6/19/2023 0 Comments Chatbot platform![]() In reality, very few AIs are truly conversational. That means, if you haven't accounted for an option to be entered at the current stage, the AI engine will ignore it, or worse, fail. Here is what a conversational AI would respond:īut here is what a scripted AI would say:Ī conversational AI can – more or less flexibly – infer important characteristics, like the size and toppings the customer selected.Ī scripted AI, however, sticks to strict conversational flows. Localization: can the AI engine be trained in languages other than English? And can it be trained in multiple languages simultaneously? Depending on that, you might have to create a new chatbot for each use case ✕ language. Re-training: are failed user requests collected in a report? And can this data be used to improve the NLP engine, for example by adding them to the AI model? (See 6.) If your organization is concerned with keeping things, that employees ask, from leaving the company network, then this will be an important criteria for your choice.Įditor's tip: If privacy is a top concern for your organization you should consider Botpress (NLP happens on-site) and for secure voice input a Google Pixel 4 ( transcription doesn't rely on an Internet connection)Īpart from security, NLP systems within a bot platform can also have strengths and weaknesses of their own which you should weigh up with what you need:Īccuracy: how good is the platform you're evaluating and how much training data does it require before results are reasonably well distinguished? If you allow voice inputs, these are also mostly transcribed in the cloud as well. Natural Language Processing is the process by which a user's question gets processed and matched with a bank of available intents. Governance: if a bot says you can stay at home if it snows, does that count? Who checks when that what bots are saying is correct? Maintenance: if bots are drawing on APIs to serve real-time data, who will be responsible to debug and fix the APIs when they will inevitably require maintenance? (See 8.)ĭeployment: will users need to navigate to certain Intranet pages for each bot or will there be integrations for Microsoft Teams or Slack? (See 7.) Search vs chatbot: when should users consult a bot, and when the Enterprise search or Intranet search? Or should chatbots appear in search results directly? Quality: who checks that the bot understands enough of the queries users have and who ensures it gets retrained as people use it? (See 6.)ĭiscoverability: how will the average user become aware that there now is a "Find a legal expert" bot or a "Make a meeting room reservation" bot? ![]() Whether you have a decentralized bot platform or not, there are some pretty considerable questions you need to try and solve for your project to become 'production ready': So you should check how agnostic your chosen platform is when it comes to handing conversations off to 3rd party chatbots. a CRM solution that you acquire may already feature a decent chatbot. However, in a future of chatbots there are inevitably going to be chatbots from 3rd parties, e.g. Editor's tip: You may find that many bot platforms may try and convince you they're also a master bot product provided you get all your bot needs fulfilled by them.
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