{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_wodka-ai","slug":"wodka-ai","name":"Wodka.ai","type":"platform","url":"https://wodka.ai","page_url":"https://unfragile.ai/wodka-ai","categories":["app-builders"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_wodka-ai__cap_0","uri":"capability://automation.workflow.visual.flow.based.chatbot.builder","name":"visual-flow-based-chatbot-builder","description":"Drag-and-drop interface for constructing conversation flows without code, using a node-based graph editor where users define branching logic, user intents, and bot responses. The builder likely compiles visual flows into an internal state machine or decision tree that executes at runtime, handling conditional routing based on user input classification and predefined response templates.","intents":["I want to build a customer support chatbot in under 30 minutes without writing any code","I need to create branching conversation paths based on customer questions without hiring a developer","I want to visually map out my sales qualification workflow and deploy it immediately"],"best_for":["non-technical business owners and support managers","small SaaS teams without dedicated ML/NLP engineers","e-commerce businesses needing rapid chatbot deployment"],"limitations":["Visual builder abstracts away advanced NLP customization—no direct control over intent classification thresholds or entity extraction rules","Complex multi-turn conversations with dynamic context switching may require workarounds or custom logic blocks","No version control or collaborative editing—simultaneous edits by multiple team members not supported"],"requires":["Web browser with modern JavaScript support (Chrome, Firefox, Safari, Edge)","Active Wodka.ai account (free tier available)","Basic understanding of conversation design (no coding required)"],"input_types":["text descriptions of conversation flows","user intent definitions","response templates"],"output_types":["executable chatbot state machine","deployed conversation flow","embeddable widget code"],"categories":["automation-workflow","no-code-platform"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_1","uri":"capability://planning.reasoning.intent.classification.and.routing","name":"intent-classification-and-routing","description":"Automatic classification of incoming user messages into predefined intents using NLP (likely transformer-based embeddings or lightweight intent classifiers), with deterministic routing to appropriate conversation branches or response handlers. The system maps user utterances to bot actions through a learned or rule-based matching layer that determines which conversation path to execute.","intents":["I want the chatbot to understand what the customer is asking and route them to the right response automatically","I need to distinguish between sales inquiries, support requests, and general questions without manual rules","I want to handle variations of the same question (e.g., 'How much does it cost?' vs 'What's your pricing?') with a single response"],"best_for":["support teams handling diverse customer inquiries","sales teams qualifying leads based on customer intent","businesses with 5-20 common customer question categories"],"limitations":["Intent classification accuracy degrades with out-of-domain queries—no fallback to human escalation is automatic","Limited to predefined intents; discovering new customer intent patterns requires manual flow updates","No multi-language intent classification—language detection and routing not mentioned in product description","Confidence thresholds for intent matching are not user-configurable"],"requires":["Wodka.ai account with chatbot builder access","Pre-defined intent categories (minimum 2-3, recommended 5-15)","Training examples or sample utterances for each intent"],"input_types":["user text messages","intent definitions with example utterances"],"output_types":["classified intent label","confidence score (if exposed)","routed conversation branch"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_2","uri":"capability://automation.workflow.pre.built.sales.and.support.templates","name":"pre-built-sales-and-support-templates","description":"Curated conversation templates for common business scenarios (lead qualification, FAQ handling, appointment scheduling, support triage) that users can instantiate and customize without building flows from scratch. Templates include predefined intents, response patterns, and conversation logic optimized for specific use cases, reducing time-to-deployment and providing best-practice conversation design.","intents":["I want to quickly deploy a lead qualification chatbot using industry best practices","I need a customer support bot that handles common FAQ categories without designing the flow myself","I want to automate appointment scheduling conversations with minimal setup"],"best_for":["startups and small businesses without conversation design expertise","teams prioritizing speed-to-market over customization","businesses with standard sales or support workflows"],"limitations":["Templates are generic and may not align with niche business processes—customization required for unique workflows","Limited template library (exact count