Context Search

Current conclusion

Context Search was originally an AI search tool designed for long videos and knowledge-based content; it allowed users to find keywords and specific segments within YouTube channels or playlists. Later, it evolved into the Context platform, which enables the creation of question-answering robots using various types of data.

As of August 22, 2026, the homepage of the original product can no longer be used as an entry point to the tool; the website details stored in the current directory point to an old restaurant website that has nothing to do with the AI tool. The older versions of the documents are still accessible, but this does not mean that registration, payment, and service generation functions are still operating properly.

A one-sentence summary

Context Search is an AI-based video search and knowledge robot product that is no longer available for use by the public; it used to allow searches of channels, playlists, documents, and code materials, but it should no longer be recommended as an online tool that can be purchased through registration.

Relationship between product development and naming

In its early stages, Context Search was also known as AddContext; its main advantage was that it enabled podcasts, videos, and creator channels to be searched and queried. The contact email addresses available in public materials, along with subsequent Context documents, indicate that these names referred to the same product at different stages of its development.

Subsequently, the Context platform expanded its capabilities to include document websites, blogs, YouTube videos, and GitHub repositories; it also allowed robots to be installed on websites, Discord, or Slack. The company behind it, Use Context, Inc., shifted its focus to other AI infrastructure services, and the original Context website is now inactive with no pages available.

Main functions of history

Channel and playlist search

Early versions of Context Search were able to handle entire YouTube channels or playlists, allowing users to search for a specific keyword or phrase without having to open each individual video one by one. The results provided access to relevant videos and content segments, making them useful for finding materials such as research interviews, courses, and podcasts.

Transcription of video and podcast content

The product converts the speech in audio and video files into searchable text, and then returns the relevant content based on searches. The accuracy of transcription is affected by factors such as accent, background noise, multiple people talking at once, the availability of subtitles, and technical terminology.

Ask and answer questions based on the content.

Users can ask questions about the imported videos, podcasts, or informational materials, and the robot will generate answers by drawing on the existing content. This approach is useful for identifying viewpoints and reviewing material, but verifying the generated answers still requires referring back to the original clips.

Multi-channel knowledge base

The subsequent Context documents list various sources such as document websites, blogs, YouTube videos, and GitHub repositories. Users can gather different types of information in a robot and update its knowledge base through synchronization.

Website chatbot

Context allows for the creation of bots that can be installed on websites; users can choose between a launcher button, a floating launcher, or a popup for the bot. Administrators can adjust the settings, models, and presentation style of these bots.

Integration with Discord and Slack

The old documents provide instructions for installing Discord and Slack, enabling team members to access relevant knowledge materials within collaborative spaces. Actual use requires authorization from external platforms as well as permissions for bots.

Query monitoring and feedback

Administrators can view user queries and provide feedback on whether the responses are helpful. This feedback helps identify missing information and low-quality responses, but it cannot replace the maintenance of the knowledge base or human support.

Team collaboration

The document lists the functions for inviting team members, making settings, managing usage, and handling channels. Different members should be granted permissions for robot editing, channel synchronization, and deployment based on their responsibilities.

Historical working principle

1. The user first selects the video channel, playlist, or other informational material that they wish to search for.
2. The system retrieves accessible content, transcribes audio and video as well as speech, and organizes web pages and code materials into documents.
3. The data is split and indexed so that relevant segments can be found using keywords or semantics.
4. The user enters a keyword or a question in natural language, and the system searches for content related to that question.
5. The robot generates responses based on the retrieved fragments, or it simply displays the matching content for the user to view.
6. Administrators identify knowledge gaps by reviewing records and feedback, and then update the settings of the channels or robots.

How to determine whether the service has been restored

1. First, ensure that the page clearly displays the name of Context Search or the Context knowledge robot, and not that of a restaurant, gambling service, or any other product with a similar name.
2. Check whether there are functional options for registration, login, and creating robots.
3. Ensure that the help documentation, price page, and terms of service have recent update dates.
4. Create a robot that contains only publicly available test data, in order to verify whether the synchronization of channels and the functioning of Q&A systems are proper.
5. Confirm that the installation process on the website, Discord, or Slack can be completed, and check the required permissions.
6. Before making the payment, check the current operating entity, the cost of the package, the refund policies, and the data processing guidelines.

Historical usage tutorials

Search for a long list of videos

1. Prepare the public channel or playlist, and ensure that the video is accessible and contains usable audio tracks or subtitles.
2. Add the channel or playlist to Context Search, and wait for the system to complete indexing.
3. Enter specific keywords for people, concepts, products, or ideas; avoid using only broad topics.
4. Open the matching videos and clips, and examine the speaker’s original intention by considering the context before and after.
5. Record the confirmed segments in the research notes, and keep the video titles and time stamps.

