AHK.AI's AI chatbot development experts combine GPT-4, Claude, or custom LLMs with Retrieval-Augmented Generation so your support team can deliver human-like answers 24/7 across web widgets, Slack, Discord, or WhatsApp. We handle data ingestion, guardrails, analytics, and training so you launch a compliant and scalable chatbot fast.
What You'll Get
Fully functional AI chatbot
Custom training on your data
Web embeddable widget
Admin dashboard
Conversation logging
Analytics and insights
Source code
Complete documentation
How We Deliver This Service
Our consultant manages every step to ensure success:
1
Discovery call to understand requirements
2
Design conversation flows and personality
3
Train AI model on your data
4
Develop and test chatbot
5
Integration and deployment
6
Training and handover
Technologies & Tools
OpenAI GPT-4 Claude LangChain Vector Databases React Node.js Pinecone Weaviate
Frequently Asked Questions
Which AI model do you use?
We primarily use OpenAI GPT-4 or Anthropic Claude, but can integrate any LLM based on your needs including open-source models like Llama for on-premise deployments.
Can the chatbot learn from my company data?
Yes! We implement RAG (Retrieval Augmented Generation) to train the bot on your documents, FAQs, and knowledge base. The bot retrieves relevant context before generating answers, ensuring accurate, company-specific responses.
What platforms does it support?
Standard package includes web widget. Premium includes Slack, Discord, WhatsApp, Microsoft Teams, and custom integrations via API.
What are the ongoing costs?
You'll need an OpenAI API account (typically $50-$300/month depending on usage) or Azure OpenAI for enterprise. Vector database hosting runs $0-$100/month. We'll help you estimate costs during discovery.
How accurate is the chatbot?
With proper RAG implementation and quality training data, chatbots achieve 85-95% accuracy on in-scope queries. We implement confidence scoring and human escalation for edge cases to maintain quality.
Can the chatbot escalate to humans?
Absolutely! We build seamless handoff to live agents via Zendesk, Intercom, Freshdesk, or your existing support platform. The bot passes conversation context so agents don't ask repeated questions.
How do you prevent the AI from making things up?
We implement guardrails: RAG grounding to source data, confidence thresholds for uncertain answers, explicit 'I don't know' responses, and moderation filters for inappropriate content. Enterprise packages include human review workflows.
How long does it take to build an AI chatbot?
Basic chatbots launch in 5-7 days. Standard with RAG takes 2-3 weeks including data ingestion. Enterprise implementations run 4-6 weeks with multi-channel deployment and integrations.
Client Reviews
★★★★★ 5
based on 89 reviews
★★★★★ 5
Support load dropped fast
We run a Shopify store with ~2,000 SKUs and constant “where’s my order?” tickets. AHK.AI built a GPT-4 + RAG chatbot that pulls from our returns policy, shipping tables, and order status docs. The web widget feels genuinely helpful, and the guardrails prevent it from inventing discount codes. The admin dashboard is clear, and conversation logs helped us spot missing FAQ content. Our agents now handle edge cases instead of repetitive tracking questions.
Project: GPT-4 RAG chatbot for Shopify storefront support, trained on policies and shipping/returns documentation with web widget + analytics
★★★★★ 5
Better answers, fewer escalations
Our B2B app has a deep knowledge base and release notes going back years. AHK.AI ingested our docs, API references, and internal runbooks, then deployed a Claude-powered bot in Slack for our support and CS teams. It cites sources and stays within our compliance boundaries, which was a hard requirement. The logging made it easy to identify hallucination attempts and tighten guardrails. Time-to-resolution improved noticeably, especially for integration questions.
Project: Claude + RAG Slack chatbot for internal support, trained on KB, API docs, and runbooks with guardrails and conversation logging
★★★★ 4.5
Solid intake assistant
We needed a patient-facing chatbot for appointment scheduling questions and pre-visit instructions without crossing HIPAA lines. AHK.AI set up a RAG workflow using our approved patient education materials and clinic policies, plus strict redaction and “no medical advice” guardrails. The widget integrates cleanly on our site, and the analytics show what patients ask most. It’s not a replacement for triage nurses, but it reduces basic call volume and keeps messaging consistent.
