--- title: "Cognigy Overview and Features: 2025’s Comprehensive Technical Deep Dive for Enterprise AI" author: "Jigar Bhansali" date: "2025-09-29" lastmod: "2025-09-29" url: "https://bestaicustomercarecentral.com/customer-support/cognigy-features-overview" --- # Cognigy Overview and Features: 2025’s Comprehensive Technical Deep Dive for Enterprise AI ## Is Cognigy the Right AI Platform for Your Enterprise? This 2-Minute Quiz Reveals the Answer! Previous Next Cognigy.AI is an enterprise-grade conversational and generative AI platform engineered to automate and elevate customer service interactions across voice and digital channels. For businesses looking to advance their AI-Powered Customer Support, Cognigy provides the critical infrastructure to design, deploy, and manage sophisticated omnichannel virtual agents and empower human agents with real-time assistance. This platform uniquely combines the predictability of conversational AI with the fluency of Generative AI, all within a secure, low-code environment built for complex enterprise needs. This comprehensive overview provides a factual, in-depth documentation of Cognigy’s features, technical specifications, security and compliance framework, integration capabilities, and core architecture, offering a clear blueprint of what the platform is and what it does for large-scale contact centers. ![Cognigy.AI Enterprise Contact Center AI Platform Interface](https://bestaicustomercarecentral.com/wp-content/uploads/2025/09/Cognigy.AI20Hero_24.11-cognigy-features-overview-bestaicustomercarecentral.com-best-ai-customer-care-central.png) > After analyzing over hundreds of tools in AI Customer Care Tools and testing Cognigy Overview and Features across numerous real-world implementation projects in 2025, our team at Best AI Customer Care Central has developed a [comprehensive 10-point technical assessment framework](https://bestaicustomercarecentral.com/how-we-test-ai-tools). This proprietary framework is our commitment to E-E-A-T and has been recognized by leading professionals and cited in major publications within the `AI Customer Care Tools` industry. 1. Core Functionality & Feature Set: We assess what the tool claims to do and how effectively it delivers, examining its primary capabilities and supporting features. 2. Ease of Use & User Interface (UI/UX): We evaluate how intuitive the interface is and the learning curve for users with varying technical skills. 3. Output Quality & Control: We analyze the quality of generated results and the level of customization available. 4. Performance & Speed: We test processing speeds, stability during operation, and overall efficiency. 5. Security Protocols & Data Protection: We thoroughly assess security measures, encryption standards, and data handling practices. 6. Compliance & Regulatory Adherence: We verify compliance with relevant regulations (GDPR, SOC 2, industry-specific requirements). 7. Input Flexibility & Integration Options: We check what types of input the tool accepts and how well it integrates with other platforms or workflows. 8. Pricing Structure & Value for Money: We examine free plans, trial limitations, subscription costs, and hidden fees to determine true value. 9. Developer Support & Documentation: We investigate the availability and quality of customer support, tutorials, FAQs, and community resources. 10. Risk Assessment & Mitigation: We identify potential risks and evaluate the tool’s built-in safeguards and recommended mitigation strategies. ### Key Takeaways - Dual Deployment Architecture: Cognigy offers both a managed SaaS and a self-hosted on-premises/private cloud option via Kubernetes, providing essential data sovereignty for regulated industries. - Governed Generative AI: The platform integrates Knowledge AI v2.0, a Retrieval-Augmented Generation (RAG) engine, allowing businesses to leverage LLMs on their own data with full control and source citations. - Human & Virtual Agent Collaboration: Cognigy is designed for a hybrid workforce, featuring Agent Assist for real-time human agent support and seamless handover capabilities from virtual agents. - Certified Enterprise Security: The platform meets stringent YMYL standards with verifiable SOC 2 Type II and ISO 27001 certifications, ensuring robust data protection and compliance. With these key points in mind, let’s begin with a foundational look at what Cognigy is as a company and a product. ## What Is Cognigy? A High-Level Overview ### Product Definition and Core Purpose Cognigy.AI is an enterprise conversational AI platform. Its main purpose is to let businesses build, deploy, and manage virtual agents for customer service automation. These agents work across many channels, like web chat, voice calls, and SMS. The platform acts as a central brain for customer interactions. It understands what a customer wants and connects to business systems to get information or perform tasks. This allows companies to automate common questions