{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_dr-gupta","slug":"dr-gupta","name":"Dr. Gupta","type":"product","url":"https://www.drgupta.ai","page_url":"https://unfragile.ai/dr-gupta","categories":["chatbots-assistants"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_dr-gupta__cap_0","uri":"capability://text.generation.language.conversational.symptom.intake.and.triage","name":"conversational symptom intake and triage","description":"Engages users in multi-turn dialogue to collect symptom descriptions, duration, severity, and medical history through natural language understanding. Uses intent classification and entity extraction to map free-form symptom narratives to standardized medical ontologies (likely ICD-10 or similar), enabling structured symptom matching against differential diagnosis databases without requiring users to navigate medical terminology or checkbox forms.","intents":["I want to describe my symptoms in natural language and get a preliminary assessment without medical jargon","I need to quickly triage whether my symptoms warrant emergency care or can wait for a clinic appointment","I want to understand what conditions might match my symptoms before consulting a doctor"],"best_for":["patients in regions with limited healthcare access seeking rapid preliminary triage","uninsured or underinsured individuals deciding whether to seek paid medical care","non-English speakers in markets where Dr. Gupta supports localized language models"],"limitations":["Cannot access patient's actual medical records, lab results, or prescription history—operates on self-reported symptoms only, increasing misdiagnosis risk for complex conditions","No ability to perform physical examination, vital sign measurement, or diagnostic imaging interpretation","Symptom descriptions are subjective and prone to misinterpretation; users may underreport or mischaracterize severity","No clinical accountability or liability protection if triage assessment leads to delayed treatment of emergencies"],"requires":["Internet connectivity for API calls to LLM backend","User ability to describe symptoms in supported language (language coverage unknown from artifact)"],"input_types":["text (natural language symptom descriptions)"],"output_types":["text (conversational responses, preliminary condition suggestions)","structured data (likely differential diagnosis list with confidence scores)"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dr-gupta__cap_1","uri":"capability://planning.reasoning.differential.diagnosis.suggestion.with.confidence.scoring","name":"differential diagnosis suggestion with confidence scoring","description":"Analyzes collected symptom data against medical knowledge bases (likely trained on clinical guidelines, epidemiological data, and diagnostic criteria) to generate ranked lists of possible conditions with relative likelihood scores. Uses probabilistic reasoning or Bayesian inference patterns to weight conditions based on symptom prevalence, demographic factors (age, gender, geography), and symptom severity, presenting results in order of clinical urgency rather than alphabetical order.","intents":["I want to know what conditions could explain my symptoms, ranked by likelihood","I need to understand which of my symptoms are most concerning or warrant immediate care","I want to prepare informed questions for my doctor by understanding possible diagnoses"],"best_for":["patients seeking preliminary differential diagnosis before professional consultation","individuals in underserved regions using symptom checking as proxy for unavailable medical expertise","health-conscious users wanting to understand their symptoms in medical context"],"limitations":["Cannot perform differential diagnosis with clinical rigor—lacks physical examination, lab confirmation, and imaging that physicians use to rule out conditions","Confidence scores are probabilistic estimates, not clinical certainty; high-confidence suggestions may still be incorrect","Rare conditions or atypical presentations may be underrepresented in training data, leading to missed diagnoses","No ability to distinguish between conditions with overlapping symptom profiles without additional clinical data","Demographic bias risk: if training data reflects healthcare disparities, algorithm may underestimate disease prevalence in underrepresented populations"],"requires":["Symptom data collected from prior conversational intake","Access to medical knowledge base or LLM trained on clinical data"],"input_types":["structured symptom data (extracted from conversation)","demographic metadata (age, gender, location if available)"],"output_types":["ranked list of conditions with confidence/likelihood scores","text explanations of why each condition matches symptoms"],"categories":["planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dr-gupta__cap_2","uri":"capability://automation.workflow.24.7.asynchronous.health.consultation.availability","name":"24/7 asynchronous health consultation availability","description":"Provides instant responses to health queries without appointment scheduling, wait times, or business hours constraints through cloud-hosted LLM inference. Enables users to initiate conversations at any time and