# Lune vs Paperguide

Lune records 6,340 monthly visits with -28% month-over-month growth and Freemium pricing. Paperguide records 371,972 monthly visits with -2.9% growth and Freemium pricing.

| Metric | [Lune](https://openaitools.app/tool/lune) | [Paperguide](https://openaitools.app/tool/paperguide) |
| :--- | :--- | :--- |
| Website URL | https://luneresearch.com | https://paperguide.ai// |
| Categories | AI Research Tool, AI Research Papers, AI Search Engine, AI Knowledge Base | AI Research Tool, AI Assistant, AI Writing Assistants, AI Papers |
| Pricing Model | Freemium | Freemium |
| Monthly Visits | 6,340 | 371,972 |
| MoM Growth Rate | -28% | -2.9% |
| Primary Market | United States | United States |
| Direct Visits | 941 | 121,585 |
| Review Score | 4.3 | 4.4 |
| Saved Count | 0 | 1 |
| Supported Platforms | Website | Website |

## Lune

Lune takes a deliberately narrow approach to AI research. Instead of crawling the open web, it indexes full texts from A/A* computer science venues — security, systems, machine learning, HCI, databases, theory and more — and exposes them to AI agents through a connector, an MCP server and a CLI. The result is an agent that can quote real paper text, trace a citation chain, and tell you which prior work makes an idea feel derivative.

The product is built around four research stages: literature review, brainstorming, experimentation and writing. For a literature review, Lune retrieves foundational papers and shows what they actually claim, with the passage it is drawing from. For brainstorming, it checks an idea against prior work and points at a specific gap — for example, that a method is brittle under domain shift and rarely evaluated cost-aware. For experimentation, it surfaces the baselines and controls reviewers expect. For writing, it helps position a method against named prior work with citations verified against the sources.

Beyond search, Lune offers a talent database of researchers with full publication records and contact information, plus venue listings for the conferences it indexes. It is aimed at students, academic researchers and applied AI teams who need trustworthy grounding rather than fluent guesses. Access is freemium: there is a free entry point and paid plans for heavier use, so check the current pricing page for limits and tiers.

**Pricing & Plans:** Freemium. There is a free entry point, with paid plans for heavier agent use and access to the full dataset. Check luneresearch.com/pricing for current tiers and limits.

- **Full-text semantic search:** Ask in plain language and Lune searches the full text of papers from top-tier venues all at once, rather than matching keywords against titles and abstracts.
- **Citation tracing:** See what a paper builds on and what later work builds on it, so you can place a result in its research lineage instead of treating it as an isolated claim.
- **Agent connector and MCP server:** Lune connects to Claude, ChatGPT and other MCP-capable clients, so your agent can pull real paper text and best-practice guidance mid-task.
- **Research best-practices library:** Battle-tested guidance on novelty checks, baselines, ablations and reviewer expectations is surfaced at the moment it is relevant, not buried in a wiki.
- **Researcher talent database:** Search leading computer scientists by research area, school or name, and check publication track records with contact details for outreach.

**Strengths:** Answers are grounded in the actual full text of peer-reviewed papers, with sources you can check; Connects to Claude, ChatGPT and other MCP clients so it works inside the agent you already use; Best-practice libraries cover the unglamorous things reviewers punish, such as missing baselines and weak novelty arguments; Researcher talent database with publication records and contact details is unusual and genuinely useful

**Limitations:** Centered on top-tier computer science venues, so researchers in other fields may find coverage thin; Requires connecting an agent (Claude, ChatGPT or a compatible MCP client) to get the most from it; Most value depends on an existing AI agent and a paid plan; the free tier is limited; Not a general web search engine — it deliberately ignores blogs, forums and non-archival sources

[Profile (Markdown)](https://openaitools.app/tool/lune.md)

## Paperguide

Paperguide has evolved from a general-purpose "chat with your PDF" study assistant into a research platform aimed squarely at rigorous evidence work. Its current centrepiece is Systematic Review: you define a protocol, run a documented search, screen abstracts and full texts with per-criterion evidence prepared by AI, resolve conflicts between two independent reviewers, and finish with verified extraction tables plus a PRISMA flow diagram generated from your own counts. The design principle is that AI prepares evidence but never casts the decisive vote — every screening call, extracted value and synthesized claim is traceable to a named source statement and a human verifier.

The rest of the product supports that workflow from the front end. AI Search answers plain-language research questions across more than 200 million peer-reviewed papers with each assertion linked to its source; the Reference Manager imports from Zotero or Mendeley, adds papers by DOI and fetches open-access PDFs automatically; Extract Data turns a stack of PDFs into a structured, cited comparison table you can export to CSV or Excel; and the Research Agent handles multi-step literature reviews up to 50 papers, organized by theme.

Paperguide also ships an AI Writer for citation-grounded drafting, an MCP integration, and a plagiarism checker, with shared team workspaces that keep papers, annotations and reviews attached to the project rather than to one person's account. It is used by academic researchers along with medical device, HEOR, pharma and government policy teams, and reports over one million researchers on the platform. Pricing runs from a free tier through Plus, Pro, Evidence Teams and custom Enterprise plans billed per seat annually.

