Customer Support Teams
Deflect repetitive tickets, summarise conversations for agents, and integrate with your helpdesk β so handoffs feel seamless to the customer.
Who we build for
Who We Build Chatbots & Voice Assistants For
Conversational AI works when it handles real customer language β not just demo scripts. We build bots that integrate with your CRM, escalate cleanly to humans, and improve every week from real conversation logs.
High-Volume Customer Businesses
Handle 24/7 engagement across web, mobile, WhatsApp, and SMS without growing your team β only routing the exceptions to humans.
Enterprise Operations
Internal assistants for HR, IT, and ops β integrated with your existing tools, governed by your policies, and improved continuously from feedback.
Sales & Lead Generation Teams
Qualify, route, and follow up on leads automatically β across channels β so your sales team only spends time on conversations that matter.
Why Chayaniq for conversational AI
Chatbot & Voice Assistant Benefits
Great conversational AI sounds like your brand, knows your product, and hands off to humans the moment it should. Here is what we deliver across chat and voice.
Multi-Channel Chatbot Development
Web widgets, WhatsApp, mobile, and SMS β one core bot with channel adapters, so behaviour stays consistent and analytics stay unified.
Voice Bot & Telephony Integration
Streaming STT and TTS connected to programmable telephony β for natural-sounding calls with low latency and clean handoffs.
Dialogflow & Custom NLU Models
Intent libraries, entity extraction, and fallback strategies β chosen for fit, with custom NLU when off-the-shelf is not enough.
Conversational Flow Design
Flows mapped to real customer language β including the messy, ambiguous edge cases β with safe escalation paths to human support.
Chatbot Analytics & Continuous Improvement
Containment, satisfaction, and escalation analytics that feed back into prompts and flows β so the bot keeps getting smarter every release.
Fallback Handling with GenAI Augmentation
When intents fail, large-language-model fallbacks step in β so users get a useful response instead of a dead end.
Industries we serve
Conversational AI for Your Industry
Conversation design changes by industry β what works for retail support fails in healthcare triage. We adapt tone, guardrails, and integrations to the vertical you operate in.
Remote patient monitoring
- Real-time collection of wearables data
- Enhanced doctor-patient communication
- Comprehensive view of patient health data
- Data-driven report generation
- Seamless integration with existing systems
- Improved patient outcomes
Electronic medical records (EMR)
- Interoperability of medical data across departments
- HIPAA / GDPR compliant solutions
- Improved patient care
- Quick access to patient records, vitals, and lab results
- Enhanced security and privacy of patient health data
Document management
- Compliant documentation workflow
- Streamlined management of health information
- Integrations with existing systems for a 360Β° data view
- Secure file sharing and access management
Insurance verification
- Automated medical insurance eligibility
- Proactive identification of coverage issues
- API-ready and HIPAA-compliant
How we work
Our Process for Chatbot & Voice Bot Delivery
From conversation design to live deployment, our process keeps real users at the centre β so the bot reaches production already aligned to how your customers actually talk.
Discovery & Intent Mapping
We map intents, business rules, and the moments where humans must take over β building a flow chart your stakeholders can sign off before code starts.
Conversation Design
Tone, persona, and dialogue trees written for the customers you actually have β including the messy phrasings, not just the demo scripts.
Build & Channel Integration
Channel adapters, NLU, and CRM hooks built around a shared core β so the bot behaves consistently across web, WhatsApp, voice, and your app.
Testing & Red-Teaming
Conversation regression suites, safety evaluation, and red-teaming β so edge cases are surfaced before customers find them.
Deployment & Phased Rollout
Phased rollouts with feature flags, agent shadowing, and live takeover β so your team builds confidence as the bot proves itself.
Optimisation
Containment, satisfaction, and escalation analytics β feeding back into prompts, flows, and training data so the bot keeps improving.
How we deploy chatbots & voice assistants
Great conversational AI combines language models with your business rules β clear intents, safe escalation paths, and analytics that show what to improve next.
We map user goals, edge cases, and handoff triggers before wiring APIs β so the bot sounds like your brand, not a generic demo.
- Intent libraries, entity extraction, and fallback strategies
- Tone and safety guidelines aligned with your policies
- Testing sets that cover real customer phrasing β not only happy paths
Our stack
Our Conversational AI Technology Stack
Modular building blocks for chatbots and voice β from NLU and orchestration to channel adapters and CRM glue, chosen for fit not fashion.
LLMs & NLU
- Anthropic Claude
- OpenAI GPT
- Dialogflow
- Rasa
- Custom NLU
Chatbot Channels
- Web widgets
- WhatsApp Business
- SMS
- Slack
- Microsoft Teams
- Mobile in-app
Voice Stack
- Deepgram
- Whisper
- ElevenLabs
- Google Speech
- Twilio / Vonage
Bot Frameworks
- Vercel AI SDK
- LangChain
- Botpress
- Microsoft Bot Framework
CRM & Helpdesk
- Salesforce
- HubSpot
- Zendesk
- Intercom
- Freshdesk
Evaluation & Analytics
- LangSmith
- Promptfoo
- Conversation analytics
- Containment dashboards
Perspectives
Ideas that pair with Conversational AI β Chatbots & Voice Assistants
Short reads from how we shipβarchitecture, product, and ops. Same themes as this service, different angles.
March 2026
Building a Chatbot That Doesn't Frustrate Users
Conversation flow design, fallback with GenAI, context management, and the metrics that matter for measuring chatbot quality.
Continue readingFebruary 2026
Voice Bots in 2026: Latency, Turn-Taking, and Telephony
Hard-won lessons on shipping voice automation that callers will tolerate β STT/TTS budgets, barge-in, and integration patterns.
Continue reading