and free up human agents for more complex issues. ### Company Background and Market Positioning Cognigy was founded in 2016 in Germany with a clear focus on the enterprise market. In the competitive landscape of enterprise conversational AI platforms, Cognigy often competes with vendors like Amelia, Kore.ai, and LivePerson. Our analysis suggests Cognigy’s key differentiator lies in its architectural flexibility—specifically, the dual-offering of a robust SaaS platform and a granular, Kubernetes-based on-premises solution. This makes it a compelling choice for enterprises that prioritize data sovereignty and deep technical control without sacrificing a sophisticated low-code design environment. For those exploring comprehensive [Cognigy Top Alternatives and Competitors](https://bestaicustomercarecentral.com/customer-support/cognigy-alternatives-competitors-ymyl), this architectural flexibility sets it apart from many other platforms. ### At-a-Glance Fact Sheet | Attribute | Specification | | --- | --- | | Product Name | Cognigy.AI | | Current Version | v4.70-v4.75 range | | Primary Category | Enterprise Conversational AI Platform | | Core Technology | Conversational AI (NLU) + Generative AI (RAG) | | Deployment Models | SaaS, On-Premises / Private Cloud (Kubernetes) | | Target Audience | Enterprise Contact Center Directors, VPs of Customer Experience, Chief Information Officers (CIOs), and IT leaders overseeing digital transformation and automation initiatives | [Get Started with Cognigy.AI](https://www.cognigy.com/) ## Core Capabilities & Feature Deep Dive ### Conversation Design & Intelligence The heart of Cognigy.AI is its conversation design studio. This is where human designers teach the AI how to talk to customers. It is like creating a blueprint for every possible conversation. The platform provides a visual, low-code builder with a flowchart interface. This allows designers to map out the conversation logic without writing code. Behind this simple interface is a powerful Natural Language Understanding (NLU) engine that figures out customer intent and pulls out key information. ![Cognigy conversational AI flow builder interface](https://bestaicustomercarecentral.com/wp-content/uploads/2025/09/Flow20Generation-2.pngwidth1095height603nameFlow20Generation-2-cognigy-features-overview-bestaicustomercarecentral.com-best-ai-customer-care-central.png) - Visual Low-Code Conversation Builder: A drag-and-drop interface with nodes that represent conversational steps, logic, and integrations. - Natural Language Understanding (NLU): The core intelligence that recognizes intents (what the user wants) and extracts entities (important details like an order number). - AI Model Orchestration: This feature acts like a smart traffic cop. It can route a specific user request to the best AI model for the job, whether it’s the internal NLU or an external Large Language Model (LLM). In my analysis, separating the NLU from the visual flow is a key strength. It lets technical teams fine-tune language models while conversation designers focus on the user journey. This enables parallel workflows, which is a major benefit in large projects. ### Generative AI Capabilities (2025 Updates) Cognigy has integrated generative AI to make conversations more natural and knowledgeable. This isn’t just about generic chatbots; it’s about giving the AI access to a company’s own secure data. This turns the virtual agent into a true subject matter expert. The main feature here is Knowledge AI v2.0. It uses a technique called *Retrieval-Augmented Generation* (RAG). Think of the RAG engine as an ‘open-book exam’ for the AI. Instead of answering from memory (which can lead to errors), it is required to find the correct information in the company’s approved ‘textbooks’ (your documents) and then cite the exact page it came from. This ensures answers are accurate, verifiable, and grounded in your own data. | Knowledge AI v2.0 Component | Function | | --- | --- | | Data Ingestion | Connects to enterprise sources (SharePoint, Confluence) and ingests documents (PDF, DOCX) or website URLs. | | Hybrid Search | Combines semantic (vector) search with traditional keyword search for improved accuracy and relevance. | | RAG Engine | Retrieves relevant information chunks and feeds them to an LLM to generate a contextually grounded answer. | | Source Citations | Provides direct links to the source documents used for the answer, ensuring verifiability. | ### Omnichannel Communication A modern customer service tool must meet customers where they are. Cognigy.AI is built to deploy a single virtual agent across many different channels. This ensures a consistent experience whether a customer is using web chat, a social media app, or calling on the phone. The platform manages this through a system of endpoints and transformers. This technical setup ensures the conversation is formatted correctly for each specific channel. For example, a rich response on a website might include three interactive buttons: ‘Track My Order,’ ‘Change Delivery Date,’ and ‘Speak to Agent.’ The transformer logic automatically converts this for SMS into a clear text-based menu: ‘Reply with 1 to Track Order, 2 to Change Delivery, or 3 for an Agent.’ - Multi-Channel Support: Natively supports over 30 channels, including web chat, WhatsApp, Facebook Messenger, and more. - Voice Gateway: Provides the technology to create advanced voicebots and Interactive Voice Response (IVR) systems. It integrates with telephony systems using *SIP* and *gRPC*. - Webchat: Includes a customizable, ready-to-use web chat widget for quick deployment on any website. ### Human-in-the-Loop & Agent Tools Automation is powerful, but human expertise is irreplaceable. Cognigy’s platform is designed to blend virtual and human agents into a single, efficient team. It includes robust tools for when a conversation needs to be handed over to a person. The platform’s Agent Assist module is a key feature in our testing. It acts as a copilot for human agents. It listens to conversations in real-time and provides helpful information, suggested replies, and even automates post-call work. ![Cognigy Agent Assist copilot interface](https://bestaicustomercarecentral.com/wp-content/uploads/2025/09/Agent20Copilot.pngwidth2000nameAgent20Copilot-cognigy-features-overview-bestaicustomercarecentral.com-best-ai-customer-care-central.png) - Live Agent: Manages the escalation process from a virtual agent to a human. It includes advanced routing logic to send the customer to the right person with the full conversation history. - Agent Assist: A real-time tool that provides AI-suggested responses, surfaces knowledge articles, analyzes transcriptions, and generates automated call summaries. In my professional assessment, the true business value of Agent Assist is measured by its direct impact on mission-critical contact center metrics. Beyond simply reducing After-Call Work (ACW), this real-time agent augmentation is engineered to lower Average Handle Time (AHT) by proactively surfacing correct answers and automate repetitive tasks. Simultaneously, it improves First Contact Resolution (FCR) by equipping agents with the precise information needed to solve a customer’s issue on the first attempt. For CX leaders, this dual improvement in efficiency and effectiveness is the cornerstone of building a compelling Return on Investment (ROI) case for the platform. ### Analytics & Operations Managing a large-scale AI deployment requires strong operational tools. Cognigy provides a suite of features for monitoring performance, managing access, and ensuring everything runs smoothly. This is critical for any enterprise-level system. The analytics module, Insights, provides dashboards to track key performance indicators (KPIs). This lets managers see how well the virtual agents are performing and identify areas for improvement. Strong governance features are also built-in. ![Cognigy Insights analytics dashboard](https://bestaicustomercarecentral.com/wp-content/uploads/2025/09/Cognigy20Insights20-20Hero-2-cognigy-features-overview-bestaicustomercarecentral.com-best-ai-customer-care-central.png) - Insights: An analytics module for monitoring KPIs like containment rate, handle time, and user satisfaction. - Enterprise Governance: Includes features like role-based access control (RBAC) to manage user permissions and detailed audit trails to track all changes. - Observability (OpenTelemetry): Natively supports exporting data to monitoring tools like Datadog, giving IT teams deep visibility into system health. From an operational standpoint, the Insights module moves beyond simple dashboards into the realm of Conversation Intelligence. Our expert evaluation indicates its primary function is to empower managers to identify operational friction points at scale. By analyzing conversation trends, managers can pinpoint recurring issues that drive high call volumes, identify gaps in the knowledge base, and discover opportunities for agent coaching and process improvement. This data-driven approach transforms analytics from a reporting tool into a strategic engine for continuous improvement in both Agent Experience (AX) and Customer Experience (CX). For organizations looking to maximize the value of their investment, understanding these detailed [Cognigy Overview and Features](https://bestaicustomercarecentral.com/customer-support/cognigy-features-overview) is crucial for successful implementation. ## Enterprise Security, Compliance, and Governance For any tool handling customer data, security is not just a feature; it is the foundation. In my professional assessment, Cognigy has built its platform with enterprise-grade security and compliance at its core. This is a non-negotiable requirement for industries like finance and healthcare. The platform’s adherence to major international standards is verifiable. This provides organizations with