Project: HIPAA-conscious web chatbot using RAG on approved patient materials, with redaction guardrails, analytics, and logging
★★★★★ 5
Leads handled 24/7
Our brokerage gets inquiries at all hours, and agents can’t respond instantly. AHK.AI built a chatbot that answers listing questions, explains HOA fees from our docs, and collects lead details before handing off. We embedded it on property pages and connected it to WhatsApp for quick follow-ups. The admin dashboard makes it easy to update listing FAQs, and the conversation history helps us see which neighborhoods generate the most questions. It feels professional, not spammy.
Project: RAG chatbot for property listings with web widget + WhatsApp channel, trained on listing packets, HOA docs, and lead qualification scripts
★★★★ 4
Great, needs tuning
We operate a fintech help center and wanted an AI assistant that could explain fees, dispute timelines, and KYC requirements without making promises. AHK.AI delivered a custom LLM + RAG setup with strong guardrails and source-based responses. The rollout was fast and the logs are invaluable for audit review. We did need a couple iterations to reduce overly cautious refusals on legitimate questions. After tuning, it’s a reliable first line for support.
Project: Custom LLM RAG chatbot for fintech support, trained on policy docs and compliance scripts with audit-friendly logging and guardrails
★★★★★ 5
Clients get instant answers
As an agency, we field the same questions about reporting cadence, ad approval timelines, and onboarding steps. AHK.AI set up a chatbot on our client portal that pulls from our SOPs, Notion docs, and campaign checklists. The tone is on-brand and it escalates cleanly when someone asks for strategy advice. The conversation logging also shows what deliverables clients misunderstand, so we can tighten our onboarding. This has saved our account managers a ton of back-and-forth.
Project: Portal-embedded chatbot trained on agency SOPs/Notion docs with escalation rules, analytics dashboard, and conversation logs
★★★★ 4.5
Fewer repetitive RFQs
We manufacture industrial components and receive RFQs that require basic spec clarification (tolerances, lead times, material grades). AHK.AI built a chatbot that references our product datasheets and ISO-related documentation via RAG, so it can answer consistently and point to the right PDF sections. We deployed it on the website and in Discord for our distributor channel. It’s reduced low-value emails, though we still route pricing and custom quotes to sales by design.
Project: RAG chatbot for manufacturing product support using datasheets and ISO docs, deployed on web + Discord with routing rules
★★★★★ 5
Internal knowledge unlocked
Our consulting team has years of proposals, playbooks, and delivery templates scattered across folders. AHK.AI created an internal chatbot that indexes our documents and answers questions like “what’s our discovery agenda for a retail client?” with citations. We use it in Slack, and the admin dashboard lets our ops lead add new material without engineering help. The guardrails prevent it from leaking client names, which was critical. It’s become part of daily workflow.
Project: Slack-based internal chatbot trained on consulting playbooks and templates with privacy guardrails, citations, and admin-managed ingestion
★★★★ 4.5
Helps students self-serve
We needed a chatbot for an online program to answer questions about enrollment, course pacing, and LMS navigation. AHK.AI trained it on our student handbook, syllabus library, and support articles using RAG. The web widget is simple for students, and the analytics highlight peak confusion points (especially around grading policies). We had to tweak a few responses to match our academic tone, but overall it reduced tickets and improved first-response time during registration week.
Project: Student support chatbot trained on handbooks, syllabi, and LMS help articles with web widget, analytics, and conversation logging
★★★★★ 5
Shipment questions answered instantly
In logistics, customers want status updates and clear documentation requirements. AHK.AI built a chatbot that references our SOPs for customs paperwork, accessorial charges, and delivery exceptions. We deployed it on our customer portal and added a WhatsApp channel for drivers and dispatch. The guardrails keep it from guessing ETAs, instead prompting for the right tracking details. Conversation logs helped our team refine the top 20 questions quickly. It’s been a practical, scalable solution.
Project: Customer portal + WhatsApp chatbot for logistics support, trained on SOPs and customs docs with guardrails and logging
