Add Zoom as a knowledge accessor to your Amazon Q index

For a lot of organizations, huge quantities of enterprise data are scattered throughout various knowledge sources and functions. Organizations throughout industries search to make use of this cross-application enterprise knowledge from inside their most well-liked techniques whereas adhering to their established safety and governance requirements.

This submit demonstrates how Zoom customers can entry their Amazon Q Enterprise enterprise knowledge immediately inside their Zoom interface, assuaging the necessity to swap between functions whereas sustaining enterprise safety boundaries. Organizations can now configure Zoom as a knowledge accessor in Amazon Q Enterprise, enabling seamless integration between their Amazon Q index and Zoom AI Companion. This integration permits customers to entry their enterprise data in a managed method immediately inside the Zoom platform.

How Amazon Q Enterprise and Zoom AI Companion work collectively

The Amazon Q Enterprise knowledge accessor is a core element inside Amazon Q Enterprise. It manages and controls entry to knowledge saved in an enterprise’s inner data repositories on Amazon Q Enterprise from an exterior impartial software program vendor (ISV) similar to Zoom whereas sustaining safety and knowledge entry compliance. This characteristic permits Zoom to retrieve related content material, enhancing the Zoom AI Companion’s data. It serves as an middleman that enforces entry management lists (ACLs), defining each knowledge supply permissions and person entry rights to the present Amazon Q Enterprise index.

Zoom AI Companion, the inspiration of Zoom’s AI-first work platform, enhances human connection by working behind the scenes to spice up productiveness, enhance work high quality, and strengthen relationships. This April, Zoom launched the Customized AI Companion add-on, enabling organizations to customise AI brokers and expertise to assist meet their particular wants and drive company-wide effectivity. By way of its partnership with Amazon Q Enterprise, clients can now join their listed knowledge in Amazon Q index to Zoom AI Companion, offering enhanced data and contextual insights.

As an Amazon Q Enterprise knowledge accessor, Zoom AI Companion can work together with the enterprise Amazon Q index in a managed approach, enriching content material past what’s out there in Zoom alone. Enterprise customers can retrieve contextual data from their Amazon Q index’s a number of linked knowledge sources immediately inside Zoom, with outcomes seamlessly introduced by means of Zoom AI Companion. Zoom AI Companion can entry Amazon Q index knowledge with its native knowledge sources, similar to earlier name transcripts, to rapidly floor related data to customers. This integration alleviates the necessity to manually swap between varied enterprise techniques like Google Drive, Confluence, Salesforce, and extra, saving time and lowering workflow disruptions.

For instance, whereas making ready for a Zoom name, customers can rapidly discover solutions to questions like “When is buyer AnyCustomer’s contract up for renewal, and who signed the final one?” The Amazon Q index processes these queries and delivers outcomes by means of Zoom AI Companion in actual time.

Answer overview

The next diagram is a high-level structure that explains how enterprises can arrange and entry Amazon Q Enterprise listed knowledge from inside the Zoom AI Companion utility.

Within the following sections, we display the best way to configure Zoom as a knowledge accessor and get began utilizing Zoom AI Companion.

Stipulations

To implement this answer, you want an AWS account with applicable permissions.

Create an Amazon Q Enterprise utility

To entry listed knowledge from Amazon Q Enterprise by means of Zoom AI Companion, organizations should first arrange their Amazon Q Enterprise utility. The applying have to be configured with AWS IAM Id Middle to allow the Zoom knowledge accessor performance. For detailed steering on creating an Amazon Q Enterprise utility, discuss with Configure application.

Configure entry management with IAM Id Middle

By way of IAM Id Middle, Amazon Q Enterprise makes use of trusted identification propagation to supply correct authentication and fine-grained authorization based mostly on person ID and group-based sources, ensuring entry to delicate knowledge is tightly managed and doc ACLs are enforced. The ISV is barely permitted to entry this index utilizing the assigned knowledge accessor.

When you’re utilizing an identification supplier (IdP) similar to Okta, CyberArk, or others, you may add the IdP to IAM Id Middle as a trusted token issuer. For added data, see Configure Amazon Q Enterprise with AWS IAM Id Middle trusted identification propagation.

For extra data on IAM Id Middle, discuss with IAM Id Middle identification supply tutorials.

