Just getting started? Complete the Using Conversation Assist tutorial.

It takes up to 3 hours for changes in Conversation Assist configuration to take effect.

Limitations

You can use any type of knowledge base in KnowledgeAI™ as a recommendation source in Conversation Assist. However, keep in mind the following limitations:

• "Rich content" answer recommendations aren't supported if the knowledge base is external (without LivePerson AI).
• LLM-enriched answers: A single rule can't contain a mix of knowledge bases that enrich answers via Generative AI and knowledge bases that don't do this. Don't set up a rule this way, not even if you put one type in one add-on and another type in another add-on within the same rule. Instead, set up different rules assigned to different skills to support your use case.

Prerequisite knowledge

To set up Conversation Assist to recommend answers, you must be able to use the KnowledgeAI application to create a knowledge base that contains a set of articles.

New to KnowledgeAI and knowledge bases? Check out the Meta Intents & Knowledge Bases tutorial.

High-level workflow

1. In KnowledgeAI, create the knowledge bases and the articles therein.
2. In Conversation Assist, create one or more knowledge base-level recommendation rules.
3. In Conversation Assist, configure relevant settings.

Step 1: Create the KB and articles

Access KnowledgeAI and create at least one knowledge base (KB) from your content source or from scratch. You can create and use any type of knowledge base, and the knowledge base can be public or private.

Also create at least one article therein, so you can verify that your setup is complete and working. You can continue to add more articles at any time after setup.

At this point, use KnowledgeAI to verify that the desired articles are active.

Step 2: Create KB-level recommendation rules

In this step, you create the rules that determine when answers from the knowledge base are offered as recommendations to agents.

Rules affect 1) recommendations offered in line in conversations and 2) recommendations offered in the On-Demand Recommendations widget.

1. Access Conversation Assist, and click Recommendation Sources.

   The Knowledge Bases tab is displayed by default.

2. Click Add rule.
3. Define the rule that determines when answers from the knowledge base(s) are recommended to agents. Each rule element is described farther below.
4. Click Save and activate.
5. Add additional rules as required.

Rule elements - general

• Name: Enter a short, meaningful, and unique name that highlights the rule’s basic function and purpose.
• Description: If desired, provide a more in-depth description of the rule: rationale, approach, i.e., anything that’s useful.

• Skills: Select the Conversational Cloud skills that you want this rule to apply to. You must specify at least one skill. A skill can be used in only one knowledge base rule.

  In conversations routed to these skills, articles in the knowledge bases listed in this rule will be offered as recommended answers. (A conversation is routed to the skills assigned to the campaign's engagement.)

Rule elements - add-ons

A rule add-on completes the rule’s definition. You must define at least one rule add-on because, at a minimum, that’s where you specify the knowledge bases to use in the rule.

If you define multiple add-ons, the order of the add-ons matters: At runtime, the add-ons are evaluated in order, and the first one that’s matched is executed. So, order the add-ons as required.

• Agent groups AND/OR profiles: You can further limit recommendations from the knowledge base to specific Conversational Cloud agent groups and/or profiles. Or, if the rule will be only skill-based, leave these blank.

• Retrieve {N} articles from EACH of {knowledge bases} with min. confidence {score}: Specify here the knowledge bases that are in play. Also specify the minimum confidence score that articles must have to be retrieved, and how many articles to retrieve from each knowledge base.

  Regarding “Retrieve N articles,” keep in mind that this isn’t the number of articles that will ultimately be offered to agents as recommended answers. The total maximum number of recommendations is determined by the Max # of recommendations setting on the Settings page, and it applies to both answers and bots…combined. “Retrieve N articles” only determines the number of matched articles to retrieve and add to the list that is evaluated by the system when determining which recommendations to offer.

  Regarding "EACH," only this option is supported.

  Regarding “min. confidence,” keep in mind that the higher the score, the more relevant the match. To increase the likelihood of a matched article, try a lower score.

• Enrich answers via Generative AI: Not ready to use Generative AI and LLMs? No problem. You can leave this setting off.

Enrich answers via Generative AI

If you want to offer your agents recommended answers that are enriched via Generative AI, turn on the Enrich answers via Generative AI setting.

• Enrichment prompt: Select a prompt from the Prompt Library. Learn about enrichment prompts.
• No Article Match prompt: Optionally, select a prompt from the Prompt Library. Learn about No Article Match prompts.

When you're in the Prompt Library selecting a prompt, you can also create, edit, and copy prompts on the fly.

The number of matched articles that are sent to the LLM (so that the LLM can use them to form a single generated response) is determined by how many articles you specify to retrieve from the knowledge base(s). The system will return one enriched answer per knowledge base.

Providing more knowledge coverage (not just a single article) to the LLM for an enriched answer often results an response that's superior.

Example rule

Our example rule below is for a fictitious, national automotive brand named Acme Auto. The rule is for a single skill named Support, which the brand assigns to all of its customer support agents.

Acme Auto agents are highly specialized, so the brand divides its agents into two Conversational Cloud agent groups:

• ICE Support for handling FAQs about cars with an internal combustion engine (ICE)
• EV Support for handling FAQs about electric vehicles (EV)

Thus, the rule includes two add-ons:

The first add-on is for offering answer recommendations from the ICE FAQs knowledge base to agents in the ICE Support agent group. The second add-on is for offering answer recommendations from the EV FAQs knowledge base to agents in the EV Support agent group.

So, for example, for an agent to receive answer recommendations from EV FAQs, the following must happen:

• The agent must pick up a conversation that is routed to the Support skill. (A conversation is routed to the skills assigned to the campaign's engagement.)
• The agent must be in the EV Support agent group.

As mentioned earlier, the order of the add-ons matters: At runtime, the add-ons are evaluated in order, and the first one that’s matched is executed. So, in our example here, if the agent were a member of both groups, the agent would never receive recommendations from the EV FAQs knowledge base because the first add-on (for the ICE Support agent group) always evaluates to true for the agent.

Learn more about how recommendations are made.

Step 3: Configure settings

1. Access Conversation Assist, and click Settings.
2. Configure relevant settings.