Agents that answer, qualify and follow up.
A chatbot recites your FAQ. An agent reads your actual data at the moment the question is asked and answers with your numbers. The difference is not the model — it is the context it can reach.
What our agents actually do
Lina handles travel enquiries for the group’s agency; Marco runs prospecting. The same layer is configured for each client’s business.
- Answer questions on your site around the clock, in English or French
- Qualify a lead by asking the questions your reps would ask
- Create the record in your CRM with the conversation attached
- Follow up by email or SMS when someone goes quiet
- Hand off to a human with the full context, instead of starting over
What we are honest about
The AI market is full of claims that do not survive contact with a technical buyer. Ours are deliberately checkable.
- Orvel AI is our agent layer, built on top of leading language models — we do not train or host a model of our own
- Your data is never used to train anyone’s model
- One layer, several models underneath: no dependency on a single provider
- An agent that does not know should say so and escalate — we configure it that way
Frequently asked questions
What is the difference between an AI agent and a chatbot?
A chatbot answers from a script or a FAQ. An agent reads your live data at the moment of the question — your services, prices, availability, records — and answers with your actual numbers, then takes an action such as creating a CRM record or booking a call.
Is Orvel AI your own model?
No, and we do not claim it. Orvel AI is our agent layer: the orchestration, the context and the integrations we built, running on top of leading language models. What differentiates it is the business context it can reach, not the weights underneath.
Is our data used for training?
No. The APIs we use do not train on customer data, and we do not use your content to train anything. We will state in writing where your data goes before you sign.
What happens when the agent does not know?
It says so and escalates to a human with the full conversation attached. An agent that invents an answer costs more than one that admits a gap, so we configure for the second.
Can it work in languages other than English and French?
The models handle many languages well. We support English and French end to end, including the human escalation; for other languages we can configure the agent but you will want a native speaker reviewing its output before launch.
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