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VerdictPal · editorial desk · 2026VerdictPal
Compare · Head-to-head

Pick two cards. See the diff.

Stat bars are editorial heuristics, methodology linked — not a fake benchmark leaderboard. Put two dossiers side by side and see where each one breaks.
CardsModels

Compare · Card A / Card B·Head-to-head

ScholarcyvsSemantic Scholar

These cards sit in different sets (Paper tools vs Academic search), so picking one over the other is mostly a question of which job you're doing. Semantic Scholar wins on citation honesty, privacy controls, speed, and value for money; the rest is a wash. Both pass our quality gate. The right pick is the one whose strengths match the job you're trying to do.

Scholarcy · avg
73
wins 7 of 16
Semantic Scholar · avg
74
wins 6 of 16
Fields differ
12
of 16 dossier rows
Receipts
18
sources + bench notes

Checked 2026-06-09 · Scholarcy·Checked 2026-06-09 · Semantic Scholar

Dossier fields

Sixteen fields, side by side.

No.FieldScholarcySemantic Scholar
01Status · Editorial quality gateSolidSolid
02Editorial fit · 0–100 score79 / 10078 / 100
03CategoryPaper toolsAcademic search
04Primary surfaceProsumer SaaSOpen data
05Modalities
  • Text
  • Data
  • Text
  • Data
06Role in a stackPaper-skimming and structured-summary assistantAI-powered academic search and open bibliography graph
07Best for
  • Students who need to triage long papers before deciding what to read closely
  • Literature-skim workflows where structured flashcards, key points, and exports save time
  • Accessibility-oriented workflows that benefit from shorter, organized summaries of dense text
  • Users who want a browser extension, library, bibliography, and literature-matrix workflow around summaries
  • Finding papers, author pages, citations, TLDRs, and related work in a free academic search UI
  • Developers who need programmatic scholarly graph access for papers, authors, citations, recommendations, or discovery features
  • Students who want a cleaner and more structured scholarly search layer than Google Scholar for quick triage
  • Academic discovery products that need open graph data but can respect Ai2 license and API constraints
08Avoid if
  • You plan to cite summaries without reading the paper’s methods, limitations, and original claims
  • Your PDFs are copyrighted/library-licensed and should not be uploaded to a third-party summarizer
  • You need systematic extraction accuracy rather than reading support
  • You need a tool that can certify evidence quality, not just summarize and organize
  • You need the broadest possible scholarly web coverage rather than an Ai2-indexed corpus
  • You need high-throughput API access without key management, rate-limit planning, or license review
  • You need final bibliographic authority without checking DOI registries or publisher pages
  • You work in fields where books, policy, or non-indexed humanities sources dominate
09Capabilities tracked
  • PDF/article/chapter/webpage/video/document summarization
  • flashcards
  • smart highlighting
  • library
  • browser extension
  • Scholarcy API
  • free Article Summarizer 1 summary/day
  • 7-day paid trial
  • unlimited summaries on paid plans
  • bibliographies
  • literature matrix
  • exports
  • reference extraction
  • Free academic search
  • paper pages
  • citation/reference graphs
  • TLDR summaries
  • author profiles
  • saved papers
  • alerts
  • Academic Graph API
  • downloadable datasets
  • Semantic Reader / experimental reading features
10Failure modes · Documented, not buried
  • Summaries can omit caveats and methods details
  • Uploading publisher PDFs can raise copyright/license/privacy concerns
  • Scholarcy logs IP and URL or filename for processed files
  • Browser extension can expose reading behavior/page URLs
  • Invoice records retained 7 years after deletion for compliance
  • Good skim quality is not evidence extraction quality
  • TLDRs can hide methods/caveats
  • Coverage incomplete for books/humanities/niche venues
  • Metadata and author disambiguation can be wrong
  • API/dataset license restrictions matter
  • Citation graphs are relationships, not quality signals
  • Rate limits constrain serious pipelines
11Evidence levelSynthesizedEditorial · hands-on
12Sources verified · Receipts on the dossier
13Benchmark entries
  • Summarize 10 papers and compare abstract, methods, results, limitations, references, and caveats against manual notes.
    Pending.
  • Use the browser extension on OA articles, publisher pages, and PDFs.
    Pending.
  • Import a small paper set, generate summaries, bibliographies, and a literature matrix.
    Pending.
  • Run 20 known-paper queries across Semantic Scholar, Google Scholar, OpenAlex, and Crossref.
    Pending.
  • For 10 focal papers, inspect references, citations, related papers, and author graph quality.
    Pending.
  • Compare TLDRs against abstracts and methods for 25 papers.
    Pending.
  • Build a small paper-recommendation pipeline with the API.
    Pending.
14Alternatives tracked
  • Elicit
  • Semantic Scholar
  • NotebookLM
  • ChatPDF
  • Zotero
  • Google Scholar
  • OpenAlex
  • Connected Papers
  • Elicit
  • Consensus
15Pricing checked2026-06-092026-06-09
16Last verified2026-06-092026-06-09
16 metrics