unknown)—may not cover all industry verticals","Template updates are platform-controlled; users cannot contribute or share custom templates"],"requires":["Wodka.ai account","Selection of relevant template for business use case","Basic customization of template responses and intents"],"input_types":["template selection","business-specific customization parameters"],"output_types":["instantiated chatbot flow","deployable conversation template"],"categories":["automation-workflow","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_3","uri":"capability://tool.use.integration.multi.channel.chatbot.deployment","name":"multi-channel-chatbot-deployment","description":"Deployment of trained chatbots across multiple communication channels (website widget, messaging platforms, email, potentially SMS or WhatsApp) from a single bot configuration. The platform likely maintains a unified conversation state and message handling layer that abstracts channel-specific protocols, allowing the same bot logic to operate across different interfaces without duplication.","intents":["I want to deploy my chatbot on my website, Facebook Messenger, and WhatsApp without rebuilding it three times","I need my chatbot to maintain conversation context across channels if a customer switches from web to mobile","I want to manage all chatbot conversations from a single dashboard regardless of which channel they came from"],"best_for":["omnichannel customer support teams","e-commerce businesses reaching customers on multiple platforms","SaaS companies with diverse customer communication preferences"],"limitations":["Integration ecosystem is limited compared to Intercom or Drift—not all messaging platforms supported","Channel-specific features (e.g., rich media, interactive buttons) may not be uniformly supported across all channels","Cross-channel conversation context requires backend state management; no mention of session persistence or context carryover","Legacy CRM system integration often requires workarounds rather than native connectors"],"requires":["Wodka.ai account with multi-channel deployment enabled","API credentials or authentication tokens for each target channel","Channel-specific configuration (e.g., Facebook App ID, WhatsApp Business Account)"],"input_types":["chatbot configuration","channel selection and credentials"],"output_types":["deployed bot instances per channel","unified conversation logs","channel-specific message formats"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_4","uri":"capability://data.processing.analysis.conversation.analytics.and.insights","name":"conversation-analytics-and-insights","description":"Basic analytics dashboard tracking chatbot performance metrics (conversation volume, intent distribution, user satisfaction, conversation length, drop-off points) with aggregated insights into conversation patterns. The system logs conversations and computes summary statistics, though the depth of analysis is limited compared to enterprise platforms—likely lacks sophisticated conversation mining, sentiment analysis, or predictive conversation optimization.","intents":["I want to see how many conversations my chatbot is handling and which topics come up most often","I need to identify where customers are dropping off in conversations so I can improve the flow","I want to measure chatbot performance and ROI with basic metrics"],"best_for":["small to mid-market teams with basic analytics needs","businesses starting to measure chatbot impact","teams not requiring sophisticated conversation mining or predictive analytics"],"limitations":["Analytics are basic—lacks sophisticated conversation analytics that power users need for optimization (e.g., sentiment analysis, conversation mining, predictive recommendations)","No custom metric definition or advanced segmentation","Limited historical data retention (exact retention period unknown)","No real-time alerting or anomaly detection","Conversation export and analysis capabilities not documented"],"requires":["Wodka.ai account with analytics dashboard access","Active chatbot with conversation history","Sufficient conversation volume for meaningful metrics (minimum ~100 conversations recommended)"],"input_types":["conversation logs","user interaction events"],"output_types":["aggregated metrics dashboard","conversation summaries","performance reports"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_5","uri":"capability://automation.workflow.freemium.model.with.usage.based.scaling","name":"freemium-model-with-usage-based-scaling","description":"Free tier providing core chatbot builder and deployment capabilities with reasonable usage limits (exact limits unknown), with paid tiers scaling based on conversation volume, number of bots, or advanced features. The pricing model allows experimentation without credit card friction, with transparent upgrade path as usage grows.","intents":["I want to try building a chatbot without committing to a paid plan or providing a credit card","I need a pricing model that scales with my business growth rather than fixed enterprise pricing","I want to understand costs upfront before deploying chatbots to production"],"best_for":["startups and bootstrapped companies with limited budgets","teams