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KNO
☆☆☆☆☆
ChatGPT (293)

KNO Verified Tool

Aided product users via conversational support.

Monthly visits: 8,915

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Starting price Free

Tool Information

Overview of KNO

KNO is an AI chat tool designed to enhance user interactions within software products. It serves as a conversational assistant, guiding users through their product journeys and providing immediate answers to their questions. This tool is particularly beneficial for organizations looking to improve user experience and streamline support processes.

Core Features

KNO integrates seamlessly with platforms like Slack, allowing users to access its capabilities directly within their existing workflows. It offers a low-code help widget that can be embedded in applications, enabling users to receive assistance without leaving the product interface. Additionally, KNO includes an in-product guide and a documentation search feature, making it easier for users to find relevant information quickly.

Training and Customization

The tool is built on OpenAI's GPT-3 model, which has been trained on a vast dataset of 800GB of information. This extensive training allows KNO to provide accurate and contextually relevant responses. Users have the option to prioritize knowledge from specific sources, tailoring the assistant's responses to better fit their organizational needs. Furthermore, KNO can be trained on specific topics, enhancing its relevance and effectiveness in addressing user queries.

User Privacy and Data Security

KNO emphasizes user privacy by securely storing the questions asked by users. This feature ensures that sensitive information remains protected while still allowing the tool to learn and improve over time. Organizations can confidently implement KNO, knowing that user data is handled with care.

Accessibility and Pricing

KNO is accessible via the web and is offered free of charge, making it an attractive option for businesses of all sizes. Its straightforward installation process for Slack, which can be completed in three steps, further enhances its accessibility for users looking to implement a conversational assistant quickly.

F.A.Q (20)

KNO is an AI-driven platform created by Alltius for conversational assistance in software products. Its main features include a Slack assistant for any question, a low code help widget, an in-product guide and companion, and an enterprise documentation search. It is built on OpenAI's GPT3 model which includes 800GB of information. The platform also includes a feature where users can prioritize knowledge from specific sources. KNO securely stores the questions asked, maintaining user privacy.

KNO helps in guiding users in their product journeys by engaging them in conversation and responding to their inquiries. This is facilitated by its integration into Slack, where users can easily ask questions and receive answers. Furthermore, KNO's in-product guide and companion features aid users by providing assistance within the product itself. It has a low code help widget which simplifies the help process even further.

KNO is integrated with Slack as a conversational assistant. Users can interact with KNO directly in their Slack workspace, either in private conversation or by adding it to a channel. The Slack assistant feature of KNO is designed to answer any questions users may have.

To install KNO on Slack, users first need to log into their Slack workspace. Next, they need to open the 'Browse Apps' screen by clicking on the small '+' symbol next to the Apps tab on the Slack sidebar. In the final step, users search for and select KNO to get started.

Yes, users can prioritize KNO knowledge from specific sources. This feature allows KNO to prioritize information from custom prescribed sources, potentially including the user's own help resources. This makes it customizable and able to adapt to the unique needs of its users.

KNO ensures data security and maintains privacy by keeping all questions asked within the system and never associating them with the user's identity. This ensures that conversations remain private and confidential.

Using the KNO platform comes at absolutely no cost to users. The website confirms that KNO is free to use.

KNO's user base has been experiencing a growth rate of 50% month on month. This robust growth rate is a testament to its popularity and usefulness.

One customer from a leading analytics automation company has compared KNO favorably to Google and Gong, stating KNO has the potential to become the next Gong and is even better than Google. Therefore, according to this specific testimonial, KNO compares very positively to both of these platforms.

Yes, KNO can be trained on specific topics. Currently this feature is being developed, and users can reach out to the team for further discussions on this.

The KNO platform was developed by a team of engineers, data scientists, and designers from Alltius.

KNO is trained on OpenAI's GPT3 model which includes 800GB of information, with the option for users to prioritize knowledge from specific, custom sources. The GPT3 model represents a broad swath of information, giving KNO extensive knowledge capabilities.

KNO handles customer support queries by providing direct responses to questions asked by users. If a conversation does not end conclusively, users are redirected to key personnel who can provide further assistance.

KNO ensures data security by ensuring that user queries remain within the algorithm and are never associated with user identity. This mechanism maintains the confidentiality of a user's interaction with KNO.

The user retention rate for KNO is at an impressive 86%. This means that more than 86% of returning users ask at least one query, indicating a high level of engagement and continued usability.

Feedback from pilot customers show positive reviews for KNO. The tool has been praised for its potential to become a major platform like Gong, its superiority over Google, and as a welcomed addition to a diverse set of tech environments.

Users can easily test KNO by adding it to their Slack workspace. The link to add KNO to Slack is provided on the Alltius website. Users can then engage in private conversations with KNO or add it to a Slack channel to begin testing.

Apart from KNO, Alltius offers products like KNO Help, KNO Concierge, and KNO Insider. These tools represent different aspects of the software product journey, ranging from general help to specific in-product guidance and documentation search.

KNO would be useful across a range of sectors like SaaS, Ed-Tech, and HR-Tech. Companies with products involving a steep learning curve, businesses that require automated applicant search and vetting, or entities that could benefit from AI-driven tutor augmentation for queries would find KNO particularly beneficial.

A product can be enhanced using KNO by integrating it to provide conversational assistance. This offers users a quick and precise way to get answers to their queries, helping them better understand and utilize the product. This can lead to improved user experiences, which in turn can drive engagement and business growth.

Pros and Cons

Pros

  • Slack integration
  • Low code widget
  • In-product guide
  • Enterprise documentation search
  • Trainable on specific topics
  • Securely stores questions
  • Prioritizes knowledge from sources
  • Free to use
  • Three-step Slack installation
  • High returning users ratio
  • Positive customer feedback
  • Quick query resolution
  • Can redirect users to support
  • Growth on user base
  • Workable on various sectors
  • Customizable for product use case
  • Built by experienced team
  • Inclusion in multiple Slack channels
  • Privacy focused
  • User-guide available
  • FAQs for immediate help
  • Ability to surprise users
  • High NPS

Cons

  • Limited to Slack integration
  • Requires user-driven knowledge prioritization
  • No customizable user interface
  • No multi-language support
  • No direct API access
  • No live user support
  • Cannot handle complex queries
  • Lacks specific domain training

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Overview

Tool Type AI Chat Tool

Applicable Tasks

chat chatbot slack gpt Q&A
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