How GenAI works with an NLP bot

this section explains how genai capabilities work alongside the existing nlp based bot framework , how different settings influence query handling, and how to choose the right configuration based on your use case the platform provides two key genai settings ai agent (bot mandate) ai intent assist (orchestrator) these settings can be enabled independently or together to control how user queries are understood and answered navigate these settings under settings > solution settings , read more here https //app archbee com/docs/g4cetdedpalg9rne6ijrn/fwmnt 4dybxa6q1tpg92t#xqepa core concepts nlp bot (default behavior) by default, bots use nlp intent detection based on keywords training phrases this works well for structured, predictable conversations, but may struggle with long or ambiguous queries paraphrased questions multiple intents in a single message ai agent (bot mandate) the ai agent allows you to build genai powered conversational flows using the ai agent studio instead of relying on predefined intent matching, ai agent flows use natural language objectives and actions handle open ended and dynamic conversations can retrieve knowledge (exomind), call apis, or perform logic based actions when enabled, ai agent flows can generate responses directly using ai ai intent assist (orchestrator) ai intent assist improves how the bot understands user queries before deciding how to respond it introduces a query analyzer layer that understands the meaning of user queries attempts to map queries to the closest nlp intent using ai the ai tries to read the user queries, all the existing nlp intents in the bot with their descriptions about what that intent does, and tries to match with the closest relevant intent reduces missed or incorrect intent detection ai intent assist does not generate responses on its own; it only improves intent identification how queries are processed the behavior of the bot depends on which settings are enabled scenario 1 only nlp (default) workflow user sends a query nlp engine tries to match a predefined intent if matched → corresponding nlp flow is triggered if not matched → fallback or failure message is shown best for simple, structured bots fixed menus and predictable queries it can integrate complex apis scenario 2 advanced nlp ai intent assist on workflow user sends a query nlp engine attempts keyword based intent matching if no intent is found it passes to the ai intent assist, where ai analyzes the query attempts to identify the closest matching nlp intent (based on intent name and description) if intent is identified → matched nlp flow is triggered if still not identified → failure or fallback message important notes ai is used only for intent detection , not response generation ai agent flows are not used best for businesses that want better intent accuracy customers who do not want ai generated responses improving nlp performance without changing bot behavior scenario 3 only gen ai bot ai agent on workflow user sends a query query is routed directly to ai agent flows ai agent determines how to respond using objectives and actions response is generated by ai no nlp intents are used important notes a default ai agent flow will be created, and the user will have to update the prompts for the supervisor & sub goal nodes nlp intent detection is not used the bot relies entirely on the ai agent logic nlp flows are preserved but inactive best for fully genai based bots bots designed for free flow conversations scenario 4 hybrid bot ai intent assist & ai agent on this is the most complete and flexible setup workflow user sends a query nlp intent detection is attempted if no match ai intent assist analyzes the query attempts to map it to the closest nlp intent if an nlp intent is identified → nlp flow is triggered if no intent is identified query is routed to the ai agent flows ai agent generates the response and completes the flow if the ai agent cannot handle and generate a response → fallback message is shown key benefits preserves structured nlp flows uses ai only when needed provides a safe fallback mechanism reduces hallucinations and incorrect answers best for production bots gradual genai adoption combining structured flows with genai flexibility new gen bots current limitations the platform currently supports nlp first with ai agent fallback ai agent–first with nlp fallback is not supported reason nlp flows support richer ui components (ctas, media, forms) ai agent flows are still evolving toward feature parity once ai agent flows support all nlp components, additional routing configurations will be introduced in a future release choosing the right configuration use the table below to decide which settings to enable use case recommended settings only nlp bot use only nlp workflows (no gen ai features) default option ai agents (bot mandate) = off ai intent assist (orchestrator) = off advanced nlp improve the intent accuracy of the nlp bot, without ai responses ai agents (bot mandate) = off ai intent assist (orchestrator) = on only genai bot build a gen ai based bot without any nlp workflows ai agents (bot mandate) = on ai intent assist (orchestrator) = off hybrid bot nlp workflows followed by ai agents ai agents (bot mandate) = on ai intent assist (orchestrator) = on best practices start with ai intent assist to improve nlp reliability add an ai agent gradually for fallback and complex queries use ai agent for faqs knowledge based queries open ended questions keep transactional and ui heavy flows in nlp until the ai agent supports full parity