# Symflowise.ai - Aligned Documentation This document provides a consolidated overview of the Symflowise.ai platform, detailing its project requirements and key user journeys. The information herein is synthesized from existing project documentation. **Part 1: Symflowise.ai - Overview and Project Requirements** **1.0 Introduction to Symflowise.ai** Symflowise.ai is an advanced AI-powered customer service platform designed to enhance user engagement, streamline call handling, and provide in-depth analytics. It aims to offer a comprehensive solution for businesses looking to optimize their customer support operations. Key differentiators include: * **Multi-modal AI Support:** Leveraging models like Gemini for sophisticated interaction handling. * **Enhanced User Interaction Tools:** Featuring screen sharing capabilities with privacy filters. * **Personalized Agent Development:** Offering personalized training modules for support agents, including AI-driven performance assessment. * **Compliance and Quality Focus:** Incorporating a compliance-focused review process, AI-to-human escalation workflows, and quality control mechanisms, with a specific emphasis on financial sector requirements. * **Multi-Channel Support:** Covering voice, chat, and web portal interactions. * **B2B SaaS Model:** Targeting markets in Africa, Canada, and the USA with a focus on multilingual support and ease of onboarding. **2.0 Project Requirements** **2.1 Core Platform Features & Capabilities:** * AI-driven ticket handling (initial handling with human escalation). * AI resolves routine queries (e.g., FAQs, order tracking) via chat/voice. * Human escalation for complex issues (e.g., payment disputes) with context transfer (chat history, CRM data). * Multi-language support (English and French). * Screen sharing capabilities with privacy filters (secure co-browsing). * Analytics dashboard (track metrics like resolution time, sentiment trends, escalation rates). * User-Friendly Interface for customers and agents. * Personalized training modules for support agents (individual learning paths, AI-driven performance assessment, documentation updates based on training data). * Compliance-focused review process for AI responses. * AI to human escalation workflow. * Quality control mechanisms. * Customers can submit tickets via chat, voice, or web forms. * Agents (AI and human) manage tickets. * Brand-aligned chatbots handling Tier-1 inquiries. * Real-time coaching tools for agents. * AI-curated Knowledge Base with automatic updates from customer interactions and product databases. * Intelligent call routing. * AI-guided resolution paths. * Onboarding automation for new clients (guided setup, workflow configuration). * Scenario-based learning and interactions (cultural sensitivity, communication styles). * Capturing user inputs through structured questionnaires. * Applying predefined rubrics for assessment. * Displaying results to assess cultural sensitivity and communication preferences. * Spam defense (ML-based pattern recognition, filters spam calls). * AI-Enhanced Bulk Outreach (automated multi-contact campaigns with smart follow-ups). * Interactive Voice Experiences (branded character interactions for upselling, celebrity voice cloning). **2.2 Technical Requirements:** * Multi-model AI support (Gemini integration mentioned). * Integration with existing telephony and messaging platforms. * Consideration for platforms like Amazon Connect or Google Dialogflow, with potential custom solutions. * Geo-redundant cloud architecture with automatic failover (target 99.99% uptime). * Omnichannel sync: Unified customer journey tracking across voice/chat/email/social with context preservation. * Wait time optimization (<2m wait times, queue callback). * Skills-based + customer value routing. * Real-time speech analytics engine for sentiment analysis. * Neural network pattern recognition for spam detection. * Self-learning semantic search system for knowledge management. * Auto-Scaling Workforce Management (dynamically allocates AI/human resources). * Predictive load forecasting. * Agent skill matching. * Elastic infrastructure. * Real-Time Quality Assurance (automates call monitoring and evaluation). * Multilingual TTS/STT (Text-to-Speech/Speech-to-Text). * Visual IVR integration. * API for external system communication. * Scalable architecture to handle multiple simultaneous users and future content expansions. * Easy update of questionnaires and scoring logic (maintainability). **2.3 Integration Requirements:** * **CRM Integrations:** * **Salesforce:** Sync customer profiles, interaction history, tickets; leverage Salesforce Einstein for predictive analytics; trigger Salesforce actions; auto-populate client history; sync cases and knowledge articles. * **HubSpot:** Sync contacts/deals; route queries from HubSpot chatbots; feed AI metrics to HubSpot dashboards; map marketing/sales workflows; embed knowledge base in chat widgets. * **Zendesk:** Sync tickets, automate responses, route escalations; prioritize tickets using SLA data; integrate KB articles. * **ServiceNow:** Prioritize tickets using SLA data; integrate KB articles. * **Messaging Integrations:** * **Microsoft Teams:** Real-time AI guidance during Teams-based support; archive regulated chat history. * **Slack:** Notify agents of AI-escalated cases. * **Knowledge Base Integrations (User-Side Knowledgebase):** * Pre-built connectors for: Asana, Box, Confluence, Dropbox, Egnyte, Figma, Freshservice, GDrive, GitLab, GitHub, Gmail, Gong, Google