{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-athena-intelligence","slug":"athena-intelligence","name":"Athena Intelligence","type":"agent","url":"https://www.athenaintelligence.ai/","page_url":"https://unfragile.ai/athena-intelligence","categories":["data-analysis"],"tags":[],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-athena-intelligence__cap_0","uri":"capability://data.processing.analysis.autonomous.document.extraction.and.structuring","name":"autonomous-document-extraction-and-structuring","description":"Automatically ingests unstructured documents (PDFs, reports, earnings calls, contracts) from enterprise systems and extracts structured data into spreadsheets and tables without manual configuration. The system appears to use document parsing combined with LLM-based semantic understanding to identify relevant fields, entities, and relationships, then outputs itemized data in standardized formats. Supports bulk processing of heterogeneous document types across finance, legal, and market research domains.","intents":["I need to extract financial figures from 50+ earnings reports and consolidate them into a single spreadsheet without manual copy-paste","I want to convert PDFs containing contract clauses into a structured ledger that flags key provisions automatically","I need to pull pack-price-volume data from market reports and organize it by SKU, channel, and time period"],"best_for":["enterprise financial analysts processing high-volume earnings filings","legal teams conducting due diligence on contract portfolios","CPG/sales teams analyzing competitive pack-price data across regions"],"limitations":["No disclosed accuracy metrics or confidence scores — unclear how hallucinations are mitigated in extracted data","Maximum document size and batch volume limits not specified","Requires pre-integration with enterprise document systems; no standalone file upload mentioned","Output format customization approach unknown — unclear if users can define custom extraction schemas","No audit trail or explainability for why specific fields were extracted or how confidence was determined"],"requires":["Active integration with enterprise document management system (Sharepoint, OneDrive, etc.) — specific connectors unknown","SOC 2 Type II and HIPAA compliance environment (product certified but deployment requirements unclear)","Existing enterprise data systems to write extracted data to (Salesforce, data warehouse, etc.)"],"input_types":["PDF documents","Word documents","Unstructured text reports","Earnings call transcripts","Contract documents","Market research reports"],"output_types":["Structured spreadsheets (CSV, Excel implied)","Itemized tables","Flagged/annotated documents","Extracted entity lists"],"categories":["data-processing-analysis","document-processing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_1","uri":"capability://data.processing.analysis.multi.document.financial.analysis.synthesis","name":"multi-document-financial-analysis-synthesis","description":"Aggregates and synthesizes financial data across multiple earnings reports, SEC filings, and consulting reports to extract key metrics (revenue, margins, growth rates), identify management sentiment and forward guidance, and generate comparative analysis across companies or time periods. The system performs cross-document reasoning to identify trends, anomalies, and relationships that would require manual review across dozens of documents. Outputs structured financial reports and insight summaries.","intents":["I need to compare revenue growth and margin trends across 10 competitors' last 8 quarters of earnings reports","I want to extract management sentiment on specific business segments from earnings call transcripts and correlate it with actual performance","I need to identify which companies are guiding down on specific product categories based on earnings call language"],"best_for":["equity research teams and investment analysts","corporate development teams evaluating acquisition targets","CFO offices tracking competitive financial performance"],"limitations":["No disclosed context window size — unclear how many documents can be analyzed in a single synthesis pass","Sentiment analysis approach not specified — unclear if it uses fine-tuned models or general-purpose LLM sentiment","No accuracy benchmarks provided for financial metric extraction or sentiment classification","Requires documents to already be integrated into Olympus platform; no ad-hoc document upload for one-off analysis","No mention of real-time earnings data feeds — appears to be batch-oriented rather than live monitoring"],"requires":["Integration with enterprise document repository containing earnings reports and SEC filings","Access to earnings call transcripts (source not specified — assumes internal repository or third-party feed)","Existing data warehouse or BI tool to consume synthesized financial reports"],"input_types":["Earnings reports (10-Q, 10-K filings)","Earnings call transcripts","Consulting reports","Market research studies","Internal financial models"],"output_types":["Comparative financial tables","Trend analysis reports","Sentiment summaries","Anomaly flags","Forward guidance