receive preliminary guidance within seconds, eliminating temporal barriers to health information access common in regions with limited healthcare infrastructure or for users unable to access care during clinic hours.","intents":["I have a health concern at 2 AM and need immediate preliminary guidance without waiting for a clinic to open","I want to quickly assess whether my symptoms are urgent before deciding to visit an emergency room","I need health information now, not days or weeks from now when I can schedule a doctor's appointment"],"best_for":["patients in time zones or regions with severe healthcare access gaps","shift workers or individuals with inflexible schedules unable to access traditional clinic hours","users seeking rapid preliminary triage to avoid unnecessary emergency room visits"],"limitations":["Asynchronous availability does not replace emergency medical services for life-threatening conditions—users must still recognize when to call emergency services","No ability to escalate to human physician if assessment suggests urgent care needed","Response latency depends on cloud infrastructure availability and LLM inference load; no SLA or uptime guarantee typical of medical systems","No persistent conversation history or medical record continuity across sessions unless explicitly stored"],"requires":["Internet connectivity (mobile or broadband)","Cloud infrastructure with sufficient LLM inference capacity to handle concurrent users","User ability to recognize when symptoms warrant emergency care despite AI availability"],"input_types":["text (symptom descriptions, follow-up questions)"],"output_types":["text (conversational responses with preliminary guidance)"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dr-gupta__cap_3","uri":"capability://automation.workflow.freemium.access.model.with.usage.based.monetization","name":"freemium access model with usage-based monetization","description":"Implements tiered access where basic symptom checking and preliminary guidance are free, with premium features (detailed explanations, follow-up consultations, integration with medical records, or priority response) available through paid subscription or per-use credits. Enables low-friction user acquisition in price-sensitive markets while creating revenue stream from users willing to pay for enhanced features, reducing barriers to entry for uninsured populations while maintaining business sustainability.","intents":["I want to check my symptoms without paying upfront, to see if the tool is useful before committing money","I need basic health triage for free, but would pay for more detailed guidance if needed","I want to access health information affordably as an uninsured or underinsured individual"],"best_for":["uninsured or underinsured populations in developing countries or underserved regions","price-sensitive users seeking low-cost health information access","Dr. Gupta as a business seeking to monetize health AI while maintaining accessibility"],"limitations":["Free tier may be limited in scope (e.g., basic symptom checking only, no follow-up consultations), potentially frustrating users with complex conditions","Freemium model creates incentive to upsell premium features, which may conflict with medical ethics of providing complete guidance regardless of ability to pay","No information provided on what features are free vs. paid, pricing tiers, or conversion rates","Freemium sustainability depends on sufficient premium conversion; if conversion is low, free tier may be degraded or discontinued"],"requires":["Payment processing infrastructure for premium tier (credit card, mobile money, local payment methods)","Clear communication of free vs. paid features to avoid user confusion or frustration"],"input_types":["user subscription status or payment information"],"output_types":["access control decisions (free vs. premium features available)"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dr-gupta__cap_4","uri":"capability://text.generation.language.medical.jargon.reduction.and.health.literacy.adaptation","name":"medical jargon reduction and health literacy adaptation","description":"Translates medical terminology and clinical concepts into plain language explanations accessible to users with varying health literacy levels, using simplified vocabulary, analogies, and contextual explanations rather than technical medical terms. Likely implements language simplification through prompt engineering or fine-tuning to detect when users may not understand medical terminology and proactively explain concepts in accessible terms, reducing barriers for populations with limited health education.","intents":["I want to understand my symptoms and possible conditions without needing a medical dictionary","I need health information explained in simple language that I can understand and act on","I want to feel confident discussing my health with a doctor after understanding the basics"],"best_for":["users with limited health literacy or non-medical education backgrounds","non-native English speakers or users in regions where medical terminology differs","populations with cultural or educational barriers to understanding Western medical concepts"],"limitations":["Oversimplification