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✓ On-time delivery
+ AI-powered
2-wk sprints
AI Chatbot Development Services

Custom AI Chatbots That Engage, Automate & Convert

We build intelligent chatbots and conversational AI systems — from customer support bots to sales automation. GPT-4, Claude, LLaMA, full deployment.

GPT-4 & Claude
WhatsApp & Web
NLP-Powered
100% IP Yours
Free first consultationNo commitment needed

Conversational AI

GPT-4, Claude, LLaMA, Rasa

100%

code & IP yours from day one

typical MVP timeline
est.

6–10 wks

48h

Avg. Response Time

no surprises, ever

What is an AI chatbot?

An AI chatbot is a conversational software system powered by a large language model (LLM) that understands natural language, reasons across context, and generates accurate responses — rather than following a fixed decision tree of pre-programmed answers. AI chatbots deployed with retrieval-augmented generation (RAG) answer questions about your specific products, policies, and knowledge base by retrieving from verified documents before generating a response, preventing hallucination. CodeShiper builds production AI chatbots with RAG pipelines, multi-channel deployment, CRM integration, and measurable accuracy before launch.

Services

What we build, how we do it

From a focused knowledge base chatbot to an enterprise multi-channel platform — every engagement is scoped in writing with a fixed fee before work begins.

01

RAG-Powered Knowledge Chatbot

Chatbots that answer accurately about your products, policies, documentation, and internal knowledge — by retrieving from verified sources rather than hallucinating from model memory. Full RAG pipeline: ingestion, chunking, embedding, vector search, retrieval tuning, and reranking.

02

Customer Support Chatbot

AI chatbot that handles tier-1 support queries, looks up order status, resolves common issues, and escalates complex cases to human agents with full context. Configurable escalation thresholds, handoff logic, and human agent notification.

03

Sales & Lead Qualification Bot

Chatbot that qualifies inbound leads, answers product questions, books demos, and captures contact information — deployed on your website, landing pages, or messaging apps. CRM integration included.

04

Internal Operations Chatbot

Enterprise chatbot for employees: HR policy queries, IT helpdesk, internal knowledge base Q&A, onboarding assistance, and workflow automation. Secure deployment within your infrastructure.

05

Multi-Channel Chatbot Platform

Single AI backend deployed across website, WhatsApp, Messenger, Telegram, Slack, and Microsoft Teams simultaneously. Consistent behavior, conversation history, and escalation logic across all channels.

06

Chatbot Fine-tuning & Optimization

Improve an existing chatbot with fine-tuning on your historical conversation data, retrieval pipeline optimization, and automated evaluation. Measurable improvement in accuracy, response quality, and task completion rate.

Deployment channels

One AI, every channel

We build a single chatbot backend that deploys across all your channels simultaneously. Same intelligence, consistent behavior, one codebase to maintain.

🌐

Website Widget

Embedded chatbot on any page. Fully white-labeled, customizable appearance, and mobile-responsive.

💬

WhatsApp

Deploy to your WhatsApp Business number with full RAG and CRM integration. Reaches 2 billion users.

📱

Messenger

Facebook Messenger integration for B2C businesses with social media presence.

✈️

Telegram

Telegram bot for communities, SaaS products, and international audiences.

⚡

Slack

Internal team bot or customer-facing Slack app with workspace-scoped knowledge bases.

🏢

Microsoft Teams

Enterprise Teams integration for internal operations, IT helpdesk, and HR bots.

Technology

The stack behind every chatbot

Production-proven tools selected for reliability, accuracy, and your specific deployment requirements — not whatever is trending.

Language Models
OpenAI GPT-4oAnthropic Claude 3.5 / 4Google GeminiLlama 3 (on-prem)
RAG & Vector
PineconeWeaviateQdrantpgvectorLangChainLlamaIndex
Channel APIs
WhatsApp Business APIMeta Graph APITelegram Bot APISlack BoltTeams Bot Framework
CRM Integrations
SalesforceHubSpotZoho CRMZendeskFreshdeskIntercom
How we work

From scope to deployed chatbot

Six stages with full transparency. You test real chatbot behavior at every milestone — not a demo against artificial questions.

Accuracy is measured, not assumed

We build the evaluation test set from your real questions before writing a line of chatbot code. Hallucination rate, retrieval accuracy, and escalation recall are all measured and reported before launch.

1

Use Case & Knowledge Audit

1 wk

Define the chatbot scope, map the questions it needs to answer, audit your knowledge base documents, identify integration points, and specify channel requirements. Output: written scope and architecture.

2

RAG Pipeline & Evaluation Setup

1–2 wks

Build the data ingestion pipeline, create the vector knowledge base, and establish the evaluation test set. We measure retrieval quality before building the conversation layer.

3

Conversation Design

1 wk

Design conversation flows, escalation triggers, fallback responses, tone guidelines, and persona. You review and approve the conversation design before we build it.

4

Chatbot Development

2–5 wks

Build the chatbot backend, channel integrations, CRM connections, admin dashboard, conversation logging, and analytics. Review demos at each sprint milestone.

5

Quality & Safety Testing

1–2 wks

Automated evaluation suite measuring hallucination rate, accuracy, escalation recall, and edge case handling. Manual testing of adversarial inputs and sensitive topic handling.

6

Launch & Ongoing Tuning

Ongoing

Production deployment, monitoring, and post-launch optimization. Retrieval quality improves with real usage data. Model updates and new knowledge base additions on retainer.

