StudioServicesai-workflowsai chatbots and customer su…
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Service · AI Workflows

Support that answers before your team wakes up.

KreativeHub builds AI chatbots and customer support automation for medium and enterprise brands. We train each bot on your own help docs, policies and past tickets, so it resolves routine questions in seconds, hands the hard ones to a human with full context, and gives your support team back the hours they lose to repeat queries.

demand-index.livesnapshot
+78%Y/Y client growth
3.4×Median ROAS · paid
98%Retention · cumulative
−34%CPL · B2B engagements
LIVE

Measured in pipeline, not pageviews. Senior operators only. Five clients per quarter, capped on purpose.

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A support bot is only as good as what it knows

Most chatbots fail for one reason: they have never read your documentation. They guess, they loop, and they push frustrated customers towards a contact form anyway. The result is a worse experience than no bot at all, and a support queue that keeps growing.

We build differently. Every bot we deploy is trained on your actual material, your help centre, product docs, policies and resolved tickets, using Retrieval-Augmented Generation (RAG). The bot retrieves the relevant passage before it answers, so its replies are grounded in what your business actually says, not a plausible-sounding invention.

That means it can resolve the questions that fill your queue every day. Where is my order, how do I reset my password, what is your returns policy, does this plan include that feature. The ones it cannot answer, it escalates to a human with the full conversation attached, so nobody starts from scratch.

This is one part of our AI Workflows practice, where support automation connects to your customer relationship management (CRM) system and the rest of your stack. If you want to see where it would pay off fastest, start with a free audit.

Frame · Manifesto · 3 positions
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What a modern support bot actually does

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Answers grounded in your knowledge

We index your help docs, product pages, policies and resolved tickets, then use Retrieval-Augmented Generation (RAG) so the bot quotes from that source material rather than guessing. Answers stay accurate as your products change, because we update the index, not the model. When the bot is not confident, it says so and routes the customer to a person instead of bluffing.

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Bots that do things, not just talk

A reply is only half the job. Our bots take action through your existing systems: checking order status, starting a return, resetting access, booking an appointment or updating a CRM record. We connect them to your tools through function calling, so a customer gets the outcome they came for in the same conversation, not a ticket number and a wait.

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A clean handoff to real people

When a query is sensitive, high value or simply beyond the bot, it hands the conversation to your team with the full history, the customer detail and what it has already tried. Your agents pick up mid-thread instead of asking the customer to repeat everything. The bot handles volume; your people handle the moments that need judgement and care.

Frame · Capabilities · 6 pillars
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What we build into every bot

The pieces that turn a chatbot from a deflection tactic into real customer support.

See how support fits our AI Workflows
  • 01

    Trained on your own knowledge base

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    One bot across web, WhatsApp and SMS

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    CRM and helpdesk integration

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    Tone and sentiment matched to your brand

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    Lead capture and qualification

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    Cover around the clock, every day

Frame · Method · 4-phase flow
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How we build and ship a support bot

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01. Ingest your knowledge

We pull in your help centre, product documentation, policies and a sample of resolved tickets. This becomes the bot's source of truth, so it answers from what your business actually says rather than generic web content. We flag any gaps in your docs as we go, because the bot exposes them quickly.

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02. Shape the voice and rules

We write the system prompt so the bot sounds like your brand, knows what it must never do, and follows your policies on refunds, escalation and data. We set the guardrails that decide when it answers, when it asks a clarifying question, and when it hands off to a person.

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03. Connect your systems

We integrate the bot with your CRM, helpdesk and the tools behind your common requests, so it can check an order, start a return or update a record in the conversation. We deploy it across the channels your customers actually use, from your website to WhatsApp and SMS.

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04. Monitor and improve

Once it is live, we review real conversations, measure resolution rate and escalation reasons, and tighten the answers that fall short. The bot gets more accurate every week as we feed back what we learn, and you see the numbers behind it rather than taking our word for it.

Frame · FAQ · 7 questions
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Support automation, answered

Every question we get asked on first calls. Answered in writing — decide before you book.

It is built not to. We use Retrieval-Augmented Generation, so the bot retrieves the relevant passage from your own documentation before it replies, rather than generating an answer from memory. We tune it to give a low, factual response and to escalate to a human when it is not confident, instead of guessing. You can review every conversation it has, so accuracy is something you can check rather than hope for.
Most older chatbots follow fixed decision trees or run on a generic model that has never seen your business. They break the moment a customer phrases a question in their own words. Our bots understand natural language and answer from your actual help docs, policies and ticket history, so they handle the messy, real questions your customers ask rather than only the ones you scripted.
The routine, high-volume questions that fill most support queues: order and delivery status, returns and refunds, password and access issues, account changes, product and pricing questions, and booking or rescheduling. Where it has access to your systems, it completes the action too, not just describes it. Anything sensitive or unusual goes to your team with the full context attached.
No. It removes the repetitive questions that burn out agents and slow down replies, so your team focuses on the conversations that need a human: complaints, complex cases, high-value customers and anything requiring judgement. Most clients use it to handle more volume with the team they have, and to give faster answers outside working hours, not to cut headcount.
We deploy a single bot across the channels your customers use, including your website, WhatsApp and SMS, so the experience is consistent everywhere. We integrate it with your CRM and helpdesk and with the systems behind your common requests, such as order management or booking. We build to your existing stack rather than asking you to switch platforms.
Yes. We design the bot to follow your data handling rules, keep customer information inside the systems you already trust, and only pass what is needed to resolve a request. We agree what the bot can access and store before anything goes live, and we are fully transparent about how it works, with no hidden processing behind the scenes.
A focused support bot trained on your existing documentation typically takes 3 to 6 weeks to build, test and launch. The timeline depends on how clean your documentation is and how many systems we connect for actions like order lookups or returns. We test it against real past tickets before it ever speaks to a customer, so it launches ready rather than as an experiment.
Send the studio a brief
Frame · Apply · new file
apply · q2-2603/05 open
Three slots remain · Q2 ’26

See what your bot could handle

Send us your support volumes and the questions that fill your queue, and we will run a free audit showing how much a trained AI chatbot could resolve, where it would hand off to your team, and the hours it would give back. Senior team, full transparency, no fixed packages.

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Customer Support Automation | KreativeHub