Conversational AI Services

Conversational AI is a system that understands what a customer means in their own words and responds from your real content and systems, across chat, voice, or messaging. A scripted chatbot follows a decision tree and can only handle the paths someone drew in advance. The practical difference shows up on the phrasing nobody predicted: a scripted bot dead-ends, and a conversational system still understands the intent and either answers or escalates.

Buy when your volume is standard customer support on a mainstream helpdesk. Those products are good at common intents and priced per resolution, and no custom build beats them on time to launch for that job. Build custom when the conversation has to reach your own systems, follow language a regulator constrains, or run in a channel the vendors don't support. We'll tell you which case you're in before you commit budget.

Every reply is generated from your help content, your policies, and live data from your systems, and the system is instructed to refuse rather than guess when the material isn't there. It's also bounded on what it may promise, discount, or disclose, so a persuasive customer can't talk it into a commitment you didn't authorise. We then score it against a test set built from your real conversations before it goes anywhere near a customer.

It escalates. The handoff carries the full transcript, the detected intent, and the customer record, so the agent picks up mid-conversation instead of asking the customer to start again.

Yes, and we usually recommend chat first. Chat costs less per conversation and mistakes are easier to correct, so it's the cheaper place to prove your intents and answers. Once those are working, the same knowledge layer drives a phone agent with speech recognition, natural voice output, and barge-in handling, so callers can interrupt the way they do with a person.

Your website and app, WhatsApp, SMS, Messenger, Slack, Microsoft Teams, and the phone. The conversation logic and knowledge layer stay shared across channels, so an answer you correct once is corrected everywhere, and a customer moving from chat to phone doesn't start over.

Containment and escalation are tracked per intent rather than as one headline deflection number, because an average hides the intents where the system is quietly failing. We also watch customer satisfaction on contained conversations specifically, since a bot that refuses to escalate can post excellent containment and terrible service at the same time.

Yes. The system detects the customer's language and replies in kind, including when someone switches mid-conversation, without running a separate bot for each market. Our own assistant does this in production, auto-detecting the visitor's language and switching seamlessly during a conversation.

Per industry averages, a focused single-channel chatbot grounded in your content typically runs from around $25,000–$70,000, while a multi-channel system with voice, live system integrations, and compliance requirements usually lands between roughly $80,000 and $250,000 or more, depending on channel count, integration depth, and language coverage. Per-conversation running costs sit separately and scale with volume.

Custom work doesn't fit a fixed price list, so we scope your project and provide a tailored estimate; if you want a build-ready plan with a fixed bid first, our Discovery Sprint is available at a fixed price. You can also use our Scope Generator to receive an approximate overview of what to expect.

A working proof of concept typically takes about a week and a production-ready first version about a month. Voice and regulated industries run longer, because speech tuning and compliance review both take real time. The first step is always a Scope & Design Document that turns the goal into a phased plan with milestones.

Yes, completely. You own the application code, the prompts, the conversation and intent designs, the integrations, and the transcripts, with full IP rights transferred and everything running in your own accounts. The conversation designs and the transcript history are what any future team tunes against.

Yes. We build to HIPAA, GDPR, PCI DSS, and SOC 2 practices depending on what you handle, with encryption in transit and at rest, redaction of sensitive data before it reaches a model, scoped retention on transcripts, and audit logging on every conversation. In regulated flows we also constrain what the system is permitted to say, not just what it can access.

Conversations drift as your products, policies, and customers change, and someone has to own that. We monitor containment, escalation, and cost per conversation, review the conversations that failed, and retune intents and content as part of ongoing support. With 80% of our clients staying 7+ years, this is the normal shape of our engagements.