Create a knowledge robot

1. Create a robot and set its name, purpose, response boundaries, and target users.
2. Add authorized sources such as document websites, blogs, videos, or code repositories.
3. Wait for the synchronization to complete, and test the quality of the retrieval using questions with known answers.
4. Adjust the data scope, robot models, and response rules, and remove outdated or conflicting channels.
5. Choose the installation method via website, Discord, or Slack, and carry out the deployment with the minimum required permissions.
6. Review user queries and feedback, continuously add missing information, and address questions that cannot be answered.

Which users are it suitable for

The user types described below refer to the historical positioning of the older version of the product; they do not indicate that it is still possible to register for use. Users looking for similar functionalities should opt for alternative tools that still have a functional official website, up-to-date documentation, and clear privacy policies.

• Video content creators: Quickly locate older content and reusable clips from their own channels and playlists.
• Podcast production team: Search for topics that the guests have discussed in order to prepare background information for the interviews.
• Students and researchers: Find concepts and their original expressions in courses, lectures, and collections of interviews.
• Documentation Team: Organize product documentation and blogs into question-answering knowledge robots.
• Customer support team: Deploy a chatbot for common questions on the website or collaboration platform.
• Developer: Use the older JavaScript toolkit to query robots and retrieve semantic search snippets.

Typical use cases

• Find the exact location in dozens of episodes where a particular podcast guest discussed a certain topic.
• Locate definitions, examples, and key points for review from the course playlist.
• Create a website Q&A bot based on the product documentation to reduce repetitive support inquiries.
• Connect the code repository and documentation to the team bot for beginner-friendly Q&A for developers.
• Check the community rules, tutorials, and common issues in Discord or Slack.
• Based on the monitoring queries, document gaps are identified, and manual updates to the knowledge materials are arranged.

Advantages of historical products

• Convert long videos and podcasts into searchable materials to reduce the time spent scrolling through the timeline section by section.
• It supports entire channels or playlists, rather than just individual videos.
• Future versions will be able to incorporate various types of content such as documents, blogs, videos, and code repositories.
• Robots can be used on websites, and installation methods for Discord and Slack are also available.
• Querying monitoring data and collecting feedback on usefulness helps identify areas where the knowledge base lacks coverage.
• The older version of the development toolkit allowed applications to query robots and perform semantic searches.

Current restrictions and risks

• The original product entry point is no longer functional; it is not possible to determine whether new users can still register, create robots, or purchase packages.
• The links stored in the current directory are not related to AI products; users should not enter their account or payment details on this page.
• The old main server returns a page-less status; only the documents are still accessible. The fact that the documents are online does not mean that the backend service is functioning properly.
• The old SDK has not had any verifiable new versions for many years, which may lead to issues such as expired dependencies and ineffective interfaces.
• Old price documents only list quotas without an identifiable current amount, and therefore cannot be used for procurement budgets.
• Audio and video transcription as well as AI-generated responses may miss the context; important quotations must be verified by referring to the original video.
• Importing private videos, code repositories, or internal documents involves issues related to permissions and privacy; the old data policy cannot be fully verified at present.
• There are numerous products with similar names in the areas of Context, Context Search, and Context AI; it is necessary to verify the company, domain name, and purpose of the product.

Price and package status

As of August 22, 2026, there is no verifiable current purchase page for Context Search. The older official documents still list the package names and quotas, but do not show the monetary amounts; the information below is provided only for identifying previous versions and does not indicate that these packages are still available for subscription.

Third-party directories once listed different prices and video duration figures, but they lack the verification provided by the current official pricing page; therefore, they should not be considered as the official prices in use today. When such services are needed, it is necessary to compare them again based on the current prices offered by new suppliers.

Platform status support

APIs, SDKs, and open-source status

Capabilities of the old API version

The old documentation states that the Context functionality is available for developers to use; the initial version covers robot queries, stream-based response delivery, query feedback, and semantic search. It is not a complete interface that includes all functions related to channel creation, synchronization, and management.

JavaScript toolkit

The older version provides TypeScript and JavaScript toolkits, with the package name @context-labs/sdk. The information available for this public package indicates that it was last released many years ago; therefore, before using it it is necessary to verify that the installation, endpoints, and authentication mechanisms still function properly.

GitHub and business direction shifts

The old documents are linked to the Context-Labs organization, which is now operating under the brand inference.net and maintains various independent open-source projects. The fact that this organization remains active does not mean that the old Context Search platform is still in use.

