The assistant sits in a chat widget on your site, and the same setup can run on WhatsApp, SMS or Slack. Here a visitor asks if the warranty covers water damage, the kind of question your team answers every day.
AI chatbot development: bots that answer from your content and know when to hand off.
We build AI assistants grounded in your own documents, policies and systems, with guardrails, human handoff and measurable accuracy - for your website, WhatsApp, SMS or internal teams.
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At a glance
- Starting price
- From $4k
- Typical first release
- 2–4 weeks
- Pricing model
- Fixed price per scope
- You own
- Code, data & accounts
- Free 30-minute consultation
- Written scope before any work
- Working demo every week
- 30 days of support after launch
A good business chatbot does three things well: answers questions correctly from your information, captures and qualifies the people who are ready to buy, and hands the conversation to a human the moment it's out of its depth. Everything else is decoration.
We build chatbots with retrieval-augmented generation (RAG) - the model answers from your approved content rather than guessing - and we test them against a set of real questions before launch, so you know the accuracy before your customers do.
How a chatbot answers from your content, and knows when to hand off.
Follow one question from a website chat through search, drafting and a confidence check, to a cited answer or a person on your team. Scroll to step through it, or ask the assistant a question yourself.
Your help center, policies and price lists are split into passages and indexed in PostgreSQL with pgvector. The question is turned into a vector, and hybrid search finds the passages closest in meaning, not just the ones that share a keyword.
The model gets the question and those passages only, and is told to cite its source and say when it doesn't know. Personal details are redacted first. A confidence check then scores how well the sources support the draft.
Well-supported answers go back with a link to the source. Anything uncertain, and topics you mark sensitive like refunds, go to your team in Zendesk, Intercom or HubSpot with the transcript attached, so nobody asks the visitor to repeat themselves.
Every conversation is logged. Before launch we build a set of real questions with known answers, run it, and re-run it after every change. When an answer is wrong, we fix it at the source, usually a missing or contradictory document.
AI Chatbots: what it looks like in practice.
Website support assistants
Answer product, pricing and policy questions 24/7 from your help center and documents, with links to the source.
Lead qualification bots
Ask the right questions, score the lead, book the appointment and push everything into your CRM.
WhatsApp & SMS assistants
The same assistant on the channels your customers already use - see WhatsApp automation.
Internal knowledge assistants
Staff ask questions of SOPs, contracts and manuals instead of interrupting the one person who knows.
Booking & order status
Connected to your scheduling or order systems so the bot can actually check availability or status, not just talk about it.
Human handoff & inbox
Seamless escalation to your team with the full conversation, in a shared inbox or your helpdesk.
What it costs, in real numbers.
Start with a pilot on one channel and one knowledge base, measure it, then expand. Typical ranges:
Pilot
From $4k
One channel, one knowledge base, human handoff, a tested set of real questions and an accuracy report.
2–4 weeks
Production assistant
$12k–$35k
Multiple channels, CRM or helpdesk integration, lead capture, analytics and admin tools to update content.
6–10 weeks
Agentic workflows
$35k+
The assistant takes actions in your systems - bookings, refunds, order changes - with approvals and audit logs.
3+ months
AI model usage is billed per use by the provider (OpenAI, Anthropic and others), plus hosting and any messaging-channel fees. For most small-business volumes that's tens to a few hundred dollars a month; we estimate it from your real traffic before you commit.
From first call to launch, no surprises.
A written scope and a fixed price before any work starts, a working demo every week, and a clean handoff at the end.
- Step 011 week
Use-case & content audit
Which questions matter, where the answers live, and which ones must always go to a human.
- Step 02Part of week 1–2
Evaluation set
We collect 50–200 real questions with correct answers - the yardstick for accuracy.
- Step 031–3 weeks
Build the pilot
Retrieval over your content, conversation design, guardrails and handoff.
- Step 041 week
Test & tune
Run the evaluation set, fix wrong answers at the source, and report accuracy before launch.
- Step 05Ongoing
Launch & monitor
Go live on one channel, review conversations weekly, then expand.
Proven technology, your accounts.
Technology we use
- Models
- OpenAI APIAnthropic Claude APIOpen-weight models when data must stay private
- Retrieval
- PostgreSQL + pgvectorDocument parsingHybrid search
- Channels
- Website widgetWhatsApp Business PlatformSMS (Twilio)Slack / Teams
- Safety
- GuardrailsPII redactionHuman handoffConversation logs
Systems we integrate with
Named platforms are examples we build against through their public APIs - not partnership claims.
An honest fit check.
A strong fit if…
- Your team answers the same 30 questions every day.
- Leads arrive after hours and go cold before anyone replies.
- You have written content - help docs, policies, price lists - to ground the answers.
Probably not the right move if…
- You need a quick FAQ widget - an off-the-shelf tool like Intercom Fin or Chatbase may be cheaper; our [AI chatbot cost guide](/guides/ai-chatbot-cost) compares them.
- Answers depend on judgment calls that must never be automated.
What we'd tell you on the first call.
Why accuracy is measured, not promised
Every chatbot sounds smart in a demo. The difference is how it handles the awkward questions. We build an evaluation set from your real inbox and chat logs, run it before launch and after every change, and share the results. Wrong answers get fixed at the source - usually a missing or contradictory document.
Custom build or subscription tool?
Subscription chatbots charge per seat or per resolution and work well for standard help-center Q&A. Custom wins when the bot must act inside your systems, follow your compliance rules, run on WhatsApp, or when per-resolution fees at your volume exceed the cost of owning it. See our custom AI chatbot vs. off-the-shelf breakdown.
Software our team built and runs.
We don't just build for clients - we operate our own SaaS products in production, so we design for the unglamorous parts: billing, support, uptime and change.
Billing & collections · SaaS
WhatsApp-first billing platform
Recurring billing and collections with WhatsApp delivery, digital payments, automatic ledgers, attendance and a customer app.
- Automated monthly billing
- Digital payment collection
- Self-updating ledgers
- WhatsApp team inbox + AI
AI Chatbots: questions buyers ask.
How much does a custom AI chatbot cost?
Our pilots start around $4k for one channel and one knowledge base. Production assistants with integrations typically run $12k–$35k, plus AI usage fees that depend on volume.
Will the chatbot make things up?
We ground answers in your approved content, instruct the model to say when it doesn't know, route sensitive topics to humans, and measure accuracy against real questions before launch.
Can it work on WhatsApp?
Yes, through the official WhatsApp Business Platform. WhatsApp's policies allow businesses to use AI for customer service; general-purpose AI assistants are not permitted, so we design for your business use case.
Can the chatbot book appointments or update our CRM?
Yes. We connect it to your calendar, CRM or order system so it can check availability, book, and log leads with the conversation attached.
Which AI model do you use?
We choose per project - commonly OpenAI or Anthropic models - based on accuracy on your evaluation set, cost and data requirements.
Is our data used to train the AI model?
We use API providers and settings where your business data isn't used to train their models, and we document where data is stored.
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Based in Fort Lauderdale, working with businesses across the US. See where we work.