extracts"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_10","uri":"capability://data.processing.analysis.sentiment.analysis.for.trend.identification","name":"sentiment-analysis-for-trend-identification","description":"Analyzes text content (earnings calls, news articles, market research, consumer feedback) to extract sentiment signals and identify emerging trends or shifts in market perception. The system performs semantic sentiment analysis to distinguish between positive/negative sentiment and identify sentiment drivers (specific products, features, competitive threats). Outputs sentiment trends, driver analysis, and anomaly flags.","intents":["I need to track sentiment trends in earnings call language to identify when management confidence is declining","I want to identify emerging consumer concerns or product issues based on sentiment analysis of social media and review data","I need to understand how market sentiment toward our category is shifting based on news and analyst commentary"],"best_for":["market research teams identifying emerging trends","investor relations teams monitoring analyst sentiment","product teams tracking consumer perception shifts"],"limitations":["Sentiment model type not specified — unclear if it uses fine-tuned models, general-purpose LLM sentiment, or domain-specific classifiers","No accuracy metrics for sentiment classification or trend detection","Unclear how system handles sarcasm, context-dependent sentiment, or mixed sentiment","No mention of how system identifies sentiment drivers or root causes","Unclear how system handles multiple languages or regional variations","No mention of real-time vs. batch sentiment analysis"],"requires":["Integration with text data sources (earnings calls, news feeds, social media, reviews) — specific sources not listed","Text data in structured format (transcripts, articles, posts)","Domain expertise to validate sentiment signals and identify actionable trends"],"input_types":["Earnings call transcripts","News articles","Social media posts","Customer reviews","Market research reports","Analyst commentary"],"output_types":["Sentiment trend reports","Sentiment driver analysis","Anomaly alerts","Trend summaries","Perception shift reports"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_11","uri":"capability://data.processing.analysis.consumer.insights.gathering.and.analysis","name":"consumer-insights-gathering-and-analysis","description":"Aggregates consumer data from multiple sources (surveys, focus groups, social media, reviews, purchase behavior) and synthesizes insights about consumer preferences, pain points, and emerging needs. The system performs cross-source analysis to identify patterns and validate insights across data types. Outputs consumer segment profiles, need statements, and opportunity assessments.","intents":["I need to understand what consumer segments value most about our product category and how that's changing","I want to identify unmet consumer needs that represent product innovation opportunities","I need to synthesize consumer feedback from surveys, social media, and focus groups into actionable insights"],"best_for":["product teams identifying innovation opportunities","marketing teams developing consumer-centric strategies","market research teams synthesizing consumer insights"],"limitations":["Data source integration not specified — unclear which consumer data sources are supported","Insight synthesis methodology not documented — unclear if it uses statistical analysis, semantic clustering, or rule-based logic","No accuracy metrics for consumer segment identification or need validation","Unclear how system handles conflicting insights across data sources","No mention of how system validates insights or assesses confidence","Unclear how system handles privacy/PII in consumer data"],"requires":["Integration with consumer data sources (surveys, social listening, purchase data, reviews) — specific sources not listed","Consumer data in structured or semi-structured format","Domain expertise to validate insights and prioritize opportunities"],"input_types":["Survey responses","Focus group transcripts","Social media data","Product reviews","Purchase behavior data","Customer feedback"],"output_types":["Consumer segment profiles","Need statements","Opportunity assessments","Insight summaries","Trend reports"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_12","uri":"capability://planning.reasoning.content.strategy.development.and.optimization","name":"content-strategy-development-and-optimization","description":"Analyzes content performance data, audience engagement metrics, and competitive content to develop content strategies and optimize distribution. The system identifies high-performing content themes, audience segments, and distribution channels, then recommends content topics and formats. Outputs content strategy recommendations, editorial calendars, and performance benchmarks.","intents":["I need to understand what content topics and formats drive the most engagement with our audience","I want to develop a content strategy that differentiates us from competitors and resonates with target segments","I need to optimize our content distribution across channels based on audience engagement patterns"],"best_for":["media and publishing companies optimizing content strategy","marketing teams developing content-driven campaigns","editorial