{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_findsight-ai","slug":"findsight-ai","name":"Findsight AI","type":"product","url":"https://findsight.ai","page_url":"https://unfragile.ai/findsight-ai","categories":["research-search"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_findsight-ai__cap_0","uri":"capability://search.retrieval.multi.source.idea.comparison.with.disagreement.surfacing","name":"multi-source idea comparison with disagreement surfacing","description":"Ingests non-fiction content from multiple sources and applies semantic similarity matching combined with contradiction detection to identify where expert consensus exists versus where authoritative sources genuinely disagree. The system likely uses embedding-based clustering to group similar claims across sources, then applies logical negation detection or stance classification to surface contradictory assertions rather than just returning independent search results.","intents":["I need to understand where experts actually disagree on a topic, not just find different perspectives","I want to identify which claims in my research are universally accepted versus contested","I'm writing a comparative analysis and need to quickly see which sources contradict each other","I need to validate whether a claim I found is consensus or fringe opinion across multiple authoritative sources"],"best_for":["academic researchers conducting literature synthesis","journalists fact-checking competing narratives","policy analysts mapping stakeholder disagreement","graduate students building comprehensive literature reviews"],"limitations":["Source quality weighting appears uniform — no indication of peer-review status, citation count, or domain authority differentiation","Unclear whether the system distinguishes between genuine disagreement and different framing of the same underlying fact","Limited transparency on how it handles nuanced positions (e.g., 'partially true' vs 'false' vs 'true')","No apparent support for temporal disagreement tracking (how consensus has shifted over time)"],"requires":["Internet connectivity to access source corpus","Query formulated as a clear research question or topic","Willingness to validate results against original sources (no automated credibility scoring visible)"],"input_types":["natural language research question","topic or concept name","comparative claim (e.g., 'does X cause Y?')"],"output_types":["structured comparison showing agreement/disagreement patterns","source citations with quoted excerpts","consensus strength indicators","contradiction mappings between sources"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_findsight-ai__cap_1","uri":"capability://data.processing.analysis.semantic.claim.extraction.and.cross.source.matching","name":"semantic claim extraction and cross-source matching","description":"Parses non-fiction sources to extract discrete factual claims and propositions, then applies semantic similarity matching (likely using dense vector embeddings) to identify the same claim expressed across different sources with different wording. This enables detection of consensus even when sources use different terminology or framing, and supports contradiction detection by matching semantically equivalent but logically opposite claims.","intents":["I want to find all sources making the same claim even if they phrase it differently","I need to know if source A and source B are actually disagreeing or just using different language","I'm tracking how a specific claim appears across multiple publications","I want to extract the core factual assertions from a source for comparison"],"best_for":["researchers comparing how different authors frame the same underlying fact","fact-checkers validating claim consistency across sources","meta-analysts synthesizing findings from heterogeneous studies"],"limitations":["Semantic matching may conflate related-but-distinct claims (e.g., 'X increases Y' vs 'X is correlated with Y')","No apparent handling of conditional claims ('X causes Y in context Z' vs 'X causes Y universally')","Extraction quality depends on source structure — may struggle with implicit claims or claims embedded in narrative","Unknown whether system distinguishes between empirical claims and interpretive/opinion statements"],"requires":["Source text in readable format (likely HTML, PDF, or plain text)","Sufficient source length to extract meaningful claims (likely minimum 500 words)"],"input_types":["full-text non-fiction content","article or book excerpts","research abstracts"],"output_types":["extracted claim statements","semantic similarity scores between claims","source attribution per claim","claim frequency/consensus metrics"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_findsight-ai__cap_2","uri":"capability://search.retrieval.source.aggregation.and.corpus.management","name":"source aggregation and corpus management","description":"Maintains an indexed corpus of non-fiction sources (books, articles, reports) and provides mechanisms to query across this collection. The