A Bot That Actually Answers the Right Way
Custom AI chatbot development by a Philippines-based engineer. I build production-grade chatbots using LangChain, RAG, and OpenAI that handle customer support, lead qualification, and internal queries — trained on your data, deployed to your stack.
Your support queue is full of questions you've already answered a hundred times.
The same 30–40 questions account for the majority of incoming support volume in most businesses. "What are your hours?" "How do I reset my password?" "What's your return policy?" Your team answers them manually, every day, at the cost of focus and money.
Generic chatbots (the kind built with drag-and-drop tools) break on anything outside their script. Customers get "I didn't understand that" and immediately escalate to a human anyway. The bot becomes a frustration layer, not a solution.
A chatbot that knows your business as well as your best support rep.
I build chatbots using Retrieval-Augmented Generation (RAG) — the AI is grounded in your actual documentation, product specs, and FAQs. It doesn't hallucinate answers, and it knows when to escalate to a human. Clients in Davao City and internationally have seen 65% or more of support load shift to the bot within the first month.
- 65% average reduction in tier-1 support tickets handled by humans
- Trained on your documents — not generic internet knowledge
- Knows when to escalate: hands off to human agents gracefully
- Works on your website, Slack, WhatsApp, or internal tool
- Delivers consistent, on-brand answers at any hour
Chatbot Types I Build
Customer Support Chatbot
Handles tier-1 support questions across your product docs, FAQs, and policies. Deflects repetitive tickets, escalates edge cases, and logs conversations for review.
Lead Qualification Bot
Engages website visitors, asks discovery questions, scores leads by fit, and books meetings or routes hot leads to your CRM — without a sales rep involved.
Internal Knowledge Base Bot
An internal Slack or web-based assistant that answers employee questions from your SOPs, HR docs, and internal wikis. Reduces time spent searching for information.
E-commerce Assistant
Helps shoppers find products, answers questions about orders and shipping, surfaces upsell recommendations, and handles post-purchase queries autonomously.
Custom-Trained Chatbot
Your knowledge base is unique — I build a custom RAG pipeline indexed on your content, with domain-specific prompt engineering for accuracy your off-the-shelf tools can't match.
Chatbot Packages, Fixed Price
One-time project fee
Best for a focused FAQ or support bot on one channel with an existing knowledge base.
- Single-purpose chatbot (support or FAQ)
- RAG on up to 50 documents or pages
- One integration (website widget, Slack, or WhatsApp)
- Escalation routing to email or human agent
- Basic conversation analytics
- 2 weeks post-launch support
One-time project fee
Best for businesses wanting a full support or lead-qual bot across multiple channels.
- Multi-purpose bot (support + lead qualification)
- RAG on up to 300 documents
- Up to 3 channel integrations
- CRM / helpdesk integration (HubSpot, Zendesk, Intercom)
- Custom admin panel to update content without code
- Conversation logs and analytics dashboard
- 30 days post-launch support
Scoped per project
Multi-bot deployments, fine-tuned models, or chatbot integrated into a larger AI platform.
- Unlimited document corpus
- Fine-tuned or custom model option
- Multi-language support
- Enterprise SSO and data privacy controls
- Full deployment on your infrastructure
- Dedicated async support channel
- SLA-backed response times available
How a Chatbot Goes From Idea to Production
Content Audit
We identify what your bot needs to know: your FAQs, docs, policies, and product info. I audit for gaps — questions your bot will face that your current docs don't answer.
RAG Pipeline Setup
Your documents are chunked, embedded, and indexed in a vector database. The AI retrieves relevant context at query time instead of relying on memorized training data.
Prompt Engineering
Personality, tone, escalation rules, and answer boundaries are defined. The bot is constrained to stay on-topic and admit uncertainty rather than guess.
Integration & Testing
The bot is connected to your channel (website, Slack, WhatsApp). Real conversations are tested with hundreds of queries — edge cases, off-topic inputs, adversarial prompts.
Launch & Handoff
Goes live with monitoring in place. You get a dashboard showing conversation volume, deflection rate, and escalation triggers. The first 30 days surface what needs tuning.
Why These Bots Actually Work
Grounded in Real Content
RAG means the bot answers based on your actual documents — not what the base model "thinks" is probably true. Hallucinations are structurally prevented, not hoped away.
Knows Its Limits
The bot is prompt-engineered to say it doesn't know and connect the user with a human when confidence is low. No frustrated users stuck in a dead-end conversation.
65% Ticket Deflection
Clients handling 200+ support tickets per week consistently see 60–70% of those resolved by the bot after 30 days of live tuning. That's 130 tickets a human no longer touches.
Live in Days, Not Months
A focused Starter bot can go from signed contract to live widget in 7–10 business days. You don't wait a quarter to see results.
Channel Flexible
The same AI core can serve your website widget, your Slack workspace, and your WhatsApp Business number — without rebuilding from scratch for each channel.
Content Updates Without Code
Professional and Enterprise builds include an admin interface where your team can add documents, update FAQs, and refresh the knowledge base — no developer needed.
What Clients Report After 30 Days Live
"We were drowning in support tickets — most of them the same ten questions. Johnbert built a chatbot trained on our help docs and in the first month it deflected 65% of incoming tickets without a single human touch. The ones that do escalate come with a full conversation transcript, so our agents have context immediately."
"The lead qualification bot he built is running on our website 24/7 now. It asks the right discovery questions, scores leads, and drops hot ones straight into HubSpot with a meeting booked. We've added about 8 qualified calls a week that would have dropped off because nobody responded fast enough."
"We built an internal Slack bot to answer employee HR questions — leave policies, benefits, onboarding steps. Before, HR was spending 6–8 hours a week on these questions. The bot handles 80% of them now. It's been running for 5 months and we've updated the knowledge base ourselves twice without needing Johnbert."
AI Chatbot Questions, Answered Plainly
Johnbert Oñez
AI Solutions Engineer & Full Stack Developer · 6+ yrs · 50+ projects
Based in Davao City, Philippines. Specialises in production AI systems, full-stack web applications, and WordPress. Remote-first, async-friendly, fixed-fee projects.
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