Conversational AI technology is five parts working in sequence: a channel that receives the message, a language model that reads it, a knowledge source that supplies facts, a set of actions the system may take, and a record where the outcome is stored. If you understand those five parts, you can judge any product and set one up properly. This article explains each part in plain terms for an operations or sales lead, then shows how they map to the levelpartner.ai platform.
The five parts, in the order a message meets them
Channel. The message arrives by web chat, SMS, WhatsApp, a social message, email or a phone call. For calls, speech recognition turns the voice into text first, and text-to-speech turns the reply back into voice.
Language model. The model reads the message in the context of the conversation so far and the instructions you wrote. It works out what the person wants and drafts a reply. Older chatbots matched keywords to fixed scripts; modern models understand intent from ordinary phrasing.
Knowledge. The model should not answer from general training. It should answer from your material: your services, prices, policies and processes. The system looks up the relevant passages from your knowledge base and gives them to the model alongside the question. This is often called retrieval.
Actions. A useful agent does things: books an appointment, updates a field, tags a contact, starts a workflow, hands over to a person. Actions are what separate a business tool from a chat toy.
Record. Every message, action and outcome is saved against the contact. Without a record, you cannot review, report or follow up.
Why the record and the actions matter most
Most coverage of conversational AI technology focuses on the model: which one, how fluent, how clever. For a business, the model is the part you control least and that matters least once it is good enough. The actions and the record decide whether a conversation turns into revenue.
An agent that writes a lovely answer but cannot book the meeting leaves your team to finish the job. An agent whose conversations are stored in a separate system leaves your salespeople blind.
Before you start
- An account with contacts, calendars and at least one connected channel.
- Your knowledge material in a form you can upload: documents, web pages or question-and-answer pairs.
- A list of actions you want the agent to take, and the ones it must never take.
How to set it up
- Go to AI Agents > Conversation AI and click + Create Bot.
- Select Prompt Based Bot.
- Choose General Q&A, Appointment Booking, Marketplace Template or Start from Scratch.
- Continue into the bot editor.
- Configure Bot Settings.
- Configure Bot Training.
- Configure Bot Goals using prompts, model settings and actions.
Imagine a visitor to a 25-person consultancy's site typing "Do you work with charities and can I talk to someone next week?" The channel delivers it. The model would recognise two intents. Retrieval finds the sector page that confirms charity work. The booking action offers three slots next week and confirms one. The record would then hold the conversation, the booked meeting and a sector tag, all within about four messages.
What to check when comparing products
Ask how each part is handled. Which channels are native and which need an integration? Can you see which knowledge passages the answer used? Which actions are built in? Where is the record stored, and is it the same place your team works? A product that is strong on the model but weak on actions and record will cost you staff time.
Buyers test a conversational AI by asking it trivia. That tests the model only. Test it with a real enquiry that requires a lookup, a booking and a hand-off.
When the technology is not the bottleneck
If your team does not answer hand-offs, or your calendar shows no free time, the best technology will not help. Fix the process first. If you get very few conversations, a person may be quicker than any set-up.
For the broader picture, read the conversational AI overview. For how the knowledge part works in more depth, see knowledge based agent in artificial intelligence. For phone calls specifically, the AI receptionist guide covers the speech side.
Time to run each week
About an hour. Most of it goes on the knowledge layer: adding answers to questions the agent could not handle. Instructions change less often, and actions rarely once tested.
Troubleshooting
The agent invents facts. The knowledge layer is missing the answer, so the model guesses. Add the fact, and instruct the agent to say it will check rather than guess.
Bookings are offered but not saved. The action is enabled but the calendar is not linked to the agent. Link it and test again.
Conversations do not appear on the contact. The channel is connected outside your account. Reconnect it through the platform so messages are stored.
Frequently asked questions
Is conversational AI technology the same as a large language model?
No. The language model is one of five parts. On its own it can chat, but it cannot look up your facts, take actions or store a record.
Do I need to choose the model?
On the platform you do not need to. What you control is the instructions, the knowledge and the actions, and those shape the results far more.
How does voice work differently?
Voice adds speech recognition and speech output around the same core. Replies need to be shorter, and confirmations matter more, because callers cannot scroll back.