Conversational AI · Chat
Chat that closes tickets, not just opens them.
AI chat agents grounded in your data, for customer service, support, and product-embedded experiences. Built on AWS.
Conversational AI · Chat
WHY MOST CHATBOTS FAIL
Most chatbots increase ticket volume. They don't decrease it.
Chatbots that don't know your business
Off-the-shelf chatbots run on model knowledge that ends years before your customer's question.
Chatbots that hallucinate
Models confidently invent answers when grounding is missing. One viral screenshot costs more than the chatbot saved.
Chatbots that escalate without context
When the bot hands off, the human agent starts from zero. The customer repeats themselves and the experience is worse.
AI chat agents, engineered for the moments that matter.
AI chat agents for customer service
Customer-facing chat grounded in your help center, policies, and product data. Closes tickets end to end, escalates with full context when needed.
AI chat agents embedded in your product
Chat that lives inside your product as an SDK or component. For in-app help, AI copilots, and product-led growth features.
Internal AI chat agents for your team
Chat agents grounded in your internal docs (Confluence, Notion, Google Drive, Slack history) for onboarding, IT helpdesk, and knowledge retrieval.
HIPAA-compliant chat for regulated workflows
Chat agents for healthcare, financial services, and any workflow touching sensitive data. PHI and PII handled at the architecture level, audit trails on every conversation.
Accurate chat is engineered, not promised.
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Your data chunked, embedded, and retrieved with relevance scoring before the model sees the question.
Strict prompting, retrieval-grounded answers only, explicit "I don't know" behavior when sources don't cover the question.
When to escalate, how to escalate, and what context to pass. The chat handles the routine 80% so your team focuses on the 20%.
Production conversations sampled and reviewed weekly. Drift caught before it shows up in complaints.
AI chat agents on AWS, with open standards underneath.
Amazon Bedrock
Foundation model reasoning (Claude, Nova, Llama)
Kendra / OpenSearch
Retrieval and vector storage
MCP
Open standard for model and tool integration
AWS Lambda
Serverless integration with CRM, helpdesk, or product
Amazon Connect
Routing chat to a human agent when needed
CloudWatch + CloudTrail
Monitoring, audit, and observability
Four to six weeks, baseline to production.
Deliver
It’s not just about having the latest tech; it’s about leveraging it intelligently to maximize your cloud ROI and drive your business forward.
Deliver
It’s not just about having the latest tech; it’s about leveraging it intelligently to maximize your cloud ROI and drive your business forward.
Deliver
It’s not just about having the latest tech; it’s about leveraging it intelligently to maximize your cloud ROI and drive your business forward.
Our process follows 5 simple stages
Free consultation
30 minutes with a senior engineer who scopes your use case, data sources, and integrations.
Fixed proposal
Within five days. Fixed price, fixed timeline. No time-and-materials.
Build
Four to six weeks. Retrieval, model selection, prompt design, escalation logic, integration.
Production and tuning
Live deployment with weekly evaluation cycles, then ongoing.
AI chat agents, answered.
How does Cloudtech prevent the chatbot from hallucinating?
By treating hallucination as a system design problem, not a model problem. Cloudtech AI chat agents only answer from retrieved sources, with explicit "I don't know" behavior when sources don't cover the question. Production conversations are reviewed weekly to catch drift before it reaches customers.
What does an AI chat engagement cost?
Cloudtech AI chat engagements are fixed-price, scoped per use case after a free 30-minute consultation. Cost depends on data complexity, integrations, and deployment shape. We provide a fixed-price proposal within five days.
Can the AI chat agent integrate with my existing systems?
Yes. Cloudtech AI chat agents integrate with helpdesks (Zendesk, Intercom, Freshdesk), CRMs (Salesforce, HubSpot), knowledge bases (Confluence, Notion, Google Drive), and custom internal tools through AWS Lambda or direct API integration.
Tell us what you're trying to build.
A 30-minute consultation with a senior engineer who has shipped production AI chat agents.