AWS Bedrock infrastructure that scales to production
AWS-certified engineers deploying RAG architectures, serverless inference and foundation models in production. The right model for each workload — Claude, Llama, Titan.
AWS Bedrock gives you access to the best foundation models through a single, enterprise-grade API. But managed infrastructure does not automatically mean production-ready architecture. We have designed RAG systems for clients with millions of documents, built serverless inference pipelines that handle traffic spikes without cold start penalties, and optimized inference costs by 40–60% through model selection and caching strategies.
Four AWS certifications — including Machine Learning Specialty — are the baseline, not the differentiator. The differentiator is we have shipped systems in production that clients still run years later.
What is AWS Bedrock?
AWS Bedrock is Amazon's managed service for accessing foundation models (Claude, Llama, Titan, Mistral, Stable Diffusion) through a single API without managing underlying infrastructure. It includes Knowledge Bases for RAG with automatic vector indexing, Agents for multi-step autonomous workflows, Guardrails for content safety, and native integration with the entire AWS ecosystem (Lambda, S3, CloudWatch). In Adoredev we use Bedrock as the inference backbone for every AI system we build — because it offers enterprise SLAs, compliance controls and the operational predictability that production systems require.
What we build on AWS Bedrock
Production-grade AI systems on the only infrastructure we trust
RAG Architectures
Knowledge BasesRetrieval-Augmented Generation pipelines connected to your internal documentation, databases and proprietary data sources.
Learn moreBedrock Agents
Multi-step WorkflowsAutonomous agents with tool-calling, action groups and integration with your business APIs — fully managed on AWS.
Learn moreServerless Inference
Lambda + API GatewayScalable inference endpoints with automatic scaling, no idle costs and sub-50ms cold start optimization.
Learn moreFine-tuning & Evaluation
Model OptimizationSupervised fine-tuning of foundation models on your domain data. Systematic evaluation with custom benchmarks.
Learn moreGuardrails & Compliance
SafetyContent safety filters, PII detection and topic blocking configured for your industry requirements and regulatory constraints.
Learn moreCost & Monitoring
CloudWatchInference cost dashboards, latency alerts and token budget controls so you never get a surprise bill.
Learn moreManaged Service ≠ Production-Ready
The biggest misconception about AWS Bedrock: because Amazon manages the infrastructure, the architecture takes care of itself. It doesn't. RAG precision degrades with poor chunking strategies. Inference costs explode without token budgets. Agents fail silently without proper error handling. We have seen $40K/month inference bills from systems that could have cost $2K with the right architecture. Our job is to build systems that are not just functional — but efficient, observable and maintainable in production.
Good fit
- Companies already invested in the AWS ecosystem (IAM, S3, VPC)
- AI projects requiring enterprise SLAs and compliance controls
- Teams needing multiple foundation models from a single managed API
- Organizations with 10K+ documents to index and retrieve
Not a good fit
- Projects that explicitly require on-premise, non-AWS infrastructure
- Simple single-model integrations with no RAG or multi-step requirements
- Budgets under $500/month for infrastructure (setup overhead not worth it)
- Teams without an AWS account or permission to create cloud resources
Our AWS Bedrock methodology
From architecture design to production in 8 weeks
Architecture Design
We map your data sources, access patterns and compliance requirements to a Bedrock architecture. Model selection, chunking strategy and vector index design before any code.
Proof of Concept
Working RAG or agent PoC against your real data. We measure precision, latency and estimated inference cost before committing to the full build.
Production Build
Serverless infrastructure with IAM least-privilege, Guardrails configuration, cost budgets and CloudWatch dashboards for every critical metric.
Handoff & Monitoring
Runbook documentation, alert configuration and a live monitoring dashboard your team can operate independently. AWS cost optimization review included.
Frequently asked questions about AWS Bedrock
Answers to the most common questions about building with Bedrock in production
For most enterprise use cases: Claude 3.5 Sonnet for knowledge retrieval and reasoning, Claude 3 Haiku for high-volume tasks where cost matters, and Titan Embeddings for vector search. We never recommend a model without benchmarking it against your specific data and use case — the best model is the one that hits your precision and cost targets.
Bedrock charges per million input/output tokens. Costs vary significantly by model: Claude Haiku is ~$0.25/M input tokens, Claude Sonnet ~$3/M. For a typical internal knowledge agent with 50 users making 20 queries/day, expect $50–$300/month depending on model choice and average document size. We include detailed cost projections in every proposal.
Yes — Bedrock is a native AWS service with full integration to IAM, VPC, S3, Lambda, SQS, Step Functions and CloudWatch. If you are already in AWS, Bedrock fits into your existing security perimeter and billing model without new vendor relationships.
No. AWS explicitly states that data processed through Bedrock API calls is not used to train foundation models. Your data stays within your AWS account boundary. For additional compliance requirements (HIPAA, SOC 2, GDPR), Bedrock supports Business Associate Agreements and operates in multiple AWS regions with data residency controls.
A focused RAG system with one data source typically takes 4–6 weeks from architecture to production. A Bedrock Agent with multiple action groups and external API integrations takes 8–12 weeks. We scope projects based on data complexity, not model capability — the models are ready; it is the data pipeline that takes the most time.
Free AWS Bedrock architecture review.
We assess your use case and recommend the right Bedrock architecture. No commitment.
We map your data sources and requirements to a production-grade Bedrock architecture with cost projections.
Talk to an architect