system likely uses full-text search indexing combined with metadata tagging (author, publication date, domain, source type) to enable filtered retrieval. Architecture probably includes a document store with inverted indices for keyword search and vector indices for semantic search.","intents":["I want to search across a curated collection of authoritative non-fiction sources","I need to filter results by source type, publication date, or domain","I want to ensure I'm comparing sources of similar credibility or relevance","I need to understand what sources the system actually consulted for my query"],"best_for":["researchers who want a pre-curated source collection rather than open web search","users seeking non-fiction specifically (not news, social media, or user-generated content)","teams needing reproducible source attribution"],"limitations":["Source diversity and coverage unknown — may have gaps in specific domains or recent publications","No indication of update frequency for the corpus","Unclear whether sources are weighted by peer-review status, citation count, or domain authority","Free tier may have access to a limited subset of the full corpus","No apparent ability to add custom sources or private documents"],"requires":["Internet connectivity to query the hosted corpus","Acceptance of the platform's source selection and curation decisions"],"input_types":["search query","topic filter","source type filter","date range filter"],"output_types":["ranked list of relevant sources","source metadata (author, publication, date)","excerpt snippets with context","source credibility indicators (if available)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_findsight-ai__cap_3","uri":"capability://data.processing.analysis.consensus.strength.quantification.and.visualization","name":"consensus strength quantification and visualization","description":"Analyzes the distribution of claims and positions across sources to compute consensus metrics (e.g., percentage of sources agreeing, strength of agreement, outlier detection). Likely uses statistical aggregation of claim frequencies and semantic similarity scores to produce quantitative measures of how universal a position is. Results are probably visualized as agreement/disagreement matrices or consensus strength indicators to make patterns immediately apparent.","intents":["I want to know what percentage of sources agree on a specific claim","I need to identify outlier or minority positions on a topic","I want to see at a glance which claims are consensus vs contested","I need to quantify the strength of disagreement for my analysis"],"best_for":["researchers building evidence-based arguments and needing to cite consensus strength","policy makers assessing the state of expert opinion","journalists reporting on areas of genuine scientific or expert disagreement"],"limitations":["Consensus metrics are only as good as the underlying source corpus — biased corpus produces biased consensus measures","No apparent weighting by source credibility, so a fringe blog and a peer-reviewed journal count equally","Consensus strength may be misleading if sources are clustered by ideology or funding rather than evidence","Unknown whether system accounts for source interdependence (e.g., multiple sources citing the same original study)"],"requires":["Minimum number of sources discussing the topic (threshold unknown)","Sufficient claim extraction quality to enable meaningful aggregation"],"input_types":["topic or claim","set of sources to analyze"],"output_types":["consensus percentage or strength score","agreement/disagreement distribution","outlier source identification","visual consensus maps or matrices"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_findsight-ai__cap_4","uri":"capability://data.processing.analysis.contradiction.detection.and.logical.stance.classification","name":"contradiction detection and logical stance classification","description":"Identifies logically opposite or contradictory claims across sources using semantic matching combined with negation detection and stance classification. The system likely applies NLP techniques to detect when two semantically similar claims have opposite truth values (e.g., 'X causes Y' vs 'X does not cause Y'), and may use machine learning classifiers trained to recognize pro/con/neutral stances on specific propositions.","intents":["I want to find sources that directly contradict each other on a specific claim","I need to understand the nature of disagreement — is it empirical or interpretive?","I want to identify which sources take opposing positions on a policy question","I need to flag genuine contradictions for further investigation"],"best_for":["fact-checkers investigating conflicting claims","researchers mapping the landscape of scholarly disagreement","policy analysts understanding stakeholder opposition","journalists reporting on controversial topics with competing expert views"],"limitations":["Negation detection may fail on implicit contradictions or subtle disagreements","No apparent