of medical concepts may lose clinical nuance or accuracy needed for informed decision-making","Plain language explanations may be longer and less efficient than technical terminology, increasing conversation length","No ability to assess user's actual health literacy level; may over-simplify for educated users or under-simplify for others","Translations of medical concepts may not align with local health beliefs or traditional medicine practices in some regions"],"requires":["LLM fine-tuned or prompted to generate plain-language explanations","Medical knowledge base with both technical and simplified explanations of conditions"],"input_types":["text (symptom descriptions, follow-up questions)"],"output_types":["text (simplified explanations of medical concepts, conditions, and recommendations)"],"categories":["text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dr-gupta__cap_5","uri":"capability://safety.moderation.emergency.severity.flagging.and.escalation.guidance","name":"emergency severity flagging and escalation guidance","description":"Identifies symptom combinations or severity indicators that suggest urgent or emergency conditions requiring immediate professional medical attention, and provides clear guidance to seek emergency services (call ambulance, visit ER) rather than attempting self-care. Uses rule-based logic or LLM reasoning to detect red flags (chest pain, difficulty breathing, severe bleeding, etc.) and escalates recommendations to emergency care with explicit instructions on how to access emergency services in user's region.","intents":["I need to know if my symptoms are serious enough to warrant emergency care right now","I want clear guidance on whether to call an ambulance or go to the emergency room","I need to understand which symptoms are dangerous and require immediate professional help"],"best_for":["users in regions with limited healthcare access who may not recognize emergency symptoms","individuals deciding whether symptoms warrant emergency care vs. waiting for clinic appointment","Dr. Gupta as a tool to reduce unnecessary emergency room visits by accurately triaging non-urgent conditions"],"limitations":["Cannot perform clinical assessment of actual severity; relies on user's self-reported symptoms which may be inaccurate or incomplete","Red flag detection may miss atypical presentations of serious conditions (e.g., silent heart attacks, appendicitis without typical pain)","No ability to verify user actually seeks emergency care after escalation recommendation; users may ignore guidance","Escalation guidance depends on local emergency services availability and accessibility; may be ineffective in regions with no functioning emergency infrastructure","Over-flagging of non-emergency symptoms as urgent may contribute to emergency room overcrowding; under-flagging may delay treatment of serious conditions"],"requires":["Medical knowledge base with emergency red flags and severity criteria","Awareness of local emergency services contact information and accessibility in user's region"],"input_types":["symptom data (severity, duration, associated symptoms)"],"output_types":["escalation flag (emergency vs. non-urgent)","text guidance on how to access emergency services"],"categories":["safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dr-gupta__cap_6","uri":"capability://text.generation.language.multi.language.support.for.global.health.access","name":"multi-language support for global health access","description":"Provides symptom checking and health guidance in multiple languages beyond English, enabling access for non-English speakers in developing countries and underserved regions. Likely implements language detection and multi-lingual LLM inference (or language-specific model routing) to respond in user's preferred language, reducing language barriers to health information access for populations where English proficiency is limited.","intents":["I want to describe my symptoms and get health guidance in my native language, not English","I need health information accessible to my family members who don't speak English","I want to use a health tool that understands my local language and cultural context"],"best_for":["non-English speakers in developing countries and underserved regions","populations where English proficiency is limited or unavailable","Dr. Gupta's expansion strategy into non-English-speaking markets"],"limitations":["Language coverage unknown from artifact; may support only major languages (Spanish, Mandarin, Hindi) and exclude minority languages","Medical terminology translation may be inconsistent or inaccurate across languages; medical concepts may not map directly between languages","LLM quality and training data availability varies significantly by language; non-English models may have lower accuracy than English","Cultural differences in health beliefs and medical terminology may not be captured by direct translation","No information on whether translations are human-reviewed or purely machine-generated"],"requires":["Multi-lingual LLM or language-specific model routing","Medical knowledge base translated or adapted for each supported language","Language detection to identify user's preferred language"],"input_types":["text