Conversational AI
RFI & RFP Template

Does Cognigy offer prebuilt/pretrained bots or virtual assistants?

Yes, Cognigy offers prebuilt/pretrained bots, known as AI Agents, which come with industry-specific skills.  They are designed to quickly deployed and integrated seamlessly with enterprise systems across various channels. Cognigy's professional services team is responsible for building and ongoing optimization.

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

How fast can an AI Agent be developed and deployed?

Depending on the complexity and use case, it could take anywhere from an hour to several weeks. Cognigy can build and deploy for you, typically within several weeks. Alternatively, you also have the option to build your own. 

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

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

The product interprets user messages through its integrated NLU engine which uses pre-trained language models trained on curated data in over 100 languages. The NLU also supports out-of-the-box prebuilt entity recognition for 28 languages. Output dialogs are managed by the chat- and voicebots built in the product, which support a wide variety of different channels including digital chat-channels, voice-channels, and smart assistants such as Amazon Alexa. Customers can also connect their custom messengers and platforms via generic REST, Webhook, and Socket.io endpoints.

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

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

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

Yes, Cognigy includes its own Natural Language Understanding (NLU) component. This NLU component is a crucial part of the conversational AI capabilities of the Cognigy.AI platform. It enables virtual agents to understand and interpret natural language input from users, which is essential for processing and responding to user queries effectively. The NLU component in Cognigy.AI is designed to handle various aspects of language understanding, including intent recognition and entity extraction, which are vital for creating responsive and interactive conversational experiences. Additionally, Cognigy.AI supports integration with third-party NLU engines through NLU Connectors, allowing users to connect with other NLU providers like Google Dialogflow and IBM Watson Assistant if needed.

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

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

"Yes, Cognigy.AI supports the use of external Natural Language Understanding (NLU) services. It includes out-of-the-box connectors for several leading NLU providers, such as Amazon Lex, Amazon Alexa Skills Kit, Microsoft LUIS, IBM Watson, and Google DialogFlow. When these connectors are used, Cognigy's own NLU engine is overridden, and the results from the connected NLU service are used instead, allowing for seamless integration and utilization of external NLU capabilities within Cognigy.AI flows.





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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 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?

Cognigy.AI supports a wide range of languages for Natural Language Understanding (NLU). It is pre-trained with data from over 100 languages to support intent recognition and key phrase detection. For 28 of the most common languages, Cognigy.AI provides prebuilt entities that allow automatic processing of inputs like dates, currencies, and others specific to a language that is defined in the flow.

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

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

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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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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/

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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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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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.

Please list relevant certifications for privacy, security etc.

ISO 27001, ISO 9001, SOC2 Type II, PCI-DSS, GDPR, CCPA, HIPAA, CSA STAR CAIQ, VDA TISAX, AIC4 BSI

https://trust.cognigy.com/

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

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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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