![]() 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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