Sixteen numbers, one shared midline.

ScholarcyvsSemantic Scholar

These cards sit in different sets (Paper tools vs Academic search), so picking one over the other is mostly a question of which job you're doing. Semantic Scholar wins on citation honesty, privacy controls, speed, and value for money; the rest is a wash. Both pass our quality gate. The right pick is the one whose strengths match the job you're trying to do.

  1. Editorial fit
    Scholarcy79Semantic Scholar78
  2. Source quality
    Scholarcy55Semantic Scholar52
  3. Citation honesty
    Scholarcy70Semantic Scholar86
  4. Privacy controls
    Scholarcy40Semantic Scholar56
  5. Value for money
    Scholarcy90Semantic Scholar94
  6. Speed
    Scholarcy70Semantic Scholar86
  7. Integration
    Scholarcy87Semantic Scholar67
  8. Onboarding
    Scholarcy70Semantic Scholar86
  9. Reliability
    Scholarcy70Semantic Scholar70
  10. Feature depth
    Scholarcy100Semantic Scholar91
  11. Data portability
    Scholarcy77Semantic Scholar73
  12. Transparency
    Scholarcy100Semantic Scholar86
  13. Ecosystem reach
    Scholarcy87Semantic Scholar67
  14. Documentation
    Scholarcy55Semantic Scholar52
  15. Independence
    Scholarcy40Semantic Scholar56
  16. Affordability
    Scholarcy79Semantic Scholar81
Scholarcy · avg 73 · wins 7 of 160avg 74 · wins 6 of 16 · Semantic Scholar
EvidenceScholarcy 1 · Semantic Scholar 2
  1. 01Editorial fit
    79
    78
  2. 02Source quality
    55
    52
  3. 03Citation honesty
    70
    86
  4. 04Privacy controls
    40
    56
PrivacyScholarcy 1 · Semantic Scholar 3
  1. 05Value for money
    90
    94
  2. 06Speed
    70
    86
  3. 07Integration
    87
    67
  4. 08Onboarding
    70
    86
CapabilityScholarcy 3 · Semantic Scholar 0
  1. 09Reliability
    70
    70
  2. 10Feature depth
    100
    91
  3. 11Data portability
    77
    73
  4. 12Transparency
    100
    86
Cost & fitScholarcy 2 · Semantic Scholar 1
  1. 13Ecosystem reach
    87
    67
  2. 14Documentation
    55
    52
  3. 15Independence
    40
    56
  4. 16Affordability
    79
    81
CARD A · Scholarcy
Paper tools
Scholarcy
79/100
ROLEPaper-skimming and structured-summary assistant
Editorial fit
79
Source quality
55
Citation honesty
70
Privacy controls
40
Value for money
90
Speed
70
FREEExtension
CUSTOMLibrary
CUSTOMInstitutional
SolidVerified 2026-06-09VP·METHOD

Paper-skimming and structured-summary assistant — Paper and document summarization tool that turns PDFs, articles, chapters, webpages, and other sources into structured summary flashcards, smart highlights, bibliographies, literature matrices, exports, and saved library items.

