Production GenAI Platform on AWS

Deploy secure, scalable AI systems using AWS-native GenAI services. RAG, agent orchestration, and guardrails: production-ready.

Overview

We design and implement production-ready GenAI systems using AWS Bedrock and related services. The result is a secure, observable AI platform that your team can maintain and extend.

Who this is for

• SaaS platforms adding AI features to their product

• Enterprise teams building internal copilots or knowledge assistants

• Companies wanting to move from prototype to production AI

Core capabilities

Retrieval-Augmented Generation (RAG)

• Vector store selection and configuration (OpenSearch, RDS pgvector, Bedrock Knowledge Bases)

• Document ingestion pipeline with chunking and embedding

• Retrieval strategy optimization for relevance and latency

• Hybrid search (vector + keyword) for improved accuracy

Model orchestration

• AWS Bedrock model selection and benchmarking for your use case

• Prompt engineering and template management

• Agent patterns with tool use (Amazon Bedrock AgentCore, with Strands, LangGraph or the Claude Agent SDK)

• Response caching strategy

Security and governance

• IAM-based access control to AI features

• PII detection and redaction in inputs/outputs

• Bedrock Guardrails for content filtering

• Audit logging of all model interactions

Observability

• Latency and cost tracking per AI operation

• Quality metrics (relevance scores, user feedback)

• Anomaly detection for model degradation

Outcomes

• Production-ready AI system on AWS

• Secure, auditable model interactions

• Cost-controlled at scale

• Team capable of extending and maintaining the platform