Multicloud AI & ERP / Cloud AI Applications & Industry AI Solutions
Why it matters
Rule-based bots frustrate users when questions stray off script, while purely generative bots can be unpredictable for transactions. A hybrid design gives reliable transactions and helpful answers.
How it works
A hybrid conversation
A message arrives on a channel. The bot understands intent: a known task goes to a fixed flow with validation and back-end calls, while an open question goes to a generative answer grounded in your knowledge. When neither works, it escalates to a person with context.
AWS, Azure and Google Cloud compared
| AWS | Azure | Google Cloud | |
|---|---|---|---|
| Bot platform | Amazon Lex | Copilot Studio, Azure Bot Service | Dialogflow CX, Conversational Agents |
| Generative answers | Lex QnAIntent with Bedrock | Generative answers in Copilot Studio | Playbooks and data store agents |
| Back-end actions | Lambda fulfillment | Power Automate, connectors | Webhooks |
| Channels | Connect, web, Slack | Teams, web, WhatsApp | Web, telephony, messaging |
| Human handoff | Amazon Connect | Omnichannel for Customer Service | Contact center integration |
What makes each cloud different
AWS
Amazon Lex manages intents and slots with LLM-assisted slot filling, QnAIntent answers from Bedrock knowledge bases and Amazon Connect provides live-agent handoff.
Azure
Copilot Studio builds agents with topics, actions and generative answers across Teams, web and WhatsApp; Azure Bot Service remains for code-first bots.
Google Cloud
Dialogflow CX models conversations as state machines, and playbooks add generative agents with instructions inside Google's Conversational Agents.
Design decisions that matter
- 01Fixed flows for transactions
Predictable and validated.
- 02Generative answers for questions
Grounded in your content.
- 03Easy escalation
Always a path to a person.
- 04Review conversations
Improve flows from real logs.
Common mistakes we see
- Rule-only bots. Dead ends on unexpected questions.
- Generative-only transactions. Unreliable for payments or changes.
- Hiding the human option. Frustration and churn.
A practical 30-day plan
- Week 1
List the top intents and open questions.
- Week 2
Build flows for the top transactions.
- Week 3
Add grounded generative answers.
- Week 4
Connect handoff and review real conversations.
How NTS helps
NTS builds conversational AI with Lex, Copilot Studio and Dialogflow, combining reliable transaction flows with grounded generative answers and smooth handoff to people.
What you get
- Chatbots and voice bots built on modern AI
- Integration with your systems and data
- Human handoff with full context
- Conversation analytics
Typical outcomes
- More customer requests resolved instantly
- Lower support costs
- Higher customer satisfaction
How we work with you
- 1Assess
A focused review of your conversational AI across AWS, Azure and Google Cloud. We look for the gaps we find most often: rule-only bots, generative-only transactions and hiding the human option.
- 2Design
A target architecture and roadmap built on the decisions that matter most: fixed flows for transactions, generative answers for questions, easy escalation and review conversations.
- 3Build
Hands-on delivery alongside your team. We list the top intents and open questions, build flows for the top transactions, add grounded generative answers, and finally connect handoff and review real conversations.
- 4Run and improve
We analyze conversations, improve flows and add new capabilities over time.
Why teams choose NTS for conversational AI
- Natural conversations
Modern AI understands customers, not just keywords.
- Connected to your business
Bots complete real tasks, not just answer FAQs.
- Customer experience first
Smooth handoffs prevent frustration.
Book a free 30-minute review
Talk to an NTS architect about your conversational AI on AWS, Azure and Google Cloud.