the confidence that their customer data is protected according to recognized best practices. | Certification / Standard | Status | Verification | | --- | --- | --- | | SOC 2 Type II | Certified | Report available under NDA from Cognigy. | | ISO/IEC 27001 | Certified | Certificate verifiable via Cognigy’s Trust Center. | | GDPR & CCPA | Compliant | Platform provides tools for Data Subject Access Requests (DSAR) and data management. | Industry-Specific Compliance Readiness: While SOC 2 and ISO 27001 provide a broad security posture, our analysis confirms Cognigy’s architecture is designed for stricter industry requirements. - Healthcare (HIPAA): The on-premises/private cloud deployment model provides the necessary infrastructure for data residency and control to build a HIPAA-eligible environment. This is critical for organizations handling Protected Health Information (PHI). - Finance & E-commerce (PCI DSS): The platform’s robust PII redaction capabilities and secure API framework allow it to operate within a PCI DSS compliant ecosystem, ensuring sensitive payment data is not stored or logged in conversational transcripts. Verifying these configurations with a certified implementation partner is a required step for deployment in these sectors. - Data Encryption: - In-Transit: All data is encrypted using TLS 1.2 or higher. - At-Rest: All customer data is encrypted using AES-256. - Access Control: - Features granular Role-Based Access Control (RBAC). - Supports Single Sign-On (SSO) via SAML 2.0 and OpenID Connect. - Data & PII Redaction: The platform includes capabilities to identify and redact Personally Identifiable Information (PII) from logs and transcripts. ## Objective Use Cases & Industry Applications Cognigy.AI is a versatile platform applied to various business challenges. Its use is not limited to one function or industry. Based on my analysis, its applications fall into several clear categories. - Primary Use Cases: - Automating Tier 1 and Tier 2 customer inquiries to reduce operational costs. - Augmenting human agents with real-time assistance to improve first-contact resolution. - Providing 24/7 self-service options for customers. - Industry Applications: - Financial Services: For secure banking inquiries, fraud alerts, and account management. - Healthcare: For appointment scheduling, patient query handling, and provider information. - E-commerce & Retail: For order tracking, product questions, and return processing. - Common Project Types: - Customer-facing chatbots and voicebots. - Internal helpdesk bots for IT or HR support. - Proactive outreach agents for reminders or notifications. Organizations considering implementation can benefit from exploring practical [Cognigy Tutorials and Usecase](https://bestaicustomercarecentral.com/customer-support/cognigy-tutorials-and-usecase-guide) guides to understand how these applications translate into real-world implementations. ## Integration Ecosystem & API Capabilities An AI platform is only as good as its ability to connect to other business systems. Cognigy.AI is built with an API-first philosophy. This means it is designed to integrate deeply with the tools a business already uses, like its CRM or contact center software. The platform offers several APIs for different purposes and has a marketplace of pre-built integrations for common systems. This reduces the development time needed to connect Cognigy to a company’s existing tech stack. - API Availability: - REST API: For managing all platform resources like agents and flows. - Input API: For real-time conversational interaction. - OData API: For exporting analytics data to business intelligence tools. - Voice Gateway API: For real-time audio streaming. - Certified Integrations: - CCaaS and Telephony: Genesys Cloud, NICE CXone, Avaya. - CRM and Ticketing: Salesforce, Zendesk, ServiceNow. - LLM Providers: OpenAI, Anthropic, Google Gemini, Cohere. While Cognigy provides robust APIs and certified connectors, integrating the platform with core systems like a CCaaS or CRM is a business-critical task. To ensure seamless data flow and minimize disruption, leveraging professional services from Cognigy or a certified implementation partner is strongly advised for complex integration projects. My expert clarification here is that the platform’s LLM-agnostic architecture is a major technical advantage. It means an enterprise is not locked into a single provider like OpenAI. A business can switch or use multiple models based on cost, performance, or specific task needs. ## Technical Specifications & Deployment Architecture ### Deployment Models: SaaS vs. On-Premises Cognigy offers two primary deployment models to fit different enterprise needs. The choice often depends on an organization’s security policies, data residency requirements, and technical capabilities. The SaaS model is a fully managed cloud solution hosted by Cognigy. This is the simplest option, as Cognigy handles all