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Conversational AI
RFI & RFQ

Based on 100+ Conversational AI RFIs we have compiled for you the most important questions you need answers to, when selecting a Conversational AI platform for your business.

RFI_Request for Information

Product Overview

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What's your Product's name? Cognigy.AI - The Low-code AI platform for Contact Center Automation

What is the main focus of your product?

Cognigy.AI is the leading enterprise conversational automation platform for building advanced, integrated conversational automation solutions.  Our customers are spread across the globe and include, but are not limited to, industries such as insurance, banking, automotive, utilities, retail, FMCG, pharma, retail and customer goods. Cognigy.AI is used to serve customer requests in a variety of different domains.

What are the key features of your product that differentiate it from competitors?

1. Easy to use graphical conversation flow editor allows conversations to be built without code, no technical skills required
2. Built-in NLP with industry leading accuracy for intent recognition
3. Open source extensions repository with drag and drop installation (pre-built connectors for SalesForce, ServiceNow, Microsoft Office365 and many more)
4. SaaS, Dedicated hosting or On-Premises deployment options
5. Seamless live agent handover for contact center integration
6. Rapid project implementation time frames
7. Machine-learning agnostic (built-in connectors for Watson, Dialogflow, LUIS and open NLP pipelines)

https://www.cognigy.com/products/cognigy-ai

What are the target industry sectors that your product specializes in?

Cognigy.AI solutions are industry agnostic, providing a perfect solution for any organization looking to interact with people in a more natural way.

Cognigy.AI's intent collections and pre-built solutions for various industries enable a quick start into a successful conversational AI project.

What are the primary chatbot building features offered by your product?

Cognigy.AI is a highly-flexible conversational automation platform to build advanced, integrated enterprise virtual agents for customer and employee service on chat and voice channels.

Cognigy.AI enables business users to create human-like automated conversations with the graphical conversation editor that harnesses the power of the Cognigy NLU in an easy to use format without the need for writing code.

https://www.cognigy.com/products/cognigy-ai

What skills does a bot developer require to use your product?

Cognigy.AI is built for non-technical users and offers a comprehensive selection of conversational building, NLU training and third party integration tools that require minimal programming knowledge to use. This even goes for back-end integrations, as many have been pre-built and therefore do not require custom development. Cognigy.AI also offers a fully featured developer CLI for technical users to build Cognigy.AI projects in code from their preferred IDE.

Please provide a sample of existing customers.

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Conversation Design

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How fast can a virtual agent be developed and deployed?

With Cogngiy.AI, your first basic virtual agent is deployed within a few clicks after logging in. This is achieved by offering in-tool templates and user journeys that show new users how to get started. More complex conversational flows and back-end interactions can be added and built from the ground up with deployment to channels within hours of creating agents.

https://docs.cognigy.com/docs/journeys

How are virtual agent output dialogs created and managed?

The conversation flow editor nodes control the logic of the conversation and virtual agent output. "Say" nodes are used to manage dialog output and include built-in menus to customize the output for each channel the agent has been deployed to. A default option is also available that automatically reformats text and rich media messages for output into any of the supported channels.

https://docs.cognigy.com/docs/say-nodes

How does the product interpret user messages and manage output dialogs?

Projects created within the Cognigy.AI platform consist of multiple "flows" which contain simple graphical node based conversation flows. The user interface is designed for by non-technical users but offers optional code nodes to fulfill the needs of developers. The flows are extremely flexible via use of the built-in node collection which come with options for performing dialog output, conversation logic, contact management or external communications.

https://docs.cognigy.com/docs/flows

Do you provide any pre-built agents for immediate deployment?

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Natural Language Understanding

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Does your product include an NLU component and how is it applied?

The Cognigy NLU comes built-in to the product and offers industry-leading performance (benchmarks available). The NLU features a smart intent building tool where user example sentences are trained via machine learning to the NLU model. The NLU results are published within the flow editor for users to easily test, review and develop their agents.

https://docs.cognigy.com/docs/nlu-natural-language-understanding

Is it possible to use an external NLU service with your product?

An external NLU can easily be connected and used with Cognigy.AI virtual agents using the NLU connector feature that allows NLU services such as Watson, MS LUIS and Dialogflow to be used for added flexibility with intent recognition and slot mapping.

https://docs.cognigy.com/docs/nlu-connectors

How effective is the NLU for recognizing user intents?

The Cognigy NLU has proven to outperform key industry competitors for user intent recognition. Cognigy.AI allows non-technical users to apply advanced machine learning algorithms to trained user example sentences via a simple and easy to understand user interface that enables user intent recognition with market leading accuracy. More information regarding benchmark testing can be found on our website.

https://www.cognigy.com/products/cognigy-ai

Is the NLU able to build on its understanding and learn from customer interactions?

Cognigy.AI virtual agents constantly improve their understanding by adding misunderstood phrases to their existing machine learning intent records when users confirm this is appropriate. The Cognigy.AI Intent Trainer also allows platform users to review misunderstood inputs to improve the accuracy of the Machine Learing Intents manually. It is easy to add an input text from a user as an example sentence to a selected ML Intent, or add it to the Reject Intent of a Flow.

https://docs.cognigy.com/docs/intent-trainer-1

Can external NLU services be used with your product?

Cognigy.AI offers full support and customization options for integrating an external NLU service such as Watson, MS LUIS and Dialog flow with Cognigy.AI virtual agents. The NLU connectors feature provides the integration channel for connecting to an NLU provider. Once set up, the external NLU is made interchangable throughout the platform alongside the built-in Cognigy NLU.

https://docs.cognigy.com/docs/nlu-connectors

Which languages does the product support?

