Integrate AI Chatbot — Without Re-launching Your Site
Production AI that grounds answers in your data
Integrate AI Chatbot — done properly, by senior engineers
The gap between an impressive AI demo and a chatbot you can put in front of customers is almost entirely production engineering. A bot that hallucinates a refund policy, leaks a system prompt, or runs up an unbounded API bill is worse than no bot at all. We integrate AI chat the way it needs to work in production: answers grounded in your own documents and product catalogue through a proper RAG pipeline, citations so users (and you) can trust the source, guardrails and confidence thresholds that hand off to a human when the model is unsure, and a per-conversation cost and latency dashboard so the economics stay under control. It ships on your stack, in your brand voice, behind a pull request you review — not as an opaque third-party widget.
What you're seeing
You need an AI chatbot, not a scripted one — but you also need it to stay accurate and on-brand.
Our approach
We ship a RAG-grounded AI chatbot on your stack, with guardrails, audit logs, and a per-conversation cost dashboard so you stay in control.
Symptoms teams come to us with
- Off-the-shelf bots look cheap or answer off-brand
- The assistant invents facts and users have noticed
- Support is drowning in repetitive tier-1 questions
- You have the data but no production-grade pipeline
What we get right
- 01Retrieval grounded in your own docs and catalogue
- 02Guardrails, citations and confident-but-wrong prevention
- 03Clean human hand-off when confidence drops
- 04Per-conversation cost, latency and analytics controls
What you get
Concrete deliverables, no fluff
Every engagement ends with measurable, documented outcomes — no black-box agency reports.
Use-case discovery + dataset prep
RAG-grounded prototype on your knowledge base
Production rollout with guardrails + analytics
Cost-control + escalation runbook
What changes after we ship
Grounded, cited answers
A RAG pipeline over your real content means the bot answers from your data and cites its sources instead of inventing them.
Guardrails and human hand-off
Confidence thresholds, refusal handling and a clean escalation to a human when the model is unsure or the topic is sensitive.
Cost and latency under control
Model routing, caching and streaming keep responses fast and the monthly API bill predictable.
On-brand and on your stack
The voice, UI and data stay yours — no generic third-party widget that looks bolted on.
From brief to shipped fix
A transparent, low-risk process — a senior engineer reads your brief personally, and nothing starts until you approve a written plan and price.
Diagnose
A senior engineer reviews your brief, reproduces the issue, and pinpoints the real root cause — not the symptom — before any code is touched.
Scoped plan & quote
You get a written plan to integrate AI Chatbot, a firm timeline, and a fixed quote. Nothing starts until you approve it — no surprise invoices.
Ship the fix
We implement on a branch and open a pull request you review, working to your code-review standards on your repo — never a black box.
Verify & hand off
We verify on staging and production, share before/after evidence where it applies, and leave you a short hand-off note so the fix sticks.
Situations we handle
Deflecting tier-1 support
A support assistant grounded in your help docs and ticket history, with hand-off to Zendesk, Intercom or Freshdesk.
Answering from a messy knowledge base
Multi-source, frequently-updated content turned into a reliable, cited retrieval pipeline.
On-site sales and search
A product-aware assistant that helps visitors find and choose, backed by semantic search over your catalogue.
Why teams hand this task to Krapton
Senior engineers only
Your brief is read and handled by a senior engineer — no junior hand-off, no sales-rep filter in between.
Root cause, not a patch
We reproduce and fix the underlying cause, then add a guard so the same class of issue does not quietly return.
Your repo, your standards
Every change lands as a pull request you review, on your repository, following your existing review process.
NDA on day one
Confidentiality and IP are covered before we look at a single line of code. All work stays in your accounts.
Fixed quote up front
You approve a written plan and price before work starts. If scope changes, we re-quote in writing — no surprise invoices.
Proof, where it applies
Performance, SEO and reliability work ships with before/after evidence so the result is measurable, not anecdotal.
Three ways to engage
No retainer required. Pick the model that matches the work — pricing for this task starts from $3,000, with a fixed quote before anything starts.
Per task
Most popularOne clearly-scoped fix at a fixed price. Best when you know exactly what is broken and want it handled end to end.
- Fixed quote up front
- One PR, reviewed by you
- No retainer required
Hourly
Pay only for the hours worked. Best for diagnostics, audits, or exploratory work where the scope is still emerging.
- Weekly timesheets
- Pay for what you use
- No minimum commitment
Per sprint
A focused 1–2 week sprint when the work is bigger than one fix but smaller than a full project.
- 1–2 week blocks
- Clear sprint goal
- Scale up or stop anytime
Tooling we use
Industry-standard stack, no proprietary lock-in
Integrate AI Chatbot — your questions, answered
How much does it cost to integrate AI Chatbot?
Pricing starts from $3,000 and depends on the scope we find during the diagnostic. You get a fixed, written quote before any work begins — most engagements like this run 2–6 weeks.
How long does it take to integrate AI Chatbot?
Typically 2–6 weeks for a focused engagement. After a short diagnostic we commit to a firm timeline so you know exactly what to expect.
Will you work directly on our existing codebase?
Yes. We work on your GitHub, GitLab or Bitbucket, ship every change as a pull request you review, and follow your code-review standards — not ours.
What exactly will I have at the end?
Concrete, documented outcomes — Use-case discovery + dataset prep, RAG-grounded prototype on your knowledge base, Production rollout with guardrails + analytics, and more. No black-box agency report.
How quickly can you start, and do you sign an NDA?
For a focused task like this we can usually start within 24–48 hours of the brief. We sign an NDA on day one, before we look at any code — yours or ours.
How do you stop the AI from hallucinating or going off-brand?
We ground answers in your own content with retrieval, require citations, add guardrails and confidence thresholds, and hand off to a human when the model is unsure — so it stays accurate and on-brand in production.
How do you keep the chatbot from making things up?
Grounding plus guardrails. We retrieve from your own content and require the model to answer from (and cite) that context, add confidence thresholds and refusal handling, and hand off to a human when it is unsure — so it stays accurate instead of confidently wrong.
Which model do you use — OpenAI, Anthropic, something else?
Whatever fits your accuracy, latency and cost targets — we work with OpenAI, Anthropic Claude and open models, and often route between them. We are not tied to one vendor and will recommend based on your evals, not a partnership.
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Let's get this off your plate
Send a 60-second brief on Integrate AI Chatbot and a senior engineer replies within 24 hours with a plan and a fixed quote. NDA on day one, no retainer required.