Secure Enterprise Generative AI

AWS Bedrock Integration Services

Deploy Secure Enterprise RAG architectures using **AWS Bedrock, Anthropic Claude, Titan**, and serverless AI infrastructure entirely within your AWS VPC. Zero data leaves your environment.

Deploy Secure AI on AWS
AWS VPC AI Deployments

Zero-Trust Data Privacy

With AWS Bedrock, your enterprise Generative AI workflows are isolated inside your AWS VPC endpoints. Your proprietary data never leaves your environment and is never used to train foundational models. We architect complete solutions ensuring strict data privacy and compliance.

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Knowledge Bases for Amazon Bedrock

Connect securely to your S3 buckets, Confluence, and databases to power highly accurate Retrieval-Augmented Generation (RAG) pipelines.

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Anthropic Claude & Amazon Titan

Leverage industry-leading foundational models optimized for enterprise reasoning, summarization, and multi-agent workflows.

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Multi-Agent Orchestration

We design autonomous multi-agent systems via our Generative AI development services that reliably execute multi-step workflows within your VPC boundaries.

AWS Bedrock VPC deployment architecture
Serverless AI Infrastructure

OpenSearch Serverless & Vector Engines

Amazon OpenSearch Serverless

Highly scalable, zero-management vector engine native to AWS. Perfect for enterprise RAG implementations without the infrastructure overhead.

Serverless Vector Engine

Pinecone & Managed Vectors

Integrate Bedrock with third-party managed vector databases like Pinecone through secure AWS PrivateLink configurations.

AWS PrivateLink

Amazon RDS & PGVector

Store vector embeddings directly inside your existing Amazon RDS PostgreSQL deployments for unified data management.

Native SQL Vector Search
Platform Evaluation

Enterprise Cloud LLM Platforms: AWS Bedrock vs. Azure OpenAI vs. Google Vertex AI

Compare foundation model diversity, data governance, private VPC endpoints, agentic tooling, and enterprise integration capabilities.

Platform Attribute AWS Bedrock Azure OpenAI Service Google Vertex AI
Model Catalog Diversity Multi-vendor: Anthropic Claude 3.5, Meta Llama 3.3, Mistral Large, Amazon Titan, AI21. Exclusively OpenAI frontier models (GPT-4o, o1, o3-mini) plus select open catalog models. Google Gemini 1.5/2.0 series, Gemma open models, plus curated third-party models in Model Garden.
Data Privacy & Isolation Zero customer data used for model training; private VPC endpoints (AWS PrivateLink) keep traffic internal. Enterprise BAA; customer data isolated within tenant subscription; optional abuse logging exemption. Customer data isolated in Google Cloud project boundary; VPC Service Controls enforced.
Agentic Orchestration Bedrock Agents (orchestrates action groups, OpenAPI schemas, and integrated Knowledge Bases). Azure AI Agent Service, Semantic Kernel, and native AutoGen / LangChain connectors. Vertex AI Reasoning Engine, integrated Google Search grounding, and LangGraph support.
Native RAG & Vector Storage Bedrock Knowledge Bases (automatic ingestion into OpenSearch Serverless, Pinecone, or Aurora). Azure AI Search (hybrid BM25 + dense vectors + semantic re-ranking) natively integrated. Vertex AI Search (Google-grade search indexing, semantic retrieval, and vector search).
Model Customization Fine-tuning supported for Llama, Titan, and Cohere; continued pre-training on custom corpora. Fine-tuning available for GPT-4o-mini and select models with curated JSONL training datasets. Supervised fine-tuning and RLHF available for Gemini models via Vertex AI Model Garden.
Ecosystem Fit Enterprises with infrastructure primarily on AWS (S3, Lambda, RDS, IAM, SageMaker). Organizations invested in Microsoft 365, Copilot Studio, Active Directory, and Azure. Teams leveraging BigQuery, Google Kubernetes Engine (GKE), Google Workspace, and Android.
Technical Details

Frequently Asked Questions

How does AWS Bedrock guarantee enterprise data privacy?

AWS Bedrock operates entirely within your AWS environment using VPC endpoints. Your proprietary data is never used to train base foundation models, and all interactions remain strictly within your private network boundaries.

What vector engines do you use for AWS Bedrock RAG?

We primarily leverage Amazon OpenSearch Serverless as the highly scalable vector engine, integrated seamlessly with Knowledge Bases for Amazon Bedrock to provide accurate, anti-hallucination document retrieval.

Can you build multi-agent workflows using AWS Bedrock?

Yes, we architect multi-agent workflows utilizing Anthropic Claude and Amazon Titan on Bedrock, orchestrating complex enterprise tasks across internal APIs, databases, and document repositories securely.

Interactive Architecture Tools

Not Sure Which AI Architecture Fits Your Budget?

Use our interactive LLM Selector and AI Chatbot Cost Calculator to get a tailored architecture estimate based on your specific security, token volume, and deployment requirements.

Estimate My Chatbot Cost Launch LLM Selector Wizard

Build Secure AI on AWS

Deploy enterprise-grade Generative AI without compromising your data privacy or security boundaries.

Discuss Your AWS Architecture
Skip the Sales Reps

Talk Directly to an AWS Bedrock Architect

Book a zero-pitch, 20-minute engineering session to evaluate your dataset readiness, scope AWS VPC deployments, map Knowledge Bases for Bedrock, or calculate Claude & Titan inference costs.

Direct Engineer Scoping

Book a 20-Min Technical Strategy Call

Discuss your architecture, feasibility, hardware sizing, or custom software requirements directly with a senior engineer.

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