The Cognigy NLU currently 20+ languages including: Generic, Danish, English, German, Japanese, Korean, Spanish, Dutch, Arabic, Finnish, French, Italian, Norwegian, Polish, Swedish, Thai, Chinese, Vietnamese, Portuguese. Output messages can be built in any language and it is also possible to incorporate external translation services within conversation flows.

https://docs.cognigy.com/docs/nlu-languages

Do you provide tools to assess the quality of training models?

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Contact Center Automation

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Is it possible to handover conversations to human contact center agents?

Cognigy.AI provides a built-in agent handover node which can be used if a request from a user is an edge case that is just too specific to be recognized by the virtual agent. The bot can offer the user to be forwarded to a support agent, a real human, that can intercept the conversation and help the customer manually without the necessity of changing channels.

https://docs.cognigy.com/docs/handover-settings

Can the product support both chat and voice conversations?

Cognigy.AI provides a voice channel connector called the the Cognigy Voice Gateway. This feature allows any virtual agent flows to be deployed to voice channels by incorprating text to speech and speech to text services inline with message input and output. The same conversation flow can be deployed to any number of output channels enabling simple conversation management in chat or vocie from a single flow.

https://www.cognigy.com/products/voice-gateway

Can the conversation history and data context of a conversation be sent to human agents?

Cognigy.AI virtual agent conversations can be customized to transfer a summary of the conversation transcript, conversation data and user profile information during agent handover process. This is typically handled by accessing and summarizing the Odata analytics records into a formatted transcript.

https://docs.cognigy.com/docs/odata-analytics-endpoint

What contact center solutions are supported by the product?

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Integration & Customization

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How easy is it to integrate your product with external systems?

Cognigy.AI is an all-inclusive platform package delivering a highly flexible and customizable enterprise ready solution. Built-in nodes allow external integrations to be created without code, with the option of adding custom features to the user interface. In addition, all Cognigy.AI functions are accessible externally via API to be activated or created by external systems.

https://docs.cognigy.com/docs/http-request

What types of integrations are possible for retrieving and storing information and executing processes?

Cognigy.AI fully supports back-end integrations with built-in https nodes allowing API calls to send or retrieve information within conversation flows. Similar native interactions are possible with SQL and mongo db with extended interactions possible by installing any of the open source extensions available on the Cognigy github repository.

https://github.com/Cognigy/Extensions/blob/master/RELEASES.md

Is it possible to customize the user interface by adding customer specific tooling?

The Cognigy.AI platform is extremely flexible due to an open-source extension framework. This is a key differentiator and allows for rapid development of fully-integrated bots with pre-packaged custom flow nodes that can be installed to each agent. Extensions customize flow nodes that are written in typescript and allow the appearance (image, colour and title) of the node to be customized in addition to the settings available in the editor menu and of the actual function that the node performs. An open-source library of existing extensions is available on the Cognigy github page.

https://docs.cognigy.com/docs/extensions

Do you provide any plug-in features to connect directly with existing back-end services?

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Analytics & Logging

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Does the product offer reporting features for monitoring performance and usage?

Cognigy.AI contains a built-in project analytics dashboard which displays key chatbot metrics to users within the platform. Conversation data is also available via the Cognigy Odata feed which can be used to import live conversation data to external visualisation tools such as Tableau and Power BI.

https://docs.cognigy.com/docs/analytics

How does the product allow users to investigate issues and are there support options provided?

Cognigy.AI provides full developer logging that monitors all comunications to or from the platform. Cognigy's online resources include the online product documentation and the community discussion thread where issues and projects can be discussed in an open forum. In addition, Cognigy technical support options are outlined in SLAs and customized for each client.

https://support.cognigy.com/hc/en-us/community/topics

Is it possible to disable analytics collection for specific channels?

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Security & Data Privacy

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Does the product include features for user management including control for access to virtual agent resources?

Cognigy.AI is enterprise ready with a built-in user management module supporting SSO providers such as Azure Active Directory and Google. The access control module allows role-based and granular user permissions to be created and granted for platform accounts.

https://docs.cognigy.com/docs/access-control

What data security capabilities does the product include?

Cognigy.AI complies to industry standards by offering a data security package including environment time-to-live settings, encrypted tokens and chat history storage control options on an infrastructure level.

Is it possible to manage multiple tenants of the application from a single user interface?

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Implementation & Support

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What training options do you offer for the product?

Alongside interactive user journeys found within the Cognigy.AI platform, four levels of training courses are provided by Cognigy that start with the fundamentals of conversational AI design and progress through to explore the more advanced features of the platform. Cognigy provides a free demo environment for new users to practice building their projects and the full product documentation is available publicly which explains to a technical level of detail how each feature is used.

https://docs.cognigy.com/docs/journeys

Does the product offer support for developent, quality assurance and production deployment pipelines?

Cognigy.AI offers the snapshots feature that allows complete virtual agent projects to be exported and imported to staged environments. In addition to snapshots, resources belonging to the agent NLU such as lexicon libraries and intent training records can also be exported and imported to staged environments.

https://docs.cognigy.com/docs/snapshots-1

What deployment options are supported by the product?

Cognigy offers SaaS, dedicating hosting and on-premises deployment options with support for Kubernetes as a container orchestrator. This allows the Cognigy.AI platform to be automatically or manually scaled to match the resource requirement of the customer.

https://www.cognigy.com/about

How does your company handle the roll out of platform software upgrades?

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