Amazon Bedrock
For enterprises whose compliance boundary is drawn around AWS, Bedrock answers the question that kills most AI proposals in review: where does our data go? Nowhere — Claude and other frontier models run inside your AWS relationship, governed by the IAM, networking, and CloudTrail auditing your security team already operates and already trusts.
We build production systems on Bedrock, not proofs of concept: agents with governed tool access, knowledge bases wired to your S3 and databases with retrieval quality actually tuned and evaluated, guardrails configured beyond the defaults, cross-region inference for resilience, and cost management across model tiers. Where Bedrock's managed conveniences fit, we use them; where they're too rigid, we build custom on the same governed substrate — and we know where that line is.
Claude on Bedrock
Frontier-model agents inside your AWS perimeter — private endpoints, IAM governance, CloudTrail audit.
Knowledge bases done properly
Managed RAG with chunking, retrieval, and relevance tuned and eval-proven, not default-configured.
Bedrock agents and tools
Action groups wired to your APIs with least-privilege execution roles.
Guardrails and governance
Content policies, PII handling, and audit configuration mapped to your compliance requirements.
Cost and model strategy
Tier routing, prompt caching, and provisioned throughput decisions grounded in your traffic.
Bedrock or the Anthropic API directly?
Bedrock when your data-residency, procurement, and audit story lives in AWS — it inherits your existing controls, which shortens security review dramatically. Direct API when you want features on day one. Same models either way; we route by governance need, and hybrid is common.
Are Bedrock's managed features enough, or will we outgrow them?
Knowledge Bases and Agents cover a real share of use cases and cut time-to-production meaningfully. Complex orchestration, custom retrieval, and sophisticated eval loops eventually want custom code on the same substrate. We start managed where it fits and know exactly when to graduate.
Can Bedrock systems pass strict compliance review?
That's its core appeal: model calls inside your VPC via private endpoints, no training on your data, CloudTrail on every invocation, and encryption under your KMS keys. For HIPAA, PCI, and FedRAMP-adjacent environments, it's frequently the shortest path to an approved AI deployment.
Put Amazon Bedrock to work — in production.
One forward-deployed engineer, embedded in your stack, owning the outcome from discovery to production. Weeks, not quarters.
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