teams planning content calendars"],"limitations":["Content performance analysis methodology not documented","No mention of how system identifies high-performing content themes or audience segments","Unclear how system handles different content types (articles, video, social, etc.)","No accuracy metrics for content recommendation or performance prediction","Unclear how system incorporates competitive content analysis","No mention of real-time vs. batch content analysis"],"requires":["Integration with content management system and analytics platform","Content performance data (views, engagement, conversions, etc.)","Audience segmentation data","Competitive content data (source not specified)"],"input_types":["Content performance metrics","Audience engagement data","Content metadata (topic, format, channel, etc.)","Competitive content data","Audience segment data"],"output_types":["Content strategy recommendations","Editorial calendars","Topic recommendations","Format recommendations","Distribution optimization"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_13","uri":"capability://data.processing.analysis.brand.positioning.and.perception.analysis","name":"brand-positioning-and-perception-analysis","description":"Analyzes brand perception data from multiple sources (surveys, social media, news, competitor positioning) to assess brand positioning, identify perception gaps, and recommend positioning adjustments. The system performs semantic analysis of brand messaging and perception to identify how the brand is perceived relative to competitors and target positioning. Outputs brand perception reports, positioning recommendations, and messaging guidance.","intents":["I need to understand how our brand is perceived relative to competitors and identify gaps in our positioning","I want to assess whether our brand messaging is resonating with target audiences or if we need to adjust positioning","I need to identify emerging brand perception issues or threats that require messaging adjustments"],"best_for":["brand management teams optimizing brand positioning","marketing teams developing brand strategies","corporate communications teams managing brand reputation"],"limitations":["Brand perception data sources not specified — unclear which sources are analyzed","Perception analysis methodology not documented","No accuracy metrics for perception gap identification or positioning recommendations","Unclear how system handles subjective brand attributes (quality, trust, innovation, etc.)","No mention of how system incorporates competitive positioning analysis","Unclear how system validates positioning recommendations"],"requires":["Integration with brand perception data sources (surveys, social listening, news monitoring) — specific sources not listed","Brand messaging and positioning data","Competitive positioning data","Domain expertise to validate perception insights and positioning recommendations"],"input_types":["Brand perception surveys","Social media mentions and sentiment","News and media coverage","Competitor messaging","Customer interviews","Brand audit data"],"output_types":["Brand perception reports","Positioning gap analysis","Positioning recommendations","Messaging guidance","Competitive positioning maps"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_14","uri":"capability://tool.use.integration.enterprise.system.integration.and.workflow.automation","name":"enterprise-system-integration-and-workflow-automation","description":"Integrates Athena with existing enterprise applications (CRM, ERP, data warehouses, document systems) to enable autonomous workflows that read from and write to these systems. The system operates as an agent within the Olympus platform that monitors integrated systems for new data, triggers analysis workflows, and writes results back to source systems. Supports bi-directional data flow and maintains data consistency across systems.","intents":["I want Athena to automatically monitor our Salesforce for new opportunities and run competitive analysis without manual data export","I need Athena to extract data from our data warehouse, perform analysis, and write results back to our BI tool","I want to set up a workflow where Athena monitors our document repository for new contracts and automatically runs compliance analysis"],"best_for":["enterprise IT teams integrating AI agents into existing systems","business operations teams automating data workflows","teams seeking to minimize manual data movement between systems"],"limitations":["Specific system integrations not documented — no list of supported CRM, ERP, or data warehouse systems","Integration methodology not specified — unclear if it uses APIs, webhooks, database connectors, or other approaches","No mention of real-time vs. batch data synchronization","Unclear how system handles data consistency and conflict resolution across systems","No mention of integration latency or performance characteristics","Unclear how system handles authentication and credential management for integrated systems","No documentation on custom integration development or extension points"],"requires":["Active enterprise systems with API access (Salesforce, SAP, Tableau, etc.) — specific systems unknown","IT infrastructure to manage system integrations and authentication","Data