distinction between direct contradiction and mere disagreement about degree/magnitude","Stance classification may struggle with nuanced positions that are neither clearly pro nor con","Unknown whether system handles temporal contradictions (source A was right in 2010, source B is right in 2024)","May produce false positives if sources are discussing different aspects of a complex topic"],"requires":["Sufficient semantic similarity between claims to enable matching","Clear logical structure in source claims (implicit or embedded contradictions may be missed)"],"input_types":["topic or claim","set of sources to analyze for contradictions"],"output_types":["pairs of contradictory claims with sources","contradiction strength/confidence scores","stance labels (pro/con/neutral) per source","contradiction type classification (empirical vs interpretive)"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_findsight-ai__cap_5","uri":"capability://automation.workflow.free.tier.research.exploration.with.limited.scope","name":"free-tier research exploration with limited scope","description":"Provides a free tier that allows users to perform a limited number of research queries and comparisons without authentication or payment. The free tier likely has constraints on query frequency, number of sources returned, or depth of analysis, but removes friction for initial evaluation. This is a product/business model capability that enables user acquisition and validation of the tool's utility before conversion to paid plans.","intents":["I want to test whether this tool actually solves my research problem before paying","I need to run a quick comparison on a single topic without committing resources","I want to evaluate the quality of sources and analysis before subscribing","I'm a student or independent researcher with limited budget"],"best_for":["individual researchers and students evaluating the tool","teams doing proof-of-concept before enterprise adoption","users with occasional research needs rather than high-volume usage"],"limitations":["Free tier scope unknown — unclear whether it's 5 queries/month or 50","May have reduced source corpus access on free tier","Likely no export, API access, or integration capabilities on free tier","No indication of whether free tier results are cached/delayed vs real-time","Conversion funnel may be designed to make paid tier feel necessary for serious research"],"requires":["No payment method required for free tier","Likely requires email signup or account creation"],"input_types":["research query","topic for comparison"],"output_types":["limited comparison results","source excerpts","basic consensus metrics"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Internet connectivity to access source corpus","Query formulated as a clear research question or topic","Willingness to validate results against original sources (no automated credibility scoring visible)","Source text in readable format (likely HTML, PDF, or plain text)","Sufficient source length to extract meaningful claims (likely minimum 500 words)","Internet connectivity to query the hosted corpus","Acceptance of the platform's source selection and curation decisions","Minimum number of sources discussing the topic (threshold unknown)","Sufficient claim extraction quality to enable meaningful aggregation","Sufficient semantic similarity between claims to enable matching"],"failure_modes":["Source quality weighting appears uniform — no indication of peer-review status, citation count, or domain authority differentiation","Unclear whether the system distinguishes between genuine disagreement and different framing of the same underlying fact","Limited transparency on how it handles nuanced positions (e.g., 'partially true' vs 'false' vs 'true')","No apparent support for temporal disagreement tracking (how consensus has shifted over time)","Semantic matching may conflate related-but-distinct claims (e.g., 'X increases Y' vs 'X is correlated with Y')","No apparent handling of conditional claims ('X causes Y in context Z' vs 'X causes Y universally')","Extraction quality depends on source structure — may struggle with implicit claims or claims embedded in narrative","Unknown whether system distinguishes between empirical claims and interpretive/opinion statements","Source diversity and coverage unknown — may have gaps in specific domains or recent publications","No indication of update frequency for the corpus","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:30.892Z","last_scraped_at":"2026-04-05T13:23:42.561Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=findsight-ai","compare_url":"https://unfragile.ai/compare?artifact=findsight-ai"}},"signature":"9UBvDia1jmhp07SvSKd6Ix1zTJfN4CZALKSH6ur7rQrwLSsr6JswP62CQIBpfrXlRWjGFrYbf9my15UydvE7BA==","signedAt":"2026-06-21T17:22:44.428Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/findsight-ai","artifact":"https://unfragile.ai/findsight-ai","verify":"https://unfragile.ai/api/v1/verify?slug=findsight-ai","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}