CARD B · Semantic Scholar
Academic search
Semantic Scholar
78/100
ROLEAI-powered academic search and open bibliography graph
Editorial fit
78
Source quality
52
Citation honesty
86
Privacy controls
56
Value for money
94
Speed
86
FREEWeb & alerts
FREEGraph API
FREEBulk datasets
SolidVerified 2026-06-09VP·METHOD

AI-powered academic search and open bibliography graph — Free Ai2 academic search engine and scholarly graph with paper search, TLDRs, author pages, alerts, citation graphs, API access, and downloadable datasets.

Privacy facets

Where each card is actually private.

ScholarcySemantic Scholar
Training on your dataUnknownUnknown: Not statedUnknownUnknown: Not stated
EU data residencyNoNo: Not documentedNoNo: Not documented
SOC 2 attestationNoNo: Not documentedNoNo: Not documented
Local-first by defaultNoNo: Cloud onlyNoNo: Cloud only
Capability split

What each card does uniquely.

Only Scholarcy13

  • PDF/article/chapter/webpage/video/document summarization
  • flashcards
  • smart highlighting
  • library
  • browser extension
  • Scholarcy API
  • free Article Summarizer 1 summary/day
  • 7-day paid trial
  • unlimited summaries on paid plans
  • bibliographies
  • literature matrix
  • exports
  • reference extraction

Shared0

No overlap detected.

Only Semantic Scholar10

  • Free academic search
  • paper pages
  • citation/reference graphs
  • TLDR summaries
  • author profiles
  • saved papers
  • alerts
  • Academic Graph API
  • downloadable datasets
  • Semantic Reader / experimental reading features
Failure modes

Where each card breaks.

Scholarcy

  • Summaries can omit caveats and methods details
  • Uploading publisher PDFs can raise copyright/license/privacy concerns
  • Scholarcy logs IP and URL or filename for processed files
  • Browser extension can expose reading behavior/page URLs
  • Invoice records retained 7 years after deletion for compliance
  • Good skim quality is not evidence extraction quality

Semantic Scholar

  • TLDRs can hide methods/caveats
  • Coverage incomplete for books/humanities/niche venues
  • Metadata and author disambiguation can be wrong
  • API/dataset license restrictions matter
  • Citation graphs are relationships, not quality signals
  • Rate limits constrain serious pipelines
Pricing

Pulled straight from each dossier.

Scholarcy

Paper tools
  • FREEExtension
  • CUSTOMLibrary
  • CUSTOMInstitutional

raw · Free article summarizer allows up to 1 summary/day. Scholarcy offers a 7-day trial for paid use. Paid Scholarcy/Scholarcy Plus/Library subscriptions unlock unlimited summaries and more features; current public pricing should be verified live before publication.

Semantic Scholar

Academic search
  • FREEWeb & alerts
  • FREEGraph API
  • FREEBulk datasets

raw · Semantic Scholar web product is free. Academic Graph API and downloadable datasets are available for developer use, with API keys/rate limits and license constraints. Existing desk notes track default API key limit at 1 request/second with higher limits by review; re-check live docs before publishing throughput guidance.

Verdict

Which card to actually pick.

These cards sit in different sets (Paper tools vs Academic search), so picking one over the other is mostly a question of which job you're doing. Semantic Scholar wins on citation honesty, privacy controls, speed, and value for money; the rest is a wash. Both pass our quality gate. The right pick is the one whose strengths match the job you're trying to do.

Open Scholarcy's dossierOpen Semantic Scholar's dossier
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