evaluating chatbot platforms before committing to larger platforms","small businesses with variable conversation volumes"],"limitations":["Free tier usage limits not explicitly documented—unclear when upgrade is required","Free tier likely excludes advanced features (e.g., custom integrations, advanced analytics, priority support)","No mention of free tier conversation volume limits or bot count restrictions","Pricing transparency could be improved with clearer tier comparison"],"requires":["Email address for account creation","No credit card required for free tier"],"input_types":["account signup information"],"output_types":["free tier account access","paid tier subscription"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_6","uri":"capability://tool.use.integration.crm.and.backend.system.integration","name":"crm-and-backend-system-integration","description":"Integration capabilities for connecting chatbots to CRM systems, databases, and backend services to enrich conversations with customer data and enable transactional actions (e.g., creating leads, updating customer records, querying order history). Integration is likely achieved through API connectors, webhooks, or pre-built integrations, though the ecosystem is limited and legacy system integration often requires workarounds.","intents":["I want my chatbot to look up customer information from our CRM and personalize responses","I need the chatbot to create leads in Salesforce when customers express interest","I want to query our database to answer customer questions about order status or account details"],"best_for":["businesses with existing CRM or backend systems","teams needing transactional chatbot capabilities","companies with modern, API-first backend architectures"],"limitations":["Limited integration ecosystem compared to competitors like Intercom or Drift—not all CRM systems have native connectors","Legacy CRM system integration often requires workarounds rather than native connectors","No mention of custom API integration framework or webhook support","Integration setup may require technical expertise despite no-code builder","Data synchronization and real-time updates not documented"],"requires":["Wodka.ai account with integration capabilities","API credentials or authentication tokens for target CRM/backend system","CRM or backend system with documented API","Potentially technical support for legacy system integration"],"input_types":["CRM/backend system credentials","API endpoint configurations","data mapping specifications"],"output_types":["enriched conversation context","transactional actions (lead creation, record updates)","customer data queries"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_7","uri":"capability://automation.workflow.conversation.handoff.to.human.agents","name":"conversation-handoff-to-human-agents","description":"Automatic escalation of conversations from chatbot to human agents when the bot cannot resolve a query or when the customer requests human assistance. The system likely maintains conversation context and history during handoff, allowing agents to continue the conversation without requiring the customer to repeat information. Handoff logic is configurable through the visual builder (e.g., trigger on specific intents, confidence thresholds, or explicit user requests).","intents":["I want the chatbot to escalate complex issues to human support agents automatically","I need agents to see the full conversation history when they take over from the chatbot","I want to configure which types of questions should always go to humans rather than the bot"],"best_for":["support teams using chatbots to handle routine queries while preserving human support for complex issues","businesses requiring seamless bot-to-human transitions","teams wanting to optimize support efficiency by automating simple queries"],"limitations":["Handoff mechanism and agent routing logic not documented—unclear how agents are assigned or queued","No mention of conversation context preservation or history visibility during handoff","Agent availability and queue management not documented","No SLA or response time guarantees for human escalation","Integration with existing support ticketing systems not mentioned"],"requires":["Wodka.ai account with human handoff enabled","Human agents or support team available to receive escalated conversations","Configuration of handoff triggers (intents, confidence thresholds, keywords)"],"input_types":["conversation context","handoff trigger configuration","agent availability status"],"output_types":["escalated conversation with context","agent assignment","conversation history"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_8","uri":"capability://tool.use.integration.embeddable.widget.and.website.deployment","name":"embeddable-widget-and-website-deployment","description":"Generation of embeddable JavaScript widget code that deploys the chatbot on websites without requiring backend changes or complex integration. The widget likely handles message rendering, user input capture, and communication with Wodka.ai backend services, with customizable styling and positioning options to match website branding.","intents":["I want to add a chatbot to my website by copying