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← All cardsDOSSIER · Research assistant · SOLID · VERIFIED 2026-06-09
Consensus58SolidBenchmark pendingCited academic Q&A and claim-level literature scanningVerified 2026-06-09

Dossier · Research assistant

Consensus

Cited academic Q&A and claim-level literature scanning · last verified 2026-06-09

Solid
Research assistant
Consensus
58/100
ROLECited academic Q&A and claim-level literature scanning
Editorial fit
58
Source quality
55
Citation honesty
58
Privacy controls
40
Value for money
70
Speed
58
FREEFree
$15/MOPro (monthly)
$120/YRPro (annual)
SolidVerified 2026-06-09VP·METHOD

VERDICT HISTORY

  • Consensus remains the claim-shaped academic Q&A card. It is strongest when the user has a research question and needs cited orientation quickly. This pass adds current corpus/user-scale claims, Research Agent, account/privacy controls, institutional full-text linking, and a sharper “answer box is not a literature review” warning.
  • Converted imported Notion research into a full flagship-ready dossier template with metrics, panes, pricing deck, scenarios, benchmark rows, and comparison slices.

EDITOR'S NOTE

Consensus is useful when the user has a question rather than keywords. VerdictPal should praise fast, cited orientation while making the user verify the papers before turning an answer box into a claim.

AT A GLANCE

AI academic search engine for cited answers, claim-level literature Q&A, Research Agent workflows, paper analysis, and deeper review-style summaries over a large peer-reviewed research corpus.

Role: Cited academic Q&A and claim-level literature scanningCategory: Research assistantSynthesized

Consensus flagship-ready dossier: Cited academic Q&A and claim-level literature scanning.

PUBLIC FACTS · vendor & repo

List prices and pay-as-you-go entry points we can cite without running our own bench. Each tile links to a source when possible.

Research assistantSetVerdictPal card ↗
synthesizedEvidenceQuality gate ↗
6Sources checkedCard sources ↗
2026-06-07Pricing checkedQuality gate ↗

Limits & product surface

Non-price vendor claims — multipliers, caps, and API scope. Detailed matrices live in subscription and SDK sections below.

Primary surface
consumer-appCard identity ↗
Modalities
textCard identity ↗
Workflow roles
[object Object], [object Object], [object Object]VerdictPal editorial ↗
Alternatives tracked
Elicit, Scite, Semantic Scholar, Perplexity, Connected PapersVerdictPal comparison set ↗

HOW IT WORKS · agent loop

The public positioning for this product — the loop we score against on VerdictPal.

Start with the wedge

Fast yes/no or claim-shaped research questions that need peer-reviewed citations

Run the representative task

Ask 10 yes/no or claim-shaped literature questions in Consensus, Elicit, Google Scholar, and manual library search.

Check the failure modes

AI summaries can over-compress uncertainty

Compare before recommending

Compare against Elicit, Scite, Semantic Scholar before shipping advice.

METRIC LAB · 16 DIMENSIONS

Click a tile for the editorial note. Color follows score: coral, yellow, mint.

Shape

Avg 69 · 40–98

58Editorial fit

Weighted roll-up across 13 dimensions for Research assistant; pending desk verification if rescored from public facts.

By group

Fit78
  • Editorial fit58
  • Wedge task fit82
  • Feature depth94
Cost67
  • Free-tier utility71
  • Cost-to-value70
  • Opportunity cost59
Trust70
  • Source grounding58
  • Privacy posture40
  • Failure transparency98
  • Evidence strength55
  • Transparency98
Workflow64
  • Integration reach60
  • Setup friction58
  • Reliability70
  • Competitive position75
  • Data portability59

SEARCH MODES · 4 lenses

One input box, many retrieval postures. Filter by tier.

01Free

Default

Default path for Consensus — verify limits on the live product.

02Pro

Deep work

Deep work path for Consensus — verify limits on the live product.

03Pro

Focused task

Focused task path for Consensus — verify limits on the live product.

04Free

Export & share

Export & share path for Consensus — verify limits on the live product.

BENCHMARK LEDGER

Public rows are vendor or third-party claims we logged with a date. Desk rows are reserved for VerdictPal self-run results.

MeasureResultSource
Ask 10 yes/no or claim-shaped literature questions in Consensus, Elicit, Google Scholar, and manual library searchsource relevance, answer caution, paper verification effort, missing seminal studies, uncertainty preservation.PlannedVerdictPal benchmark plan
Use Research Agent for 5 complex multi-step research questionssearch planning quality, filter use, citation support, missed branches, reproducibility.PlannedVerdictPal benchmark plan
Test incognito mode, Zotero integration, institution links, history clearing, and account deletiondiscoverability, actual workflow value, privacy friction, export/lock-in.PlannedVerdictPal benchmark plan

PRICING DECK · checked 2026-06-09

Desk pick

Pro (monthly)

$15

month

  • Imported from the current pricing summary.
  • Verify live regional checkout before publishing procurement advice.

Deep (monthly)

$65

month

  • Imported from the current pricing summary.
  • Verify live regional checkout before publishing procurement advice.

RAW · checked 2026-06-09: Current desk price note: Free · Pro $15/mo or $120/yr · Deep $65/mo or $540/yr · Teams custom · Enterprise custom · student discount on Pro with eligibility verification. Re-check live pricing before public publication because quotas and plan names can change.

RESEARCH LOG · desk notes

What we learned while building this dossier — not vendor copy.

Notion Card pipeline ↗

Notion research pass

Consensus remains the claim-shaped academic Q&A card. It is strongest when the user has a research question and needs cited orientation quickly. This pass adds current corpus/user-scale claims, Research Agent, account/privacy controls, institutional full-text linking, and a sharper “answer box is not a literature review” warning.

