All solutions
LLM Observability & Evals

LLM Observability & Evaluation on AWS

See what your AI features actually do: every prompt, response, cost and latency traced, and evaluations that tell you whether a change made things better or worse. Running in your own AWS account.

2–4 weeks

$12k–$30k

Overview

Once an AI feature is live, three questions arrive together: what did the model see and say, is it getting better or worse, and what is it costing. We set up the tracing, evaluation and cost accounting that answers all three — in your own AWS account by default, because an observability store holds every prompt your users ever typed.

Who this is for

  • Teams with an LLM feature in production and no visibility into its quality or cost

  • Teams on Helicone, which stopped taking new customers in 2026, who need somewhere to move

  • Companies that need prompts and completions to stay inside their own AWS account

  • Teams about to scale an AI feature and wanting to catch regressions before customers do

What we implement

Tracing

  • OpenTelemetry instrumentation across your services, with traces for every model call, tool call and retrieval step

  • Integration with Amazon Bedrock and Bedrock AgentCore, LangChain/LangGraph, LlamaIndex, Strands or plain SDK calls

  • PII handling decided up front: redaction, sampling and retention set to match your obligations

Evaluation

  • Golden datasets drawn from real traffic

  • LLM-as-judge and rule-based scorers for the qualities you care about

  • Evaluations run in CI, so a prompt or model change that makes things worse fails the build

Cost and performance

  • Token cost and latency by feature, customer and model

  • Alerts on cost spikes and latency regressions

The platform

  • Self-hosted Langfuse on ECS Fargate with RDS PostgreSQL, ClickHouse, ElastiCache and S3 — private networking, SSO, backups — or Langfuse Cloud if you'd rather not run it

  • Infrastructure as code (CDK or Terraform), runbooks, and a handover session for your team

Deliverables

  • Working tracing across your AI features

  • An evaluation suite running in CI

  • Cost and latency dashboards with alerts

  • IaC for the whole platform, and runbooks

Frequently Asked Questions

Ready to get started?

Tell us about your current environment and goals. We'll review the details and respond with a proposed engagement structure and timeline.

Typical response time: 1–2 business days.

Prices and timelines are estimates for typical engagements, not offers. Scope, price and terms are set in a written agreement after we understand your situation. Terms of use.