governance policies for bi-directional data flow","Workflow definition and testing before production deployment"],"input_types":["Data from CRM systems","Data from ERP systems","Data from data warehouses","Documents from content management systems","Structured data exports"],"output_types":["Analysis results written to source systems","Alerts and notifications","Updated records in CRM/ERP","Data warehouse updates","Document annotations"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_2","uri":"capability://data.processing.analysis.contract.analysis.with.playbook.automation","name":"contract-analysis-with-playbook-automation","description":"Analyzes contracts and legal documents using predefined or custom 'playbooks' that encode domain-specific rules, risk patterns, and compliance requirements. The system scans documents for key provisions (liability caps, indemnification clauses, termination rights, regulatory obligations), flags deviations from standard terms, and surfaces red flags for due diligence or M&A workflows. Playbooks appear to be templates that encode legal expertise without requiring manual document review.","intents":["I need to review 200 vendor contracts and flag any with liability caps below our standard threshold or missing indemnification clauses","I want to identify inconsistencies in payment terms, termination clauses, and IP ownership across our contract portfolio","I need to extract all regulatory compliance obligations from a set of contracts and map them to our compliance calendar"],"best_for":["in-house legal teams managing large contract portfolios","M&A due diligence teams evaluating target company contracts","compliance and risk teams automating regulatory obligation tracking"],"limitations":["Playbook creation and customization approach completely undocumented — unclear if users can build custom playbooks or if they are pre-built by Athena","No information on playbook accuracy or false positive rates","Unclear whether playbooks are jurisdiction-specific or industry-specific","No mention of how playbooks are updated when legal standards or company policies change","Red flag detection logic not explained — unclear if it uses pattern matching, semantic similarity, or rule-based logic","No audit trail for why a specific clause was flagged or what rule triggered the flag"],"requires":["Integration with contract management system or document repository (specific systems not listed)","Pre-defined or custom playbooks encoding company-specific contract standards (creation process unknown)","Legal expertise to validate playbook rules and interpret flagged items"],"input_types":["PDF contracts","Word documents","Contract management system exports","Scanned/OCR'd contracts"],"output_types":["Flagged clause lists","Red flag summaries","Deviation reports","Compliance obligation extracts","Annotated contracts"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_3","uri":"capability://data.processing.analysis.pack.price.volume.mix.analysis","name":"pack-price-volume-mix-analysis","description":"Analyzes product mix, pricing, and volume data across channels, regions, and time periods to generate OBPPC (Occasion, Brand, Pack, Price, Channel) reports and KPI dashboards. The system ingests sales data, promotional calendars, and competitive pricing data, then performs multi-dimensional analysis to identify performance drivers, promotional effectiveness, and category expansion opportunities. Outputs structured reports and trend analysis.","intents":["I need to understand why our premium pack is underperforming in the Northeast region and what promotional levers could improve velocity","I want to analyze the impact of our Q3 promotion on volume lift, margin impact, and cannibalization across pack sizes","I need to track SKU performance across 50+ retailers and identify which packs are gaining/losing shelf space"],"best_for":["CPG brand managers optimizing product mix and pricing","sales operations teams tracking KPIs across channels and regions","category managers analyzing promotional effectiveness"],"limitations":["Data source integration not specified — unclear if system pulls from POS systems, trade databases, or manual uploads","Analysis methodology not documented — unclear if it uses statistical modeling, time-series forecasting, or rule-based heuristics","No mention of real-time vs. batch analysis — appears to be periodic reporting rather than live dashboards","Competitive pricing data source not specified","No accuracy metrics for volume lift attribution or promotional impact modeling","Unclear how system handles missing data or data quality issues"],"requires":["Integration with sales data systems (Salesforce, SAP, or similar) — specific connectors unknown","Access to POS or trade data feeds (Nielsen, IRI, or internal systems)","Promotional calendar and pricing data in structured format","BI tool or data warehouse to consume OBPPC reports"],"input_types":["Sales transaction data","POS data","Promotional calendar","Competitive pricing data","Inventory data","Market research data"],"output_types":["OBPPC reports","KPI dashboards","Trend analysis","Performance variance reports","Promotional effectiveness