Add Zoom as a knowledge accessor

After creating an Amazon Q Enterprise utility with IAM Id Middle, directors can configure Zoom as a knowledge accessor by means of the Amazon Q Enterprise console. Full the next steps:

1.  On the Amazon Q Enterprise console, select Knowledge accessors within the navigation pane.
   
2. Select Add knowledge accessor.
   
3. Select Zoom as your knowledge accessor.
4. For Accessor title, enter a reputation in your knowledge accessor.
5. For Knowledge supply entry, configure your stage of entry.

You’ll be able to choose particular knowledge sources to be out there by means of the information accessor. This lets you management which content material is surfaced within the ISV setting. You should use Amazon Q Enterprise pre-built connectors to synchronize content material from varied techniques. For extra data, discuss with Supported connectors.

6. For Consumer entry, specify which customers can entry the Amazon Q index by means of the information accessor.

This feature lets you configure granular permissions for knowledge accessor accessibility and handle organizational entry controls.

For extra details about knowledge entry, discuss with Accessing a buyer’s Amazon Q index as a knowledge accessor utilizing cross-account entry.

Directors can modify knowledge accessor settings at any time after implementation. You’ll be able to regulate person entry permissions, replace out there knowledge sources, and alter the scope of accessibility. To revoke entry, full the next steps:

7. On the Amazon Q Enterprise console, select Knowledge accessors within the navigation pane.
8. Find the accessor you wish to delete and select Delete.
9. Affirm the deletion when prompted.

Eradicating a knowledge accessor from a knowledge supply instantly cancels the ISV’s entry to your group’s Amazon Q index.

Configure Amazon Q for Zoom AI Companion

To start out utilizing Zoom as a knowledge accessor in your Amazon Q Enterprise index, the next data out of your enterprise Amazon Q Enterprise utility have to be shared with Zoom:

• Amazon Q Enterprise utility ID
• Amazon Q Enterprise AWS Area
• Amazon Q Enterprise retriever ID
• Knowledge accessor utility Amazon Useful resource Title (ARN)
• IAM Id Middle occasion Area

For extra data, discuss with Accessing a buyer’s Amazon Q index as a knowledge accessor utilizing cross-account entry.

After you add Zoom as a knowledge accessor, a pop-up window will seem on the Amazon Q Enterprise console. This pop-up accommodates the required parameters, as proven within the following screenshot.

Navigate to the Zoom App Market to configure Amazon Q in Zoom, and enter the data you collected.

After you submit this data, you’re able to entry Amazon Q index knowledge from Zoom AI Companion.

With AI Companion linked to Amazon Q index, you might have the data you want immediately. For instance, you may make AI Companion conscious of your group’s IT troubleshooting guides so workers may rapidly get assist with questions like “How do I repair a damaged keyboard?”

Utilizing the SearchRelevantContent API

When an enterprise buyer with an Amazon Q index allows a knowledge accessor, it permits authenticated Amazon Q Enterprise customers to go looking and retrieve related content material in actual time whereas utilizing exterior ISV platforms (like Zoom). This performance is achieved by means of the ISV calling the Amazon Q index SearchRelevantContent API as an exterior knowledge accessor throughout accounts. The SearchRelevantContent API is particularly designed to return search outcomes from the Amazon Q index, which might be additional enhanced by the ISV’s generative AI stack. Through the use of the Amazon Q index SearchRelevantContent API, Zoom and different ISVs can combine question outcomes immediately into their setting.

The SearchRelevantContent API is an identity-aware API, which suggests it operates with data of the person’s identification and related data (similar to e-mail and group membership) by means of the credentials used to name the API. This identification consciousness is a prerequisite for utilizing the API. When querying the index, it reconciles doc entry controls in opposition to the authenticated person’s permissions. In consequence, customers can solely retrieve outcomes from content material they’re approved to entry.

When an ISV calls the SearchRelevantContent API as a knowledge accessor, each sparse and dense searches are utilized to the Amazon Q index, combining key phrase search and vector embedding proximity. Outcomes are ranked earlier than being returned to the ISV interface.

For instance, when you ask in Zoom, “What’s Firm XYZ’s engagement on the most cancers moonshot challenge?”, Zoom AI Companion triggers a name to the SearchRelevantContent API as a knowledge accessor.

For a extra complete code instance, see the pocket book in Module 2 – Amazon Q cross-app index.

