{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_sully-ai","slug":"sully-ai","name":"Sully AI","type":"product","url":"https://www.sully.ai","page_url":"https://unfragile.ai/sully-ai","categories":["automation"],"tags":[],"pricing":{"model":"paid","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_sully-ai__cap_0","uri":"capability://healthcare.emr.integrated.clinical.documentation.assistance","name":"emr-integrated clinical documentation assistance","description":"Analyzes patient data from integrated EMR systems and generates or suggests clinical documentation in real-time within the clinician's existing workflow. Reduces manual documentation burden by auto-populating fields and structuring notes based on clinical context.","intents":["I want to spend less time on paperwork and more time with patients","I need to ensure my clinical notes are complete and compliant","I want to avoid switching between multiple systems to document care"],"best_for":["Clinicians at mid to large healthcare systems","Healthcare organizations with standardized EMR platforms"],"limitations":["Effectiveness depends on EMR system compatibility","Legacy EMR systems may have limited integration","Requires institutional IT infrastructure and approval"],"requires":["Active EMR system integration","HIPAA-compliant network environment","Institutional deployment and configuration"],"input_types":["patient data from EMR","clinical encounter notes","structured EMR fields"],"output_types":["auto-populated documentation","suggested clinical notes","structured EMR entries"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sully-ai__cap_1","uri":"capability://healthcare.real.time.diagnostic.decision.support","name":"real-time diagnostic decision support","description":"Analyzes patient clinical data and medical history to flag potential diagnoses, contraindications, and rare condition patterns during clinical encounters. Provides evidence-based suggestions to support clinician decision-making without replacing clinical judgment.","intents":["I want to catch rare or atypical diagnoses I might otherwise miss","I need to identify potential drug interactions before prescribing","I want evidence-based suggestions to inform my clinical decisions"],"best_for":["Physicians and clinicians in diagnostic roles","Healthcare systems seeking to improve diagnostic accuracy","Institutions with complex patient populations"],"limitations":["Dependent on completeness and accuracy of EMR data","Cannot replace clinical judgment or physical examination","Effectiveness varies based on condition rarity and data quality"],"requires":["Complete patient medical history in EMR","Current medication and allergy information","Real-time access to clinical data during encounters"],"input_types":["patient symptoms and chief complaints","medical history","current medications","lab results and vital signs","clinical examination findings"],"output_types":["diagnostic suggestions","drug interaction alerts","rare condition pattern flags","evidence-based recommendations"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sully-ai__cap_2","uri":"capability://healthcare.drug.interaction.and.contraindication.screening","name":"drug interaction and contraindication screening","description":"Automatically screens patient medication lists and clinical profiles against comprehensive drug interaction databases to identify potential contraindications, adverse reactions, and unsafe combinations before prescribing decisions are finalized.","intents":["I need to verify a medication is safe for this patient before prescribing","I want to catch dangerous drug-drug interactions automatically","I need to check for allergies and contraindications quickly"],"best_for":["Prescribing clinicians","Pharmacists reviewing medication orders","Healthcare systems with high prescription volumes"],"limitations":["Requires accurate and up-to-date medication lists in EMR","May generate false positives requiring clinical interpretation","Cannot account for all patient-specific factors"],"requires":["Current medication list in EMR","Patient allergy information","Access to comprehensive drug interaction database"],"input_types":["current medications","proposed new medication","patient allergies","patient age and renal/hepatic function"],"output_types":["interaction alerts","contraindication warnings","severity classifications","alternative medication suggestions"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sully-ai__cap_3","uri":"capability://healthcare.context.aware.clinical.pattern.recognition","name":"context-aware clinical pattern recognition","description":"Identifies clinically significant patterns in patient data including rare disease presentations, atypical symptom clusters, and disease progression indicators by analyzing historical EMR data and current clinical context.","intents":["I want to recognize rare disease patterns I might not immediately think of","I need to understand how this patient's presentation compares to similar cases","I want to identify early warning signs of disease progression"],"best_for":["Physicians managing complex or unusual cases","Healthcare systems with large patient populations","Specialists seeking pattern validation"],"limitations":["Effectiveness depends on data completeness and quality","Rare conditions may have insufficient training data","Patterns may not apply to individual patient circumstances"],"requires":["Comprehensive historical patient data in EMR","Multiple clinical encounters and data points","Access to aggregated pattern databases"],"input_types":["patient medical history","symptom presentations","lab and imaging results","temporal clinical data"],"output_types":["pattern match alerts","rare disease flags","disease progression indicators","similar case references"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sully-ai__cap_4","uri":"capability://healthcare.hipaa.compliant.data.handling.and.security","name":"hipaa-compliant data handling and security","description":"Manages all patient data with healthcare-specific security protocols, encryption, and compliance frameworks designed to meet HIPAA requirements and healthcare data protection standards without requiring generic enterprise security overlays.","intents":["I need to ensure patient data is handled securely and compliantly","I want to use AI tools without creating compliance and security risks","I need audit trails and security controls built into the system"],"best_for":["Healthcare organizations subject to HIPAA","Institutions with strict data governance