summaries"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_4","uri":"capability://data.processing.analysis.competitive.intelligence.aggregation.and.synthesis","name":"competitive-intelligence-aggregation-and-synthesis","description":"Aggregates competitive data from multiple sources (market research reports, news, pricing data, product announcements) and synthesizes insights at company, product, and category levels. The system performs cross-source reasoning to identify competitive threats, market share shifts, and strategic moves, then surfaces actionable intelligence without requiring manual research synthesis. Outputs competitive benchmarking reports and trend analysis.","intents":["I need to track what our top 5 competitors are doing across product launches, pricing changes, and promotional activity in real-time","I want to understand how competitor sentiment and messaging has shifted over the last quarter based on their public statements","I need to identify emerging competitors or product categories that pose a threat to our market position"],"best_for":["competitive intelligence teams in CPG, retail, and technology companies","product managers monitoring competitive product launches and positioning","strategy teams identifying market threats and opportunities"],"limitations":["Data sources for competitive intelligence not specified — unclear if system monitors news, social media, pricing databases, or relies on manual uploads","Real-time vs. batch monitoring not documented","No mention of how system handles unstructured competitive data (news articles, social posts) vs. structured data (pricing, product specs)","Sentiment analysis approach for competitive messaging not explained","No accuracy metrics for threat identification or market shift detection","Unclear how system distinguishes signal from noise in competitive data"],"requires":["Integration with competitive intelligence data sources (market research databases, news feeds, pricing APIs) — specific sources not listed","Access to internal competitive tracking systems or manual competitive data uploads","Domain expertise to validate competitive insights and prioritize threats"],"input_types":["Market research reports","News articles","Competitor pricing data","Product announcements","Social media data (implied)","Earnings call transcripts","Patent filings (implied)"],"output_types":["Competitive benchmarking reports","Threat assessments","Market share analysis","Competitive positioning maps","Trend summaries"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_5","uri":"capability://data.processing.analysis.bulk.document.inspection.and.key.item.extraction","name":"bulk-document-inspection-and-key-item-extraction","description":"Processes large batches of documents (100s-1000s) to identify and extract specific items, entities, or information patterns without per-document configuration. The system uses semantic understanding to locate relevant content, extract structured data, and organize results into searchable tables or reports. Supports heterogeneous document types and extraction targets within a single batch job.","intents":["I need to extract all customer names, contract values, and renewal dates from 500 vendor contracts","I want to identify all regulatory compliance obligations mentioned in a portfolio of 200 documents and organize them by obligation type","I need to find all instances of specific product names, pricing, or promotional terms across a set of market research reports"],"best_for":["legal teams conducting due diligence on document portfolios","compliance teams automating obligation identification","research teams extracting specific data points from large document sets"],"limitations":["Extraction target definition approach not documented — unclear if users specify what to extract or if system auto-detects relevant items","No accuracy metrics for item identification or extraction","Maximum batch size and processing time not specified","Unclear how system handles ambiguous or context-dependent items","No mention of how extracted items are validated or deduplicated across documents","Output format customization not documented"],"requires":["Integration with document repository or batch upload capability","Clear specification of extraction targets (items, entities, patterns to find)","Existing data system to consume extracted results"],"input_types":["PDF documents","Word documents","Text files","Scanned/OCR'd documents"],"output_types":["Structured extraction tables","Entity lists","Searchable item indexes","Annotated documents"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_6","uri":"capability://data.processing.analysis.pdf.to.word.conversion.and.document.redaction","name":"pdf-to-word-conversion-and-document-redaction","description":"Converts PDF documents to editable Word format while preserving formatting and structure, and applies selective redaction to remove sensitive information (PII, confidential terms, regulated data). The system uses document parsing to identify redactable content types and applies consistent redaction rules across document batches. Outputs editable documents with audit trails of redaction actions.","intents":["I need to convert 50 PDF contracts to Word format so our legal team can edit and annotate them","I want to redact all customer names, pricing terms, and confidential information from contracts before sharing them with external