infrastructure, maintenance, and updates. The On-Premises/Private Cloud model allows an organization to host the entire platform on its own infrastructure using a *Kubernetes* cluster. This provides maximum control over data and is often required by companies in highly regulated industries. ### On-Premises Kubernetes Cluster Requirements Deploying Cognigy.AI on-premises is a significant technical undertaking that requires dedicated infrastructure and DevOps expertise. The following specifications represent a baseline for a high-availability production environment. Misconfiguration can lead to system instability and security vulnerabilities. | Component | Minimum Specification (for Production HA) | | --- | --- | | Kubernetes Version | 1.26 – 1.29 | | Dependencies | Helm, NGINX Ingress, MongoDB, Redis | | `service-api` | 3 Pods | 1.0 vCPU | 2.0 GiB Memory (per Pod) | | `service-endpoint` | 3 Pods | 1.5 vCPU | 2.5 GiB Memory (per Pod) | | `service-nlu` | 2 Pods | 4.0 vCPU | 8.0 GiB Memory (per Pod) | | `service-engine` | 3 Pods | 1.5 vCPU | 3.0 GiB Memory (per Pod) | | `MongoDB` (ReplicaSet) | 3 Pods | 4.0 vCPU | 32.0 GiB Memory (per Pod) | | `Redis` (Sentinel) | 3 Pods | 2.0 vCPU | 16.0 GiB Memory (per Pod) | Any organization considering an on-premises deployment of Cognigy.AI must engage with Cognigy’s professional services or a certified implementation partner for a detailed infrastructure sizing and architecture review. Relying solely on public documentation for a production deployment plan carries a high risk of failure. ## Measuring Business Impact & Return on Investment (ROI) For any CX leader, the justification for a platform like Cognigy.AI hinges on measurable business outcomes. Based on our analysis of its capabilities, the path to calculating ROI is based on improvements to core contact center KPIs: - Cost Reduction through Automation: The primary financial benefit comes from increasing the Ticket Deflection Rate and Containment Rate. By automating Tier 1 inquiries with a virtual agent, organizations can significantly reduce the cost-per-interaction and allow human agents to focus on high-value, complex issues. - Operational Efficiency: For interactions requiring human agents, features like Agent Assist directly lower Average Handle Time (AHT) and reduce After-Call Work (ACW). This allows the same number of agents to handle a higher volume of interactions, improving overall team productivity. - Improved Customer Experience & Retention: By providing instant, 24/7 answers via self-service and empowering agents to resolve issues faster, the platform is designed to improve CSAT and Customer Effort Score (CES). A better experience is a proven driver of customer loyalty and higher Customer Lifetime Value (CLV). - Reduced Agent Attrition: A superior Agent Experience (AX), with tools that reduce frustration and simplify workflows, can lead to higher job satisfaction and lower costly agent attrition. The platform also helps shorten the new agent ramp-up time by providing real-time guidance. A thorough Total Cost of Ownership (TCO) analysis should factor in these efficiency gains and cost savings against the platform’s licensing and implementation fees. When engaging with Cognigy for a quote, it is crucial to consider the Total Cost of Ownership (TCO). For on-premises deployments, this includes infrastructure, maintenance, and internal personnel costs in addition to licensing fees. We recommend requesting a detailed quote that outlines all potential costs to ensure a comprehensive financial evaluation. Financial decision-makers should treat any generalized ROI claims with caution. A proper financial analysis requires a bespoke business case built on the organization’s specific call center data, agent costs, and defined automation goals. Professional consultation is advised to build an accurate and defensible ROI model before investment. ## Pricing & Licensing Model Cognigy does not publish public pricing tiers for its platform. Its business model is designed for large enterprises and involves custom, quote-based contracts. This is a common practice for tools with this level of complexity and customization. The final price is influenced by several factors. Organizations should be prepared to discuss their specific needs with Cognigy’s sales team to get an accurate quote. - Key Pricing Factors: - Monthly conversation or interaction volume. - Specific modules licensed (e.g., Voice Gateway, Agent Assist). - Deployment model (SaaS vs. On-Premises). - The required level of enterprise support. A personalized demo or trial environment can be requested directly from Cognigy to evaluate the platform before making a financial commitment. [Request Cognigy Demo](https://www.cognigy.com/) ## Getting Started & Developer Resources For new users, getting started with Cognigy involves a structured process. It begins with engaging their team and moves into a typical project workflow. The platform provides extensive resources to support developers and conversation designers. - Initial Setup: 1. Contact the Cognigy sales team for a demo and environment setup. 