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I will develop hipaa compliant ai backend using AWS bedrock and claude vpc endpoint ai
Daniel
Sobre este Serviço
AWS Bedrock Developer, Generative AI, LLM Integration, RAG Chatbot, Serverless Lambda Backend, Claude Foundation Model, LangChain Vector Database, Knowledge Base API, Cloud Automation Architect, NLP Claude API AI Backend Custom LLM App AWS Lambda AI Claude API Integration AI Web App AWS Healthcare AI SOC2 AI Infrastructure Secure LLM Backend HIPAA Compliant AI
Are you building an AI-powered product on AWS? I develop scalable, production-ready backends using Amazon Bedrock, Generative AI, and LLM Integration all built for speed and results.
From RAG Chatbot pipelines to serverless Lambda architectures, I turn your AI vision into a fully deployed Cloud solution using the latest Foundation Models.
Services I Offer:
- AWS Bedrock API setup & integration
- RAG Chatbot development
- LLM backend architecture
- Serverless Lambda pipeline
- Knowledge Base & Vector Database
- Bedrock Agents & Automation
- Claude Foundation Model deployment
- NLP & document processing
- API Gateway configuration
Tools I Use:
- AWS Bedrock
- LangChain
- Claude
- Lambda
- API Gateway
- OpenSearch
- Amazon S3
- DynamoDB
- Terraform
- LangGraph
ORDER NOW or CONTACT ME NOW to discuss your project to align better. Thanks
Conheça mais sobre Daniel
Daniel
Professional Website design and development
- A partir deEstados Unidos
- Membro desdemai. de 2026
- Responde em aprox.:1 hora
Idiomas
Alemão, Francês, Inglês, Espanhol
I build high-converting AI voice agent systems that automate calls, boost lead qualification, increase appointment booking, and improve customer support for modern businesses. Completed 120+ automation projects for startups, agencies, clinics, SaaS brands, and service companies worldwide. Specialized in conversational AI, AI receptionist, outbound dialing, CRM integration, workflow automation, Twilio, Vapi AI, Retell AI, ElevenLabs, and virtual assistant solutions focused on speed, scalability, accuracy, and business growth.
Perguntas frequentes
What exactly does this gig include?
This gig covers full AWS Bedrock API setup, Claude LLM integration, serverless Lambda backend, and API Gateway config. Higher packages include RAG chatbot development, Bedrock knowledge base, vector database, LangChain orchestration, Bedrock Agents, AI automation, and CloudWatch monitoring.
Can you build a RAG chatbot using AWS Bedrock?
Absolutely! I develop custom RAG chatbots on AWS Bedrock using LangChain, OpenSearch vector database, and Claude foundation model. The knowledge base RAG pipeline ingests your documents, embeds them, and retrieves precise answers via serverless Lambda and API Gateway scalable, production
How long does delivery take for each package?
Delivery depends on your chosen package. Basic AWS Bedrock API setup and Claude LLM integration ships in 3 days. Standard RAG chatbot with knowledge base and vector database takes 5 days. Premium full Bedrock Agents, production RAG pipeline
Which foundation models do you support on AWS Bedrock?
I support all major AWS Bedrock foundation models — Anthropic Claude (Sonnet and Opus), Amazon Titan, Meta Llama 4, Cohere, and AI21. Each LLM integration is tailored to your use case. Claude delivers best generative AI backend results for RAG chatbots, NLP tasks, and custom chatbot AWS solutions.
What is a serverless AI backend and do I need one?
A serverless AI backend runs your generative AI on AWS Lambda and API Gateway no servers to manage. It auto-scales, costs only what you use, and connects AWS Bedrock, LangChain, and vector database seamlessly. Perfect for startups needing fast LLM integration and your production-ready custom chat
Can you build Bedrock Agents for AI automation workflows?
Yes! I specialise in building multi-step Bedrock Agents that use foundation model reasoning to call APIs, query knowledge bases, and complete complex tasks autonomously. Deployed on AWS Bedrock Agents, Lambda, and DynamoDB your agentic AI automation handles real business workflows.
Is the LLM backend scalable and production-ready?
Every LLM backend on AWS Bedrock I deliver is production-ready from day one — serverless Lambda for auto-scaling, API Gateway for secure access, CloudWatch monitoring, and Bedrock Guardrails for safety. Your generative AI backend handles enterprise-scale requests reliably, LangChain-orchestrated
What tech stack do you use for LLM integration?
My stack: AWS Bedrock, Claude and Titan foundation models, LangChain orchestration, OpenSearch vector database, Lambda, API Gateway, DynamoDB, Amazon S3, Terraform, and CloudWatch. Every RAG chatbot, knowledge base RAG, and LLM integration is tested, documented, and production-ready.
Do you offer post-delivery support and updates?
Yes! All packages include full source code, README, and post-delivery support. For ongoing serverless AWS Bedrock maintenance, LLM integration updates, or RAG chatbot improvements, order a revision or contact me. I keep your generative AI backend, knowledge base RAG, and custom chatbot AWS deploy.
How do I get started with this gig?
Getting started is simple! Message me with your project, whether it's a RAG chatbot, LLM integration, AWS Bedrock API setup, Bedrock Agents, or a full generative AI backend. I'll review your requirements, recommend the right package, and we can hop on a call. Most orders launch within 24 hours