parties","I need to prepare documents for regulatory review by removing PII and applying consistent redaction rules"],"best_for":["legal teams managing document workflows and redaction","compliance teams preparing documents for regulatory disclosure","document management teams converting legacy PDF archives"],"limitations":["Redaction rule customization approach not documented — unclear if users can define custom redaction patterns","No mention of redaction audit trail or verification that sensitive data was actually removed","PDF-to-Word conversion quality not specified — unclear how it handles complex layouts, images, or embedded objects","No information on OCR quality for scanned PDFs","Unclear how system handles password-protected or encrypted PDFs","No mention of batch processing limits or performance characteristics"],"requires":["Integration with document repository or batch upload capability","Definition of redaction rules (PII types, confidential terms, etc.) — approach unknown","Existing document management system to store converted/redacted documents"],"input_types":["PDF documents","Scanned/OCR'd PDFs","Image-based PDFs"],"output_types":["Word documents (.docx)","Redacted PDFs","Redaction audit logs"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_7","uri":"capability://data.processing.analysis.m.and.a.deal.provision.evaluation","name":"m-and-a-deal-provision-evaluation","description":"Analyzes acquisition target contracts and legal documents to identify provisions that impact deal value, integration risk, or post-closing obligations. The system evaluates change-of-control clauses, termination rights, consent requirements, and other deal-critical provisions, then surfaces issues that require negotiation or assumption planning. Outputs deal risk assessments and provision summaries.","intents":["I need to identify all contracts that require customer consent for our acquisition and estimate the risk of customer loss","I want to understand what post-closing obligations we're assuming from the target's contract portfolio","I need to flag any contracts with termination rights triggered by change of control that could impact revenue"],"best_for":["M&A due diligence teams evaluating acquisition targets","corporate development teams assessing deal risk and integration planning","legal teams managing deal closing and post-closing obligations"],"limitations":["Deal-critical provision identification approach not documented — unclear if it uses predefined patterns or semantic understanding","No accuracy metrics for risk assessment or provision impact estimation","Unclear how system prioritizes provisions by deal impact","No mention of how system handles industry-specific or jurisdiction-specific deal risks","Unclear how system estimates customer loss risk or integration complexity","No mention of integration with deal models or financial projections"],"requires":["Integration with target company contract repository or bulk document upload","Access to deal model and financial projections (to assess provision impact)","M&A expertise to validate risk assessments and prioritize issues"],"input_types":["Target company contracts","Customer agreements","Supplier contracts","Employment agreements","Licensing agreements","Regulatory permits"],"output_types":["Deal risk assessments","Provision summaries","Change-of-control impact analysis","Integration risk flags","Assumption schedules"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_8","uri":"capability://automation.workflow.regulatory.compliance.automation.and.obligation.tracking","name":"regulatory-compliance-automation-and-obligation-tracking","description":"Identifies regulatory compliance obligations embedded in contracts, policies, and regulatory documents, then tracks compliance status and deadlines across the organization. The system extracts obligation details (requirement, deadline, responsible party, penalty for non-compliance), maps obligations to compliance calendars, and flags upcoming deadlines or missed obligations. Supports multiple regulatory frameworks and jurisdictions.","intents":["I need to identify all GDPR, CCPA, and HIPAA compliance obligations in our contract portfolio and track compliance status","I want to create a compliance calendar that shows all regulatory deadlines and required actions across the organization","I need to flag any contracts with compliance obligations that we're not currently meeting"],"best_for":["compliance and risk teams automating obligation tracking","legal teams managing regulatory requirements across contracts","operations teams coordinating compliance activities"],"limitations":["Regulatory framework coverage not specified — unclear which regulations are supported (GDPR, CCPA, HIPAA, SOX, etc.)","Obligation extraction accuracy not documented","No mention of how system handles jurisdiction-specific variations in compliance requirements","Unclear how system determines compliance status or validates that obligations are being met","No mention of integration with compliance management systems or audit tools","Unclear how system handles changing regulatory requirements"],"requires":["Integration with contract management and document repositories","Access to regulatory documents and compliance policies","Existing compliance tracking system or