VerdictPal git ↗

Flagship-ready structure

Converted imported research into metrics, panes, scenarios, benchmark rows, comparison notes, and pricing deck.

COMPETITIVE LENS

Where Consensus wins for cited research — and where a rival still belongs in the stack.

Consensus is stronger when fast yes/no or claim-shaped research questions that need peer-reviewed citations; Elicit may still win for narrower fit, procurement, or specialist depth.

Consensus

  • Fast yes/no or claim-shaped research questions that need peer-reviewed citations
  • Students who need a first-pass literature answer with links back to papers

Elicit

  • You need a full systematic-review workflow with reproducible search strings, screening audit trails, and PRISMA documentation
  • You plan to cite summaries without opening the underlying papers

UNDER THE HOOD

Vendors named on the product about page — useful for procurement and privacy reviews.

claim-level answers
Consensus
literature Q&A
Elicit
study snapshot summaries
Scite

DEEP PANES · 6 LENSES

Editorial lenses only. Subscription and API pricing live in their own sections above.

Lens 01

Positioning

Consensus is framed here as Cited academic Q&A and claim-level literature scanning. Consensus remains the claim-shaped academic Q&A card. It is strongest when the user has a research question and needs cited orientation quickly. This pass adds current corpus/user-scale claims, Research Agent, account/privacy controls, institutional full-text linking, and a sharper “answer box is not a literature review” warning.

Checked
2026-06-07
Evidence
synthesized
  • Fast yes/no or claim-shaped research questions that need peer-reviewed citations
  • Students who need a first-pass literature answer with links back to papers
  • Comparing paper-level evidence before deciding whether to run a deeper review
  • Users who want Research Agent style multi-step search planning and academic filters

TEST SCENARIOS · hands-on lab

How we exercised the product. Step through each run before you trust the scores.

Test run

Step 1 of 4

Start from the persona in best-for item 1.

BEST FOR

  • Fast yes/no or claim-shaped research questions that need peer-reviewed citations
  • Students who need a first-pass literature answer with links back to papers
  • Comparing paper-level evidence before deciding whether to run a deeper review
  • Users who want Research Agent style multi-step search planning and academic filters

AVOID IF

  • You need a full systematic-review workflow with reproducible search strings, screening audit trails, and PRISMA documentation
  • You plan to cite summaries without opening the underlying papers
  • Your topic depends heavily on books, policy documents, grey literature, or sources outside its scholarly corpus
  • You need a completely transparent ranking/corpus methodology for final evidence grading

STRENGTHS

  • AI academic search
  • cited answers
  • Research Agent
  • multi-step search planning
  • Pro Analysis
  • Ask Paper
  • advanced filters
  • paper lists
  • institution links
  • Zotero integration
  • incognito mode
  • history controls

WEAKNESSES

  • AI summaries can over-compress uncertainty
  • Retrieval/ranking can make a field look settled
  • Academic-paper corpus can miss books, policy, and niche sources
  • Agent workflows can still miss important search terms
  • UX may encourage citing answer text instead of papers

HOW IT COULD IMPROVE

  • Summaries that flatten disagreement should preserve the debate, present multiple positions and mark where the literature is contested instead of smoothing it into one answer.
  • Sparse coverage in niche fields is a corpus problem, not an algorithm one. Consensus should surface a coverage-confidence indicator so the reader knows when results are thin rather than pretending otherwise.
  • Metadata quality could be improved with a verification layer that cross-checks imported records against authoritative databases before they enter the library.
  • Privacy posture scores 40/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.

EDITORIAL EVIDENCE · 3 ENTRIES

TASK

Ask 10 yes/no or claim-shaped literature questions in Consensus, Elicit, Google Scholar, and manual library search.

Pending.

↳ source relevance, answer caution, paper verification effort, missing seminal studies, uncertainty preservation.

TASK

Use Research Agent for 5 complex multi-step research questions.

Pending.

↳ search planning quality, filter use, citation support, missed branches, reproducibility.

TASK

Test incognito mode, Zotero integration, institution links, history clearing, and account deletion.

Pending.

↳ discoverability, actual workflow value, privacy friction, export/lock-in.

This tool is in the VerdictPal Citation Fidelity protocol — frozen question bank, dual-reviewer grading, results still pending. Citation Fidelity v0.1 →

PRIVACY DEEP-DIVE · checked 2026-06-09

Consensus privacy policy was last modified 2026-05-15. Existing desk notes state the service encrypts data in transit and at rest, does not sell data, and says it does not use user data to train LLMs including third-party models. Account settings include incognito mode, account deletion, and thread-history clearing.

Training on your dataOff by default
EU data residencyNot documented
SOC 2 attestationNot documented
Local-first by defaultCloud only

WORKFLOW ROLES

How this tool fits into a composed research stack:

claim-level answersliterature Q&Astudy snapshot summaries

QUALITY GATE · SOLID

Evidence ready
Benchmark pending
  • score-revision 2026-06-09: differentiated from public facts; pending desk verification
  • Flagship-quality promotion 2026-06-04: source-backed dossier promoted; benchmark and public recommendation remain locked until evidence packet is complete.
  • Next action: Run claim-shaped question, Research Agent, and privacy/workflow benchmarks.
  • Public recommendation: false
  • evidence-override: Notion source-of-truth sync; evidence remains source-backed until desk benchmark or hands-on pass.
  • Flagship-ready structure generated from Notion deep research and imported git fields on 2026-06-09.

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