AI SOLUTIONS > ai-solutionStop paying people to do
Stop paying people to do
what software can do automatically.
Intelligent chatbots that handle conversations, qualify leads, and resolve support — around the clock.
THE EDITORIAL DEFINITION
Intelligence that initiates.
iSkylar builds AI-powered chatbots for websites, mobile apps, and enterprise platforms, using NLP, LLMs, and custom training on your data to create bots that understand context, escalate intelligently, and get measurably better over time. Whether you need a customer support bot, a sales qualification assistant, or an internal knowledge agent, we deliver conversational AI that works in production, not just demos.
This is for you if...
Customer Support Chatbots
AI-powered support agents that resolve common queries instantly, reduce ticket volume, and escalate complex issues to human agents with full conversation context intact — available 24/7 across web, mobile, and messaging channels.
Lead Qualification & Sales Bots
Conversational bots that engage website visitors, ask qualifying questions, score leads, and book meetings directly into your CRM or calendar — turning passive traffic into pipeline.
Internal Knowledge Assistants
Enterprise chatbots trained on your documentation, SOPs, and internal wikis — giving your team instant answers to operational questions without burdening senior staff.
Multilingual Chatbots
NLP-driven bots that detect language automatically and respond in the user's preferred language — built for businesses with global audiences or multilingual support teams.
Voice-Enabled Bots
Conversational AI that works via voice interfaces — IVR replacement, voice search, and spoken interaction for kiosks, call centres, and accessibility-first products.
Chatbot Integration & CRM Connectivity
We connect your chatbot to Salesforce, HubSpot, Zendesk, Intercom, WhatsApp Business, Slack, and custom APIs — so conversations flow into your existing tools without manual handoff.
The Implementation Roadmap
01
Discovery & Bot Design
We map your use cases, define conversation flows, identify escalation triggers, and agree on the channels and integrations before any development begins.
TIMELINE
1–2 weeks
02
NLP & Training Data Preparation
We prepare intent libraries, entity definitions, and training utterances — or connect your existing documentation to a RAG pipeline for knowledge-grounded responses.
TIMELINE
1–2 weeks
03
Development & Integration
Bot logic built, CRM and channel integrations connected, fallback handling designed, and a staging environment available for you to test real conversations throughout.
TIMELINE
3–8 weeks
04
QA & Conversation Testing
We run dialogue testing across hundreds of scenarios — edge cases, ambiguous inputs, multi-turn conversations, and language variations — until accuracy meets agreed benchmarks.
TIMELINE
1–2 weeks
05
Launch & Monitoring Setup
Production deployment across your channels, conversation analytics dashboard live, escalation routing confirmed, and your team trained on the management console.
TIMELINE
3–5 days
06
Optimisation & Ongoing Support
We monitor conversation metrics, retrain on failed interactions, expand intent coverage, and iterate on flows as your users' needs evolve.
TIMELINE
Ongoing
THE ARCHITECT'S TOOLKIT
Python
OpenAI API
Anthropic Claude API
LangChain
Rasa
Dialogflow CX
Twilio
WhatsApp Business API
Pinecone (vector DB)
FastAPI
React (chat UI)
Node.js
Firebase
AWS Lambda
Sentry
Frequently Asked Questions
What is the difference between a rule-based chatbot and an AI chatbot?
Rule-based chatbots follow fixed decision trees — they only respond to exact triggers you have pre-programmed. AI chatbots use NLP and machine learning to understand intent from natural language, handle variations, and learn from conversations over time. We build AI-native bots, not flowchart wrappers.
What platforms can the chatbot be deployed on?
Web (embedded chat widget), mobile apps (iOS and Android SDK), WhatsApp Business, Facebook Messenger, Slack, Microsoft Teams, and custom API integrations. We deploy to as many channels as your use case requires from a single bot backend.
How do you train the chatbot on our specific business knowledge?
We use RAG (Retrieval-Augmented Generation) to connect the bot to your documentation, FAQs, and knowledge bases — so answers are grounded in your content, not hallucinated. For structured use cases, we also build custom intent libraries from your historical support data.
How long does chatbot development take?
A focused pilot bot is typically 4–6 weeks. A full multi-intent, multi-channel system with CRM integration is usually 10–16 weeks. We provide a timeline after scoping your specific use case.
What does AI chatbot development cost?
Pilot bots start from $5,000. Full systems from $18,000. Pricing depends on the number of intents, channels, and integrations required. Fixed-scope quote before signing.
Will the chatbot improve over time?
Yes. We set up conversation analytics and flag low-confidence responses for review. On retainer engagements, we run monthly retraining cycles so the bot's accuracy improves as it encounters real user inputs.
Who owns the chatbot and its training data?
You do. All bot configuration, training data, conversation logs, and integration code are fully transferred at project close. We retain no rights.
Do you integrate with our existing CRM or helpdesk?
Yes. We regularly integrate with Salesforce, HubSpot, Zendesk, Intercom, Freshdesk, and custom ticketing systems — connecting conversation handoffs, lead records, and support tickets automatically.