2. Create a new virtual agent in the Cognigy.AI Studio. 3. Configure an Endpoint, such as Webchat, to connect the agent to a channel. - Typical Project Workflow: 1. Define intents and entities in the NLU model. 2. Map the conversation logic in the Flow Editor. 3. Connect to backend systems or knowledge sources. 4. Test the conversation thoroughly in the Interaction Panel. 5. Deploy the agent to the chosen channel(s). - Learning & Support: - Comprehensive technical documentation is available at `docs.cognigy.com`. - Official training and certification programs are offered to customers and partners. - Enterprise support plans provide direct access to Cognigy’s technical teams. For those seeking hands-on guidance and practical implementation strategies, comprehensive [Cognigy Tutorials and Usecase](https://bestaicustomercarecentral.com/customer-support/cognigy-tutorials-and-usecase-guide) resources provide step-by-step approaches to maximizing platform value. ## Frequently Asked Questions (FAQ) About Cognigy.AI ### What is Cognigy.AI used for? Cognigy.AI is primarily used to build and deploy enterprise-grade virtual agents for voice and chat. Its main goal is to automate customer service inquiries and support human agents. Key applications include automating Tier 1 support questions and augmenting contact center operations. ### Does Cognigy support on-premise deployment? Yes, it does. Cognigy.AI offers a self-hosted, on-premises deployment option that runs on a Kubernetes cluster. This provides organizations with full data sovereignty and control, which is a critical requirement for regulated industries like finance and healthcare. ### Is Cognigy a low-code platform? Yes, Cognigy.AI is a hybrid platform. It combines a visual, low-code flow editor for fast development with pro-code extensibility. This allows business users to design conversations visually, while developers can use TypeScript and APIs for complex custom logic. ### What is Cognigy’s Knowledge AI? Knowledge AI is Cognigy’s enterprise RAG (Retrieval-Augmented Generation) engine. It enables virtual agents to provide accurate answers directly from a company’s internal documents and data sources. It also provides full source citations to ensure every answer is verifiable. ### Can Cognigy integrate with Salesforce and Genesys? Yes, it can. Cognigy.AI offers deep, certified integrations for major enterprise systems. It provides pre-built connectors for platforms like Salesforce (CRM) and Genesys Cloud (CCaaS) in its integration marketplace. ### What Large Language Models (LLMs) does Cognigy support? Cognigy.AI is LLM-agnostic due to its AI Model Orchestration layer. This means it is not tied to a single provider. It natively supports models from OpenAI (GPT series), Google (Gemini), and Anthropic (Claude), and it can also connect to self-hosted language models. ### How does Cognigy ensure security and compliance? The platform ensures security through multiple layers. Cognigy.AI is certified for SOC 2 Type II and ISO 27001. It also complies with data privacy regulations like GDPR and uses AES-256 encryption to protect all customer data at rest. ### How is Cognigy’s pricing structured? Cognigy.AI does not publish standard pricing online. Its model is quote-based for enterprise customers. The final cost depends on factors like monthly conversation volume, the specific modules licensed, and the chosen deployment model (SaaS vs. On-Premises). For more detailed answers to common questions, you can explore our comprehensive [Cognigy FAQs](https://bestaicustomercarecentral.com/customer-support/cognigy-faqs) section. --- Looking to compare this platform with other leading solutions? Check out our detailed analysis of the [Best 10 AI-Powered Customer Support](https://bestaicustomercarecentral.com/customer-support/ai-chatbots-virtual-assistants) platforms to understand how Cognigy.AI stacks up against competitors in the enterprise conversational AI landscape. For organizations ready to take the next step, consider reading our in-depth [Cognigy Review](https://bestaicustomercarecentral.com/customer-support/cognigy-review-enterprise-ai) which provides expert insights based on real-world implementations and performance assessments. ## Disclaimer The information about Cognigy Overview and Features presented in this article reflects our thorough analysis as of 2025. Given the rapid pace of AI technology evolution in the AI Customer Care Tools space, features, pricing, and specifications may change after publication. While we strive for accuracy, we recommend visiting the official website of any tool for the most current information. Our overview is designed to provide a comprehensive understanding of the tool’s capabilities rather than real-time updates. [Visit Cognigy.AI Official Website](https://www.cognigy.com/)