers, abstracts, author pages, and pre-prints. It then summarizes findings and identifies themes.

Can it run statistical analysis?

Yes. The agent executes Python with pandas, numpy, scipy, and other statistical libraries. Upload your dataset, describe the analysis, and the agent writes and runs the code. Regression, hypothesis testing, descriptive statistics — all supported.

Does it store my research data securely?

Each KiwiClaw tenant runs in an isolated Fly.io machine. Your data is not shared with other users. For institutional requirements (data residency, compliance), Enterprise tier provides additional guarantees.

Can it help with grant writing?

Yes. The agent can research funding opportunities, analyze successful grant proposals' structures, and draft sections of grant applications. It excels at literature review sections and background research that support your proposal.