in supported languages"],"output_types":["text responses in user's language"],"categories":["text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dr-gupta__cap_7","uri":"capability://planning.reasoning.reduction.of.unnecessary.emergency.room.visits.through.preliminary.triage","name":"reduction of unnecessary emergency room visits through preliminary triage","description":"Enables users to assess symptom severity and determine whether professional medical care is needed before visiting emergency room or clinic, potentially reducing unnecessary ER visits and associated costs for non-urgent conditions. By providing preliminary triage and guidance on symptom severity, the tool helps users make informed decisions about care-seeking behavior, reducing healthcare system burden and out-of-pocket costs for patients in regions with expensive emergency care.","intents":["I want to know if my symptoms are serious enough to warrant an expensive emergency room visit","I need to decide whether to go to the ER or wait for a clinic appointment based on symptom severity","I want to reduce unnecessary healthcare costs by getting preliminary guidance before seeking professional care"],"best_for":["uninsured or underinsured patients in regions with expensive emergency care","healthcare systems seeking to reduce ER overcrowding and unnecessary visits","patients in developing countries where ER costs are prohibitive"],"limitations":["Triage accuracy depends on user's ability to accurately describe symptoms; self-assessment may be inaccurate","Risk of under-triage: users may avoid necessary emergency care due to cost concerns, leading to delayed treatment of serious conditions","Risk of over-triage: users may visit ER unnecessarily despite preliminary guidance suggesting non-urgent care","No ability to verify whether users actually follow triage recommendations or seek appropriate care","Liability risk: if preliminary triage assessment leads to delayed treatment of serious condition, Dr. Gupta may face legal liability"],"requires":["Accurate symptom severity assessment and red flag detection","Clear communication of triage recommendations to users"],"input_types":["symptom data (severity, duration, associated symptoms)"],"output_types":["triage recommendation (emergency vs. urgent vs. non-urgent)","guidance on appropriate care setting (ER vs. clinic vs. self-care)"],"categories":["planning-reasoning","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"low","permissions":["Internet connectivity for API calls to LLM backend","User ability to describe symptoms in supported language (language coverage unknown from artifact)","Symptom data collected from prior conversational intake","Access to medical knowledge base or LLM trained on clinical data","Internet connectivity (mobile or broadband)","Cloud infrastructure with sufficient LLM inference capacity to handle concurrent users","User ability to recognize when symptoms warrant emergency care despite AI availability","Payment processing infrastructure for premium tier (credit card, mobile money, local payment methods)","Clear communication of free vs. paid features to avoid user confusion or frustration","LLM fine-tuned or prompted to generate plain-language explanations"],"failure_modes":["Cannot access patient's actual medical records, lab results, or prescription history—operates on self-reported symptoms only, increasing misdiagnosis risk for complex conditions","No ability to perform physical examination, vital sign measurement, or diagnostic imaging interpretation","Symptom descriptions are subjective and prone to misinterpretation; users may underreport or mischaracterize severity","No clinical accountability or liability protection if triage assessment leads to delayed treatment of emergencies","Cannot perform differential diagnosis with clinical rigor—lacks physical examination, lab confirmation, and imaging that physicians use to rule out conditions","Confidence scores are probabilistic estimates, not clinical certainty; high-confidence suggestions may still be incorrect","Rare conditions or atypical presentations may be underrepresented in training data, leading to missed diagnoses","No ability to distinguish between conditions with overlapping symptom profiles without additional clinical data","Demographic bias risk: if training data reflects healthcare disparities, algorithm may underestimate disease prevalence in underrepresented populations","Asynchronous availability does not replace emergency medical services for life-threatening conditions—users must still recognize when to call emergency services","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"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":"2026-05-24T12:16:30.283Z","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=dr-gupta","compare_url":"https://unfragile.ai/compare?artifact=dr-gupta"}},"signature":"9DiGh81AFFqnuwLObjQ3sYfEqKP3QWxrzuYfw1oc1iZw9+JuKpb+W0LaZdSTfkNEQ+hO7hpKja5lS1NUYHdSCQ==","signedAt":"2026-06-22T14:26:37.475Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/dr-gupta","artifact":"https://unfragile.ai/dr-gupta","verify":"https://unfragile.ai/api/v1/verify?slug=dr-gupta","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"}}