requirements","Healthcare systems prioritizing compliance over generic solutions"],"limitations":["Compliance requirements vary by jurisdiction and institution","Requires ongoing monitoring and updates for regulatory changes","May limit certain AI capabilities that conflict with privacy requirements"],"requires":["HIPAA-compliant infrastructure","Proper data access controls and authentication","Regular compliance audits and monitoring"],"input_types":["patient protected health information","clinical data","user access logs"],"output_types":["encrypted data storage","audit logs","compliance reports","access control enforcement"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sully-ai__cap_5","uri":"capability://healthcare.clinician.workflow.context.switching.reduction","name":"clinician workflow context switching reduction","description":"Integrates AI capabilities directly into existing EMR interfaces and clinical workflows, eliminating the need for clinicians to switch between separate tools or systems to access diagnostic support and documentation assistance.","intents":["I want AI support without leaving my EMR system","I need to minimize interruptions and context switches during patient care","I want AI integrated into my existing clinical workflow"],"best_for":["Busy clinicians with high patient volumes","Healthcare systems with standardized EMR platforms","Organizations focused on workflow optimization"],"limitations":["Limited to EMR systems with integration support","Legacy systems may not support seamless integration","Requires institutional IT configuration and maintenance"],"requires":["Supported EMR system","IT infrastructure for system integration","Clinician training on integrated features"],"input_types":["EMR interface interactions","patient data from EMR","clinical encounter context"],"output_types":["in-EMR AI suggestions","integrated documentation assistance","contextual decision support"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sully-ai__cap_6","uri":"capability://healthcare.institutional.change.management.and.adoption.support","name":"institutional change management and adoption support","description":"Provides organizational support for implementing AI-driven clinical workflows including training, change management guidance, and adoption monitoring to help healthcare institutions successfully integrate the system across their clinician population.","intents":["I need help getting my clinicians to actually use this system","I want to understand adoption barriers and how to overcome them","I need training and support materials for my staff"],"best_for":["Healthcare system administrators and IT leaders","Organizations implementing new clinical technologies","Institutions with diverse clinician populations and adoption challenges"],"limitations":["Adoption rates vary dramatically based on organizational culture","Requires sustained institutional commitment and leadership support","Cannot guarantee clinician acceptance or usage"],"requires":["Institutional leadership buy-in","Dedicated change management resources","Clinician training and support infrastructure"],"input_types":["organizational structure and workflows","clinician feedback and concerns","adoption metrics and usage data"],"output_types":["training materials","change management guidance","adoption monitoring reports","best practice recommendations"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_sully-ai__cap_7","uri":"capability://healthcare.administrative.overhead.reduction.through.automation","name":"administrative overhead reduction through automation","description":"Automates routine clinical administrative tasks including documentation, data entry, and compliance-related paperwork to reduce the non-clinical burden on healthcare providers and allow more time for patient care.","intents":["I want to reduce time spent on administrative tasks","I need to automate repetitive documentation and data entry","I want to focus more on patient care and less on paperwork"],"best_for":["Clinicians with high administrative burden","Healthcare systems seeking to improve clinician satisfaction","Organizations with standardized administrative workflows"],"limitations":["Automation effectiveness depends on workflow standardization","Complex or non-standard workflows may not be automatable","Requires initial configuration and ongoing maintenance"],"requires":["Standardized administrative workflows","EMR system integration","Clear documentation and compliance requirements"],"input_types":["clinical encounter data","patient information","administrative requirements"],"output_types":["auto-generated documentation","completed administrative forms","compliance-ready records"],"categories":["healthcare","productivity"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":44,"verified":false,"data_access_risk":"high","permissions":["Active EMR system integration","HIPAA-compliant network environment","Institutional deployment and configuration","Complete patient medical history in EMR","Current medication and allergy information","Real-time access to clinical data during encounters","Current medication list in EMR","Patient allergy information","Access to comprehensive drug interaction database","Comprehensive historical patient data in EMR"],"failure_modes":["Effectiveness depends on EMR system compatibility","Legacy EMR systems may have limited integration","Requires institutional IT infrastructure and approval","Dependent on completeness and accuracy of EMR data","Cannot replace clinical judgment or physical examination","Effectiveness varies based on condition rarity and data quality","Requires accurate and up-to-date medication lists in EMR","May generate false positives requiring clinical interpretation","Cannot account for all patient-specific factors","Effectiveness depends on data completeness and quality","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.39999999999999997,"quality":0.77,"ecosystem":0.25,"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":"2026-05-24T12:16:33.648Z","last_scraped_at":"2026-04-05T13:23:42.541Z","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=sully-ai","compare_url":"https://unfragile.ai/compare?artifact=sully-ai"}},"signature":"qg/fFY0TBzu92QcPeCCQvISTaZ5uCskAF9wsAZzH2gLxpsQtUW96yvu57eaMSxGBEqMQBPSuKwb3nX/q+r3ODg==","signedAt":"2026-06-21T18:22:08.077Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/sully-ai","artifact":"https://unfragile.ai/sully-ai","verify":"https://unfragile.ai/api/v1/verify?slug=sully-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"}}