Generative AI Solutions

Amazon Bedrock provides managed access to leading foundation models (Claude, Titan, Llama) with built-in security features — VPC endpoints, KMS encryption, no model training on your data, and Guardrails for content filtering. For regulated industries, Bedrock's compliance posture (HIPAA, SOC 2, ISO 27001) is often the deciding factor.

Retrieval-Augmented Generation (RAG) combines a foundation model with your own data. Instead of fine-tuning, RAG retrieves relevant documents from a vector store and includes them in the model's context. Use RAG when you need AI that answers questions about your proprietary data — documentation, policies, product catalogs — without retraining a model.

We use a layered approach: VPC endpoints to keep traffic off the public internet, KMS encryption for data at rest and in transit, Bedrock Guardrails for PII/PHI filtering, IAM boundary policies to prevent cross-zone data access, and CloudTrail audit logging for every inference call. For healthcare workloads, we implement structural safeguards that make PHI exposure architecturally impossible.

AWS inference costs for production generative AI are typically $200–$3,000/month depending on volume and model selection. Our case studies show ROI ranging from 3.9x to 108x. Total project costs depend on complexity, integrations, and compliance requirements — contact us for a scoped estimate based on your use case.