Senior Analyst at a tech vendor with 10,001+ employees
Real User
Top 20
Jul 6, 2026
My main use case for Cognigy.AI Platform is building conversational AI agents. Regarding my main use case on Cognigy.AI Platform, we're also now looking into, or maybe mainly I'm looking into the domain also for integrating MCP within the conversational AI agents.
I built an agentic bot for customer support with Cognigy.AI Platform, where I had the possibility to come up with my own architecture. I constructed both an agent that was performing intent recognition. To understand the accuracy of the agent, I built a judge that was an LLM system evaluating the agent responses and intent accuracy recognition. This was useful because since the analysis section in Cognigy.AI Platform is limited, by using another system to judge the decision, I was able to track how accurately the system was performing intent recognition.
AI Engineer at a transportation company with 10,001+ employees
Real User
Top 20
Jul 3, 2026
Over the past year, my main use case for Cognigy.AI Platform has been to build both voicebots and chatbots for B2C use cases across several industries. Projects have included a voice assistant for an automotive dealership that automates appointment scheduling, handling identity verification, customer data lookup, and escalation without using staff involvement, as well as projects related to an internal employee-facing chatbot for a large corporate to handle ID and document processes, automating this entire process with self-service flows such as identity verification, document request, and appointment booking, as well as developing a multilingual, agentic hotel chatbot answering guest questions using both German and English. The project for building an assistant for an automotive dealership stands out as the most interesting and challenging because we had to integrate multiple databases and use API endpoints, which made it complex because of the way the endpoints were also built. Understanding users' requests and intents regarding when they want their input was very challenging as well.
My main use case for Cognigy.AI Platform is that we use it as the enterprise voice chat AI agent layer for Instill's Manager, HR, and employee workflows, which helped us expose Instill culture operating system and people insights through conversational experience. A quick, specific example of how I use Cognigy.AI Platform in one of those workflows is that our users, such as managers, can ask questions about why a team's trust score dropped, and they will receive Instill-backed answers through chat or voice.
Contact Center Platforms are crucial for managing customer interactions efficiently through multiple channels, enhancing communication and service delivery.Contact Center Platforms integrate various communication methods, such as voice, email, and chat, into a single interface. These platforms enhance customer experience and streamline the operations of businesses. They are designed to support different business models, facilitating seamless interactions and boosting productivity.What are the...
My main use case for Cognigy.AI Platform is building conversational AI agents. Regarding my main use case on Cognigy.AI Platform, we're also now looking into, or maybe mainly I'm looking into the domain also for integrating MCP within the conversational AI agents.
I built an agentic bot for customer support with Cognigy.AI Platform, where I had the possibility to come up with my own architecture. I constructed both an agent that was performing intent recognition. To understand the accuracy of the agent, I built a judge that was an LLM system evaluating the agent responses and intent accuracy recognition. This was useful because since the analysis section in Cognigy.AI Platform is limited, by using another system to judge the decision, I was able to track how accurately the system was performing intent recognition.
Over the past year, my main use case for Cognigy.AI Platform has been to build both voicebots and chatbots for B2C use cases across several industries. Projects have included a voice assistant for an automotive dealership that automates appointment scheduling, handling identity verification, customer data lookup, and escalation without using staff involvement, as well as projects related to an internal employee-facing chatbot for a large corporate to handle ID and document processes, automating this entire process with self-service flows such as identity verification, document request, and appointment booking, as well as developing a multilingual, agentic hotel chatbot answering guest questions using both German and English. The project for building an assistant for an automotive dealership stands out as the most interesting and challenging because we had to integrate multiple databases and use API endpoints, which made it complex because of the way the endpoints were also built. Understanding users' requests and intents regarding when they want their input was very challenging as well.
My main use case for Cognigy.AI Platform is that we use it as the enterprise voice chat AI agent layer for Instill's Manager, HR, and employee workflows, which helped us expose Instill culture operating system and people insights through conversational experience. A quick, specific example of how I use Cognigy.AI Platform in one of those workflows is that our users, such as managers, can ask questions about why a team's trust score dropped, and they will receive Instill-backed answers through chat or voice.