The next is a code snippet in Python exhibiting what that search request would possibly seem like:

search_params = {  'applicationId': Q_BIZ_APP_ID, 
    'contentSource': {
        'retriever': { 
            'retrieverId': Q_RETRIEVER_ID 
            }
    }, 
    'queryText': 'What's Firm XYZ engagement on the most cancers moonshot challenge?', 
    'maxResults': 10
}

search_response = qbiz.search_relevant_content(**search_params)

The search response will comprise an array of outcomes with related chunks of textual content, together with supply data, doc attributes, and confidence scores. The next is a snippet from the SearchRelevantContent API response. That is an instance of outcomes you would possibly see from the online crawler knowledge connector used with Amazon Q Enterprise.

[
    {
        "content": "nSeveral initiatives have been launched or will soon launch to address the goals of this next phase, including:nIncluding more people in expanded and modernized cancer clinical trialsnIncreasing the pipeline of new cancer drugsnEnsuring access to current and new standards of cancer carenEnhancing diversity in the cancer research workforce",
        "documentId": "Cancermoonshot",
        "documentTitle": "About The Cancer Moonshot",
        "documentUri": "https://companyxyz/cancermoonshot.html",
        "documentAttributes": [
            {
                "name": "_source_uri",
                "value": {
                    "stringValue": "https://companyxyz.com/cancermoonshot.html"
                }
            }
        ],
        "scoreAttributes": {
            "scoreConfidence": "VERY_HIGH"
        }
    },...]

The SearchRelevantContent API has a wealthy set of optionally available parameters out there that ISVs can select to make use of. For instance, doc attributes can be utilized as filters. If paperwork with meta attributes have been listed, and considered one of these attributes accommodates the writer, it could be doable for an ISV to use a filter the place you may specify an writer title. Within the following instance, outcomes returned are constrained to solely paperwork which have the desired attribute writer title “John Smith.”

search_params = {
    'applicationId': Q_BIZ_APP_ID,
    'contentSource': {
        'retriever': {
            'retrieverId': Q_RETRIEVER_ID
            }
    },
    'queryText': myQuestion,
    'maxResults': 5,
    'attributeFilter': {
        'equalsTo': {
            'title': 'Creator',
            'worth': {
                'stringValue': 'John Smith'
            }
        }
    }
}

For a extra complete reference on what is obtainable within the SearchRelevantContent API request object, discuss with search_relevant_content.

Clear up

Whenever you’re carried out utilizing this answer, clear up the sources you created.

1. Delete the Zoom knowledge accessor from the Knowledge accessors console. Deleting this knowledge accessor will delete permissions and entry to the information accessor for all customers.
2. Delete the Amazon Q Enterprise utility that you just created as a prerequisite.
   • Navigate to the Amazon Q Enterprise console.
   • Select Purposes on the left menu.
   • Choose the applying you created.
   • Select Delete from below Actions to delete the applying.

Deleting the Amazon Q Enterprise utility will take away the related index and knowledge supply connectors, and stop incurring further prices.

Conclusion

Amazon Q indexes affords a transformative method to office effectivity. By making a centralized, safe repository in your group’s knowledge, you may seamlessly combine very important data together with your on a regular basis productiveness instruments like Zoom AI Companion.

On this submit, we explored how Amazon Q Enterprise enterprise customers can add knowledge accessors to combine with exterior events like Zoom AI Companion, permitting customers to entry their enterprise data in a managed approach immediately from inside these platforms.

Able to supercharge your workforce’s productiveness? Begin your Amazon Q Business trip as we speak alongside Zoom. To be taught extra about Amazon Q Enterprise knowledge accessors, see Improve enterprise productiveness in your LLM answer by turning into an Amazon Q Enterprise knowledge accessor.

In regards to the authors

David Girling is a Senior AI/ML Options Architect with over 20 years of expertise in designing, main, and growing enterprise techniques. David is a part of a specialist workforce that focuses on serving to clients be taught, innovate, and make the most of these extremely succesful companies with their knowledge for his or her use instances.

Chinmayee Rane is a Generative AI Specialist Options Architect at AWS, with a core give attention to generative AI. She helps Unbiased Software program Distributors (ISVs) speed up the adoption of generative AI by designing scalable and impactful options. With a robust background in utilized arithmetic and machine studying, she focuses on clever doc processing and AI-driven innovation. Exterior of labor, she enjoys salsa and bachata dancing.

Sonali Sahu is main the Generative AI Specialist Options Structure workforce in AWS. She is an writer, thought chief, and passionate technologist. Her core space of focus is AI and ML, and she or he continuously speaks at AI and ML conferences and meetups all over the world. She has each breadth and depth of expertise in expertise and the expertise business, with business experience in healthcare, the monetary sector, and insurance coverage.