**Pricing & Plans:** Freemium with a free plan (1,500 AI credits per month plus limited agents and reference manager) and paid per-seat tiers billed annually: Plus around $12/seat/month, Pro around $29/seat/month, Evidence Teams around $89/seat/month with dual-reviewer screening, and custom Enterprise pricing. Yearly billing advertises savings up to 41%.

- **AI Search over 200M+ papers:** Ask a research question in plain language and get a synthesized answer drawn from PubMed, arXiv, OpenAlex and Semantic Scholar, with every claim linked to its source paper.
- **Auditable Systematic Review:** Run PRISMA-style reviews with a predefined protocol, recorded screening decisions, dual independent reviewers and a conflict resolver, and a PRISMA diagram generated from your actual counts.
- **AI-native Reference Manager:** Import from Zotero or Mendeley, add papers by DOI, and get metadata and open-access PDFs fetched automatically, with annotations and notes that feed every other workflow.
- **Cited data extraction tables:** Define custom extraction columns and have AI fill them across many papers, with each value linking back to the sentence it came from, exportable to CSV or Excel.
- **Citation-grounded AI Writer:** Draft from your own library and 200M+ papers in the same document, switching between 1,000+ citation styles without manual reformatting and without invented references.

**Strengths:** Statement-level traceability: click any claim to land on the exact source sentence; Combines search, reference management, extraction and writing in one workspace; Per-criterion evidence speeds up abstract screening and improves reviewer consistency; Free tier is genuinely usable, and annual billing discounts are generous

**Limitations:** Credit-based limits can be reached quickly on heavy research-agent usage; The advanced systematic review features and dual review sit behind the pricier team tiers; It is primarily English-oriented, which may suit non-English primary research less well; Newer compliance certifications such as SOC 2 and ISO 27001 are still listed as coming soon

[Profile (Markdown)](https://openaitools.app/tool/paperguide.md)

## Frequently Asked Questions

### How do Lune and Paperguide compare in monthly traffic?

Lune has 6,340 monthly visits, while Paperguide has 371,972. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Lune has a month-over-month growth rate of -28%; Paperguide has -2.9%.

### How does pricing compare?

Lune: Freemium. Freemium. There is a free entry point, with paid plans for heavier agent use and access to the full dataset. Check luneresearch.com/pricing for current tiers and limits. Paperguide: Freemium. Freemium with a free plan (1,500 AI credits per month plus limited agents and reference manager) and paid per-seat tiers billed annually: Plus around $12/seat/month, Pro around $29/seat/month, Evidence Teams around $89/seat/month with dual-reviewer screening, and custom Enterprise pricing. Yearly billing advertises savings up to 41%.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Perplexity](https://openaitools.app/tool/perplexity-ai) | 88,310,223 | -3.7% | Freemium | Real-time AI answer engine and research workspace combining live web citations with frontier reasoning models. | [.md](https://openaitools.app/tool/perplexity-ai.md) |
| 2 | [Semantic Scholar](https://openaitools.app/tool/semantic-scholar) | 8,198,672 | +5.8% | Free | A free, AI-powered academic search engine for 240M+ papers across every scientific field | [.md](https://openaitools.app/tool/semantic-scholar.md) |
| 3 | [Consensus](https://openaitools.app/tool/consensus) | 6,014,388 | -1.2% | Freemium | Superior for quick evidence-based academic search, but less of a comprehensive writing and reference suite. | [.md](https://openaitools.app/tool/consensus.md) |
| 4 | [SciSpace](https://openaitools.app/tool/scispace) | 4,464,111 | +8.6% | Freemium | Offers robust PDF analysis and literature search workspaces, but lacks advanced systematic review screening workflows. | [.md](https://openaitools.app/tool/scispace.md) |
| 5 | [Elicit](https://openaitools.app/tool/elicit) | 1,751,507 | +3.1% | Freemium | Stronger automated evidence synthesis and systematic review extraction, but less focused on end-to-end reference management. | [.md](https://openaitools.app/tool/elicit.md) |
| 6 | [Jenni](https://openaitools.app/tool/jenni) | 1,498,133 | +5.2% | Freemium | Stronger AI academic writing and autocomplete assistance, but less comprehensive for systematic literature mapping. | [.md](https://openaitools.app/tool/jenni.md) |
| 7 | [Rayyan](https://openaitools.app/tool/rayyan) | 1,116,437 | +7.9% | Freemium | Industry standard for systematic review screening and deduplication, but weaker on AI writing generation. | [.md](https://openaitools.app/tool/rayyan.md) |
| 8 | [Scite](https://openaitools.app/tool/scite) | 841,974 | +1.1% | Free Trial, Contact for Pricing | Excellent smart citation analysis to verify if papers support or dispute claims, but narrower writing capabilities. | [.md](https://openaitools.app/tool/scite.md) |
| 9 | [ResearchRabbit](https://openaitools.app/tool/researchrabbit) | 831,571 | +3.1% | Free | Free visual research discovery and literature mapping tool, but offers less automated evidence synthesis and writing. | [.md](https://openaitools.app/tool/researchrabbit.md) |
| 10 | [Connected Papers](https://openaitools.app/tool/connected-papers) | 750,576 | +3.1% | Freemium | Unmatched visual literature discovery and graph mapping, but lacks document drafting and reference management features. | [.md](https://openaitools.app/tool/connected-papers.md) |

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Source: https://openaitools.app/compare/lune-vs-paperguide

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