Groups, Google Sites, Greenhouse, Guru, Jira, Lumapps, Looker, Miro, Microsoft Teams (for content), Notion, OneDrive, Outlook, Salesforce (for content). * Specific use case for **Confluence/Jira:** Deflect tickets by linking helpdesk queries to Confluence documentation. * **Telephony Platforms:** Integration with existing telephony systems. * **Payment Processing Integration:** For self-service resolution. * **LMS/CMS Integration:** For training module personalization. **2.4 Compliance and Security Requirements:** * Privacy filters for screen sharing. * Specific focus on financial sector requirements. * Data privacy during handoff (human escalation). * Real-time CRM sync (implies secure connection). * Encryption for sensitive data (e.g., payment history). * Audit trails for compliance review and other actions. * Version control for compliance updates (AI responses). * Consent logging for screen sharing. * Masking of sensitive fields (e.g., passwords). * Spam pattern sharing (FedRAMP mentioned). * DNC list compliance for bulk outreach. * Consent verification for bulk outreach. * Cryptographically signed logs for spam defense. * Voiceprint licensing logs. * Encrypted recordings for real-time quality assurance. * Bias-free scoring models for QA. * Audit-ready evaluation logs for QA. * Data residency compliance. * GDPR-compliant data deletion. * Voice data anonymization. * Transaction audit logs. * PCI-DSS compliance for payment processing. * Regulated file governance (e.g., healthcare, finance) for Egnyte. * Secure document sharing (Box). * Audit email communication (Gmail). * Archive regulated chat history (Microsoft Teams). * Email retention policies (Outlook). * Data protection and accessibility for all users. **2.5 Data Handling and Analytics Requirements:** * Analytics and Reporting: Includes sentiment analysis, ticket trend tracking. * Post-call analytics by language. * Confidence thresholds for AI escalation. * Performance analytics for training module personalization. * Data aggregation for analytics dashboard. * Visualization of data in dashboards. * Data export for reporting. * Role-based access for analytics. * Real-time vs. historical views for analytics. * Customer Sentiment Tracking: Real-time voice/text analysis with emotion detection. * AI-powered workload forecasting. * Agent Performance Management: Real-time coaching tools, customer history integration. * Response pattern analysis for bulk outreach. * Voice fingerprinting and behavior analysis for spam defense. * Scenario performance metrics for interactive voice experiences. * Predictive load forecasting data. * Performance benchmarking data. * Resource utilization metrics. * CSAT prediction. * Store user responses for comparison and analysis. * Generate reports based on history and user profiles. **2.6 Deployment and Operational Requirements:** * B2B SaaS business model. * Client onboarding with customizable support channels and analytics access. * Target Markets: Africa, Canada, USA. * Emphasis on multilingual support and web portal usability in Africa. * Easy Onboarding: Simple setup for companies. * User-friendliness and smooth onboarding design. * Performance Monitoring: Track loading times, uptime, user interactions. * Feedback gathering from early users. * Regular updates and improvements. * Relevant and up-to-date landing page content. * Cost Optimization: AI-powered workload forecasting, automated routine task handling. * Infrastructure Reliability: Geo-redundant cloud architecture, 99.99% uptime target. * Prebuilt industry templates (e.g., e-commerce) for onboarding. * Error handling for API failures during onboarding. * Scalability for future content expansions. * Intuitive navigation with clear instructions. **Part 2: Symflowise.ai - User Journeys** **3.0 Introduction to User Roles** The Symflowise.ai platform is designed for several key user roles, each with distinct interactions and goals: * **End-Users/Customers:** Individuals seeking support or information. * **Contact Center Agents (Human):** Support staff handling customer inquiries. * **AI Agents:** Automated systems providing initial support and task execution. * **Administrators/Client Admins:** Personnel responsible for platform setup, configuration, and management. * **Supervisors/QA Personnel:** Staff focused on monitoring service quality and agent performance. * **Campaign Managers:** Users responsible for planning and executing bulk outreach campaigns. **4.0 Detailed User Journeys** **4.1 End-Users/Customers (Seeking Support)** * **Initiation/Engagement:** * Contacts support via voice, chat, or web portal/form. * May select language preference (English/French). * **Key Interactions & Touchpoints:** * Interacts with an AI agent for initial query resolution (FAQs, order tracking). * May use a Visual IVR. * May search or be directed to a knowledge base. * Provides details and answers questions. * May undergo identity verification. * May grant screen sharing permission to a human agent. * Receives updates/solutions via text/email. * **Decision Points & Potential Paths:** * **AI Resolution:** Issue resolved by AI. -> Journey ends. * **Escalation to Human Agent:** If AI cannot resolve or user requests. * **Callback Option:** Offered if wait times are high. * **Tools/Features Interacted With:** * Web chat, voice call systems, web forms. * Knowledge base, screen sharing UI, multi-language options, Visual IVR. * **Typical Outcome/Goal:** * Issue resolved, question answered, information