calendar to consume obligations","Compliance expertise to validate extracted obligations and assess compliance status"],"input_types":["Contracts","Regulatory documents","Compliance policies","Audit reports","Regulatory guidance"],"output_types":["Compliance obligation lists","Compliance calendars","Deadline alerts","Compliance status reports","Risk assessments"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-athena-intelligence__cap_9","uri":"capability://data.processing.analysis.litigation.support.deposition.analysis","name":"litigation-support-deposition-analysis","description":"Analyzes deposition transcripts and litigation documents to identify inconsistencies, contradictions, and key admissions that impact case strategy. The system performs semantic analysis of testimony across multiple depositions to surface contradictory statements, timeline inconsistencies, and factual disputes. Outputs summaries of key testimony, contradiction flags, and case impact assessments.","intents":["I need to identify contradictions between witness depositions that could undermine opposing counsel's case","I want to extract all admissions of fact from deposition transcripts and organize them by topic","I need to identify timeline inconsistencies in witness testimony that could be used to impeach credibility"],"best_for":["litigation teams preparing for trial or settlement negotiations","in-house counsel managing complex litigation","law firms supporting large-scale litigation"],"limitations":["Inconsistency detection methodology not documented — unclear if it uses semantic similarity, timeline analysis, or rule-based logic","No accuracy metrics for contradiction identification or impact assessment","Unclear how system handles ambiguous or context-dependent testimony","No mention of how system prioritizes contradictions by case impact","Unclear how system handles multiple witness accounts of the same event","No mention of integration with case management systems"],"requires":["Integration with litigation document repository or bulk deposition transcript upload","Deposition transcripts in text or searchable PDF format","Legal expertise to validate identified contradictions and assess case impact"],"input_types":["Deposition transcripts","Trial testimony","Interrogatory responses","Document productions","Expert reports"],"output_types":["Contradiction summaries","Testimony extracts","Timeline analyses","Credibility assessments","Case impact flags"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":29,"verified":false,"data_access_risk":"high","permissions":["Active integration with enterprise document management system (Sharepoint, OneDrive, etc.) — specific connectors unknown","SOC 2 Type II and HIPAA compliance environment (product certified but deployment requirements unclear)","Existing enterprise data systems to write extracted data to (Salesforce, data warehouse, etc.)","Integration with enterprise document repository containing earnings reports and SEC filings","Access to earnings call transcripts (source not specified — assumes internal repository or third-party feed)","Existing data warehouse or BI tool to consume synthesized financial reports","Integration with text data sources (earnings calls, news feeds, social media, reviews) — specific sources not listed","Text data in structured format (transcripts, articles, posts)","Domain expertise to validate sentiment signals and identify actionable trends","Integration with consumer data sources (surveys, social listening, purchase data, reviews) — specific sources not listed"],"failure_modes":["No disclosed accuracy metrics or confidence scores — unclear how hallucinations are mitigated in extracted data","Maximum document size and batch volume limits not specified","Requires pre-integration with enterprise document systems; no standalone file upload mentioned","Output format customization approach unknown — unclear if users can define custom extraction schemas","No audit trail or explainability for why specific fields were extracted or how confidence was determined","No disclosed context window size — unclear how many documents can be analyzed in a single synthesis pass","Sentiment analysis approach not specified — unclear if it uses fine-tuned models or general-purpose LLM sentiment","No accuracy benchmarks provided for financial metric extraction or sentiment classification","Requires documents to already be integrated into Olympus platform; no ad-hoc document upload for one-off analysis","No mention of real-time earnings data feeds — appears to be batch-oriented rather than live monitoring","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.35,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:02.371Z","last_scraped_at":"2026-05-03T14:00:10.321Z","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=athena-intelligence","compare_url":"https://unfragile.ai/compare?artifact=athena-intelligence"}},"signature":"tzJ34SzqNI3D827DHOBUmWTiIir9TilT1qvTcjbgjVr01Pwmkc/u90E/FuxnTJG1wD4bm2wnfGuKwb985IgHCg==","signedAt":"2026-06-20T17:09:25.081Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/athena-intelligence","artifact":"https://unfragile.ai/athena-intelligence","verify":"https://unfragile.ai/api/v1/verify?slug=athena-intelligence","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"}}