A bot that closes routine questions using facts from your documents, says plainly when it doesn't know, and hands the question to a person. With CRM handover and regular review of conversations.
The real risk with a smart bot isn't that it fails to answer — it's that it answers confidently and wrongly: a discount that doesn't exist, an invented lead time, a condition you don't offer. Customers reasonably expect a promise like that to hold, and blaming the model afterwards is a poor position to argue from. So we build the assistant so there is nothing for it to invent from: it answers only from your knowledge base, it says so and hands over to a person when the answer isn't there, and prices and lead times come from a maintained source rather than the model's memory. Anything touching money or obligations defaults to human confirmation. Before launch we run a list of real customer questions through it and check the answers by hand; after launch we review conversations and extend the knowledge base. The value is measured not by having AI on the site but by the share of questions closed without an operator and by the enquiries that reach your CRM.
Enquiries come in at night and at weekends and get answered on Monday. By then the person has usually asked somebody else.
'Choose menu option 3' — users close the tab. NPS on scripted bots trends negative.
Most incoming questions are about price, lead time and how it works. Experienced people spend their day on answers a document could give.
Client ready to buy at 11pm Sunday — no one to respond. Lead goes to the competitor with a working bot.
Contact form generates many cold leads. Salesperson spends 30 minutes qualifying each one.
International audience needs EN/ES/DE reps. Each is $60K-100K/year in salary.
Not a template — custom-configured for your product, brand voice, sales funnel, target audience.
Load: website, PDF catalog, FAQ, case studies, documentation. Bot answers from your knowledge base, not generic responses.
Asks the right questions (budget, timeline, project type), assigns lead score, passes only qualified leads to sales.
HubSpot, Salesforce, Pipedrive, Intercom, Telegram, WhatsApp Business API. Lead flows to your funnel with full conversation history.
Product selection through questions, pricing calculation, meeting booking, proposal delivery — all inside the chat without hand-offs.
One bot answers in 10+ languages automatically. No need for separate EN/ES/DE support reps.
Dashboard: top questions, conversion by stage, answer quality, drop-off points. Bot continuously improves on real conversations.
We scope it after a short review: which questions it must handle, where the facts come from, where enquiries are handed off and what happens when it isn't sure. A bot without a well-built knowledge base is cheap and expensive at the same time.
For reference: in 2026 a bot with a knowledge base and CRM handover runs in the low thousands of dollars to build, with monthly support on top.
A handover path to a human is mandatory. A bot you can't escape loses customers.
Not templates — a custom model on your data. Responds like your company's expert, not with generic replies.
Bot doesn't just chat — asks the right questions, scores leads by your criteria, hands off only qualified ones.
HubSpot, Salesforce, Pipedrive, Intercom, any CRM via API. Leads flow to your funnel with full history.
Only answers from your knowledge base. If it doesn't know — says 'let me check with our team', not making things up.
Study your website, funnel, common customer questions, sales practices. Define bot scenarios.
Design flows: greeting, qualification, top-30 questions, product recommendations, sales escalation.
Load site, catalog, FAQ, cases into knowledge base. Fine-tuning to your tone of voice.
Connect to CRM, messaging channels, analytics. Configure lead routing, scoring, escalation.
Run 100+ test conversations, identify weaknesses, retrain. Pilot with internal team.
Start on a share of traffic and watch the logs, then open it up once the answers hold. After launch we keep reviewing conversations and extending the knowledge base.
The real risk with language models is confident fiction: a discount that doesn't exist, a lead time nobody promised, a term you don't offer. You contain it with architecture, not with promises.
If the bot quotes a price, promises a date or states a condition, the customer reasonably expects it to hold. "That was an AI error" is a poor position in a conversation and a worse one in a dispute. So we fix the boundaries: what the bot may assert outright, and what it phrases as provisional and a person confirms. Anything touching money, deadlines or obligations defaults to human confirmation.
No 'maybe' or 'I'll get back to you' — if the bot doesn't know, it escalates honestly. False answers kill trust.
The bot handles routine and hands over anything it isn't sure about, with the full conversation. A bot you can't escape loses customers.
Every lead has a baseline score. Sales doesn't waste time on 'how much' — only on closing deals.
Every month we analyze conversations, find where the bot gets confused, retrain. Quality doubles in 6 months.
Architecture, not promises. It answers only from your knowledge base — documents, price list, terms — with no free reasoning. When the answer isn't there it says so and hands the question to a person, which is better than a polished invention. Prices and availability come from a maintained source. Conversations are logged and reviewed, and before launch we run real customer questions through it and check the answers by hand.
No — it takes the routine off them. How much it closes depends on how well the knowledge base is built, and that shows up in the logs within the first weeks. We report that figure as it is. Complex cases go to a person with the full conversation attached, because that's where deals are actually made.
You are, in practice — which is why we set the boundaries explicitly. The bot may state what's in the knowledge base; anything touching money, deadlines or obligations is phrased as provisional and confirmed by a person. That's a deliberate design decision, not a limitation we ran into.
Most of the time goes into the knowledge base, not the integration: gathering accurate answers, deciding what the bot may say and where it must hand over. We give a schedule after a short review of your questions and materials. A bot deployed without that groundwork is quick to launch and expensive to live with.
Share of conversations closed without an operator, share handed to a human and why, enquiries from the bot that reached the CRM and their quality as you judge it, repeat questions on the same topic, and response time outside working hours. The second metric is the most useful: it shows exactly what the knowledge base is missing.
The site, and messaging channels where your customers already are. The channel matters less than the knowledge base behind it: the same grounded answers should be available wherever the question is asked, and every enquiry should land in one place rather than in separate inboxes.
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