Open-source status of the product

There is no evidence indicating that the Context Search or Context Knowledge Robot platforms are fully open source. Document repositories, toolkits, or other open source projects within the same organization do not constitute proof that the source code of the commercial platforms can be deployed on one’s own.

Privacy and data security

At present, it is not possible to obtain information from the official product homepage regarding Context Search’s latest privacy policies, data retention practices, as well as the procedures for model training and deletion. The lack of such information represents a significant risk that makes it inappropriate to proceed with deployment when dealing with internal documents, private videos, or code.

• Do not enter account details, payment information, or API keys on pages that are invalid or have mismatched domain names.
• Do not continue to synchronize internal documents with the old robot, unless the operating entity and the data protocols have been reconfirmed.
• Before migration, export the list of public materials, robot settings, common questions, and records of human feedback.
• Revoke permissions for the old website, Discord, Slack, YouTube, and the code repository.
• When choosing alternative tools, check data retention, training termination procedures, deletion processes, and third-party model providers.
• Data containing personal information or trade secrets should first be minimized, anonymized, and have restricted access rights.

Steps to migrate to an alternative tool

1. List the channels, playlists, document sites, blogs, and code repositories used by the original robot.
2. Verify the authorization, owner, update time, and sensitivity level of each piece of data.
3. Choose a knowledge base or video search tool that still has a valid official website, is regularly updated, and offers clear pricing and data policies.
4. Use a small amount of publicly available information to verify transcription, semantic search, citation location, and the performance in Chinese.
5. Reestablish robot rules, manual routing, website embedding, and collaboration platform permissions.
6. After the migration is complete, revoke the old integration, delete the copies that are no longer needed, and document the results of the process.

Basic information

Recommendation score

The current recommendation score is 1.5 points. The approach behind Context Search holds practical value, especially for searching across playlists, answering content-related questions, and using multi-channel robots; however, the product’s interface, pricing, privacy policy, and service availability have not yet been fully verified.

Users who have already saved the old links should consider them as historical entries and prioritize switching to the products that are still being maintained. If there is an official announcement regarding their restoration in the future, it will be necessary to recheck the operating entity, domain name, documentation, and payment page before adjusting the evaluations.

Frequently Asked Questions

Is Context Search still available?

It is not possible at the moment to determine whether the original service is still functional. The homepage of the original product is no longer accessible, and the links in the current directory have nothing to do with AI tools; only the old version of the documents can still be viewed.

Why isn’t the current link an AI tool?

The existing links in the database point to an old version of a restaurant’s website, and they have no connection to the products offered by Context Search. Users should not use that page as an entry point for logging in, downloading, or making purchases.

What could Context Search do originally?

It was initially used to search for YouTube channels, playlists, and long-form video content; later, the Context platform enabled the creation of question-answering robots based on documents, blogs, videos, and code repositories.

Is Context Search free?

Old documents listed a free plan that included 50 query requests, 100 documents, and 2 synchronization operations; however, it is not possible to determine at present whether it is still possible to sign up for this plan. The old quotas cannot be considered as part of the current free offerings.

How much was the old paid plan?

The old official documents only listed the package names and quotas, without any indication of the current monetary amounts. Historical prices from third parties should not be used as the current official pricing.

Does it provide APIs?

Historically, limited interfaces were provided, primarily for robot queries, stream-based responses, feedback, and semantic search. It is necessary to verify again whether the endpoints and account access are still valid.

Does it have an official SDK?

Historically, it has provided TypeScript and JavaScript toolkits, but no verifiable new versions of these packages have been released in many years. New projects should not rely on it without first testing it.

Is Context Search open source?

The product itself does not have its complete source code made public. The available documentation, toolkits, and other projects within the context-labs organization do not constitute proof that the old platform is open-source.

Is it the same as the current Context Enterprise Agent platform?

It cannot be determined in this way. There are multiple Context products with the same name available on the market; the companies behind the current enterprise agent platforms, as well as their domain names and product focuses, vary, so they need to be studied as separate tools.

What should existing users do?

It is necessary to export the retrievable data and configurations, revoke the authorization for the old channels, and migrate to an alternative platform that still has valid operational information. When internal data is involved, it is also required to confirm with the original operator that the data has been deleted.

Summary

Context Search used to convert long videos, podcasts, and informational materials into content that could be searched and queried, and it further developed knowledge robots for use on websites and collaboration platforms. Its historical functions offer valuable insights for content research and the automation of support tasks.

However, the most important information regarding this entry is not the old features; rather, it is the fact that the original entry point is no longer functional, the directory links are incorrect, and the current prices as well as the privacy policy cannot be verified. At this stage, it should be marked as a historical tool that should no longer be recommended, instead of continuing to guide users to register or pay for it.