Pricing

Chatbot development cost & timeline

Cost depends on knowledge base complexity, number of channels, integration scope, and compliance requirements.

Project typeExample scopeTimelineIndicative cost

Focused RAG Chatbot

Single knowledge domain

Product/policy Q&A chatbot with RAG pipeline, web widget, basic analytics4–8 weeks$15,000–$35,000

Full Chatbot Platform

Multi-channel + CRM

Multi-channel deployment, CRM integration, escalation, admin dashboard, analytics2–4 months$35,000–$80,000

Enterprise Chatbot

Fine-tuning + compliance

Custom fine-tuned model, multi-language, compliance logging, SSO, on-premise option3–6 months$80,000+

Final pricing follows a free scoping call. Knowledge base size, channel count, and CRM integration complexity are the primary cost drivers.

Why CodeShiper

Why clients choose us for chatbot work

Production AI chatbots require more than connecting an API to a widget. Here is what our approach delivers that matters.

RAG before fine-tuning

We build the retrieval layer first. Hallucination rate is measured before launch, not discovered after a customer complaint.

Escalation design included

Every chatbot we build has configurable human escalation. No chatbot should handle every situation — we design the boundaries carefully.

Multi-channel from day one

One backend, every channel. No duplicated AI logic for each channel. Consistent behavior and context across web, WhatsApp, Telegram, Slack.

Your conversation data is yours

Conversations log to your infrastructure. Your data never trains third-party models. NDA before any technical discussion.

Evaluation-first methodology

We define what "good" looks like in measurable terms before we build anything. Accuracy is a number, not a feeling.

Post-launch optimization included

Retrieval tuning, prompt updates, model improvements, and new content ingestion. AI chatbots need ongoing attention to stay accurate.

Got questions?

Frequently asked questions

AI chatbot development — costs, timelines, channels, hallucination prevention, and integration options.

What is the difference between an AI chatbot and a rule-based chatbot?
A rule-based chatbot follows a fixed decision tree — it responds to exact keywords or button choices. An AI chatbot uses a large language model to understand natural language, handle unexpected questions, reason across context, and generate coherent responses. AI chatbots can handle open-ended conversations; rule-based bots cannot. We build AI-powered chatbots only.
How much does AI chatbot development cost?
A focused RAG chatbot for a specific knowledge base or support function costs between $15,000 and $35,000. A full multi-channel chatbot platform with CRM integration, escalation logic, analytics, and admin tooling costs $35,000 to $80,000. Enterprise chatbot systems with fine-tuned models, multi-language support, and compliance features scale higher. You receive a line-item estimate after a free scoping call.
How long does it take to build an AI chatbot?
A focused AI chatbot with a defined knowledge base and a single deployment channel takes 4 to 8 weeks. A full chatbot platform with multi-channel deployment, CRM integration, escalation workflows, and admin dashboard takes 2 to 4 months. Enterprise chatbot systems with fine-tuning and compliance requirements take 3 to 6 months.
What is RAG and why does it matter for chatbots?
Retrieval-Augmented Generation (RAG) is the architecture that lets the chatbot pull accurate information from your specific documents, knowledge base, product data, or internal systems before generating a response. Without RAG, an LLM can only answer from training data — which does not include your products, policies, or internal knowledge. With RAG, the chatbot answers accurately about your specific context. We design and build the full RAG pipeline: ingestion, chunking, embedding, vector search, retrieval tuning, and reranking.
Which channels can the chatbot be deployed on?
We build chatbots that deploy on your website, mobile app, WhatsApp, Facebook Messenger, Telegram, Slack, and Microsoft Teams. All channels connect to a single backend — context, conversation history, and escalation logic are consistent across all deployments. Adding new channels does not require rebuilding the AI layer.
Can the chatbot integrate with our CRM or support system?
Yes. We build integrations with Salesforce, HubSpot, Zoho CRM, Zendesk, Freshdesk, Intercom, and custom backends via REST API. The chatbot can read customer records, look up order status, log conversations, create tickets, and hand off to human agents with full conversation context. Integration scope is defined in writing before development begins.
How does human escalation work?
We design configurable escalation logic: the chatbot detects low-confidence responses, explicit escalation requests, repeated failed intents, or sensitive topics, and hands off to a human agent. The human receives the full conversation history. The chatbot can queue the conversation, send a notification, or redirect to a live chat platform depending on your setup.
How do you prevent hallucinations in a customer-facing chatbot?
We address hallucinations through four mechanisms: (1) RAG so the chatbot answers from verified documents instead of memory, (2) confidence thresholds so low-confidence responses trigger escalation instead of a guess, (3) response validation that checks factual claims against the source documents, and (4) automated evaluation suites that measure hallucination rate on your real question set before launch.
Can you fine-tune the model on our conversation data?
Yes. If you have historical support conversations, sales call transcripts, or chat logs, we can fine-tune a model on that data to improve tone consistency, domain terminology accuracy, and response quality for your specific use case. We evaluate whether fine-tuning outperforms prompt engineering plus RAG on your data before committing to the training cost.
Who owns the chatbot code and conversation data?
You own all code, models, conversation logs, and vector embeddings. The chatbot runs in your infrastructure, and your conversation data never trains third-party models. Full IP transfer on delivery. NDA available before any technical discussion.

Let's Talk

Ready to build a chatbot that actually answers correctly?

Tell us your use case, your knowledge base, and your channels. We will scope the project in writing, tell you exactly what it costs, and give you a timeline you can hold us to.

NDA available before any technical discussionResponse within 48 hoursFixed-fee. No hourly billing.