and pasting a single line of code","I need the chatbot widget to match my website's look and feel with custom colors and branding","I want to deploy the chatbot without involving my development team"],"best_for":["non-technical website owners and marketers","small businesses without dedicated development resources","teams wanting rapid website chatbot deployment"],"limitations":["Widget customization options likely limited to basic styling (colors, fonts, positioning)—no deep HTML/CSS customization","Widget performance and loading time not documented—may impact website performance if not optimized","No mention of offline functionality or fallback behavior if Wodka.ai service is unavailable","Widget analytics integration may be limited compared to custom implementations"],"requires":["Wodka.ai account with deployed chatbot","Website with HTML access or ability to add custom code","Modern web browser with JavaScript enabled"],"input_types":["chatbot configuration","widget styling preferences","website HTML"],"output_types":["embeddable JavaScript code snippet","deployed widget on website","conversation logs"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_wodka-ai__cap_9","uri":"capability://data.processing.analysis.user.satisfaction.and.feedback.collection","name":"user-satisfaction-and-feedback-collection","description":"Built-in mechanisms for collecting user feedback on chatbot responses (e.g., thumbs up/down ratings, satisfaction surveys, explicit feedback prompts) integrated into the conversation flow. Feedback is aggregated and displayed in the analytics dashboard to help teams identify problematic conversation paths and improve bot responses over time.","intents":["I want to measure whether customers are satisfied with chatbot responses","I need to identify which conversation paths are failing and need improvement","I want to collect feedback to justify chatbot investment to stakeholders"],"best_for":["teams focused on continuous chatbot improvement","businesses measuring customer satisfaction metrics","support teams optimizing conversation quality"],"limitations":["Feedback collection mechanisms not documented—unclear if feedback is optional or mandatory","No mention of sentiment analysis or NLP-based feedback interpretation","Feedback response rates and bias not addressed","No integration with external survey tools or feedback platforms","Feedback-driven bot improvement recommendations not mentioned"],"requires":["Wodka.ai account with feedback collection enabled","Configuration of feedback prompts or rating mechanisms","Sufficient conversation volume for meaningful feedback aggregation"],"input_types":["user satisfaction ratings","feedback text","conversation context"],"output_types":["aggregated satisfaction metrics","feedback summaries","improvement recommendations (if available)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Web browser with modern JavaScript support (Chrome, Firefox, Safari, Edge)","Active Wodka.ai account (free tier available)","Basic understanding of conversation design (no coding required)","Wodka.ai account with chatbot builder access","Pre-defined intent categories (minimum 2-3, recommended 5-15)","Training examples or sample utterances for each intent","Wodka.ai account","Selection of relevant template for business use case","Basic customization of template responses and intents","Wodka.ai account with multi-channel deployment enabled"],"failure_modes":["Visual builder abstracts away advanced NLP customization—no direct control over intent classification thresholds or entity extraction rules","Complex multi-turn conversations with dynamic context switching may require workarounds or custom logic blocks","No version control or collaborative editing—simultaneous edits by multiple team members not supported","Intent classification accuracy degrades with out-of-domain queries—no fallback to human escalation is automatic","Limited to predefined intents; discovering new customer intent patterns requires manual flow updates","No multi-language intent classification—language detection and routing not mentioned in product description","Confidence thresholds for intent matching are not user-configurable","Templates are generic and may not align with niche business processes—customization required for unique workflows","Limited template library (exact count unknown)—may not cover all industry verticals","Template updates are platform-controlled; users cannot contribute or share custom templates","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.72,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.3,"quality":0.25,"ecosystem":0.15,"match_graph":0.25,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:34.117Z","last_scraped_at":"2026-04-05T13:23:42.553Z","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=wodka-ai","compare_url":"https://unfragile.ai/compare?artifact=wodka-ai"}},"signature":"+T5fTSeunUj3f3IX09JGvcMNz7jge/0g8c1PeT7pzpBTAvKCHBnEmrxddegfBeWkuNJKwlLiuDtoEUxYQmJkAw==","signedAt":"2026-06-20T03:42:09.151Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/wodka-ai","artifact":"https://unfragile.ai/wodka-ai","verify":"https://unfragile.ai/api/v1/verify?slug=wodka-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"}}