obtained, service request fulfilled. * Positive customer experience. **4.2 Contact Center Agents (Human)** * **Initiation/Engagement:** * Logs into the agent platform and sets availability. * **Key Interactions & Touchpoints:** * Receives escalated or directly assigned tickets/interactions (voice, chat, web). * Views customer context from AI/CRM (Salesforce, HubSpot). * Accesses knowledge base (Confluence, Jira). * Uses AI response suggestions. * May use screen sharing with privacy filters. * Updates ticket status and logs interactions. * Receives real-time coaching and accesses personalized training. * **Decision Points & Potential Paths:** * **Resolve Issue:** Successfully resolves query. -> Ticket closed. * **Escalate Further:** To specialized team or supervisor if needed. * **Follow-up:** Schedules follow-up if immediate resolution isn't possible. * **Tools/Features Interacted With:** * Agent dashboard, CRM, knowledge base, AI suggestions, screen sharing, ticketing system, training modules, coaching tools. * **Typical Outcome/Goal:** * Resolve customer issues efficiently (FCR, handle time). * Provide excellent customer service (CSAT). * Achieve performance targets and update records accurately. **4.3 AI Agents (Automated Interaction Flow)** * **Initiation/Engagement:** * Automatically engages on customer initiation (call, chat, form submission). * **Key Interactions & Touchpoints:** * Uses NLU (Gemini) to understand customer intent. * Accesses knowledge bases and integrated systems for answers. * Provides responses (TTS for voice, text for chat). * Manages conversation context and performs real-time sentiment analysis. * Filters spam. * **Decision Points & Potential Paths:** * **Resolve Query:** Successfully resolves. -> Interaction ends. * **Escalate to Human Agent:** If complex, sentiment is negative, or user requests. Transfers context. * **Compliance Review:** AI responses may go to human review in regulated industries. * **Tools/Features Interacted With:** * NLU/NLP (Gemini), STT/TTS, knowledge base APIs, sentiment analysis engine, spam detection, escalation workflows, CRM data access. * **Typical Outcome/Goal:** * Resolve Tier-1 inquiries automatically (call deflection). * Provide 24/7 instant responses. * Accurately identify need for human escalation and gather context. **4.4 Administrators/Client Admins (Platform Setup & Management)** * **Initiation/Engagement:** * Logs into the administration portal. * **Key Interactions & Touchpoints:** * Goes through guided onboarding and setup. * Configures support channels, branding, multi-language options. * Manages integrations (CRMs, KBs). * Sets AI agent parameters and intelligent routing rules. * Manages user accounts and roles. * Creates/modifies automated workflows and escalation paths. * Accesses analytics dashboard for platform monitoring. * **Decision Points & Potential Paths:** * Decides on specific configurations for channels, AI, routing. * Manages user roles and integration setups. * **Tools/Features Interacted With:** * Admin portal, onboarding tools, workflow configuration, integration management, user management, analytics dashboard. * **Typical Outcome/Goal:** * Onboard company, configure platform to business needs, manage users, maintain operational efficiency, gain insights via analytics. **4.5 Supervisors/QA Personnel (Monitoring & Quality Assurance)** * **Initiation/Engagement:** * Logs into the platform with supervisor/QA credentials. * **Key Interactions & Touchpoints:** * Monitors real-time agent interactions (possibly with QA AI). * Views live dashboards of agent activity and service levels. * Reviews AI and human agent interactions (recordings, transcripts). * Uses QA AI for automated evaluation (compliance, CSAT prediction). * Validates AI responses in compliance reviews. * Provides feedback and identifies training needs. * Accesses analytics for performance tracking. * **Decision Points & Potential Paths:** * **Intervene in Interaction:** May join or take over if necessary. * **Flag for Review/Feedback:** Marks interactions for follow-up. * **Adjust Processes:** Identifies areas for improvement. * **Tools/Features Interacted With:** * Supervisor dashboard, QA AI tools, recording playback, analytics, performance metrics, compliance review interface, coaching tools. * **Typical Outcome/Goal:** * Ensure high service quality, maintain compliance, improve agent performance, optimize operations, achieve quality metric targets. **4.6 Campaign Managers (Bulk Outreach)** * **Initiation/Engagement:** * Logs into the bulk outreach module ("SuperCalls AI"). * **Key Interactions & Touchpoints:** * Sets up campaigns: defines objectives, uploads contact lists, creates dynamic scripts, configures smart follow-ups. * Launches automated multi-contact campaigns. * Monitors campaign performance (connection rates, lead qualification, voicemail drop effectiveness). * Ensures DNC list compliance and manages consent verification. * **Decision Points & Potential Paths:** * **Adjust Campaign:** Modifies scripting or targeting based on performance. * **Pause/Stop Campaign:** Halts a campaign if needed. * **Tools/Features Interacted With:** * Bulk outreach interface, dynamic scripting tools, contact list management, campaign analytics, voicemail drop, compliance tools. * **Typical Outcome/Goal:** * Execute automated outreach campaigns successfully. * Achieve campaign objectives (e.g., lead generation). * Ensure compliance with regulations. * Optimize campaign effectiveness.