LLM and AI Observability on AWS
Inetum · Cybersecurity & IT
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
**Inetum delivers an end-to-end consulting offering to observe, secure, and scale LLM and AI systems on AWS.**
By combining Dynatrace observability with AWS-native services, we provide full transparency across AI models, agents, data pipelines, and applications.
Show the rest of the publisher’s description (22 more lines)
Our approach enables organizations to control AI performance, costs, risks, and compliance, transforming AI into a reliable and business-critical capability.
**The offer enables :**
- **End-to-end observability for AI and LLM workloads on AWS**, from prompts and agents to applications and cloud infrastructure ;
- **Performance and reliability monitoring**, including latency, errors, saturation, and bottlenecks across RAG pipelines, multi model chains, and agentic architectures ;
- **AI cost governance**, with detailed tracking of token consumption, cost per request, per model, and per application ;
- **Model and data drift detection**, ensuring long-term accuracy, quality, and trust ;
- **Security, compliance, and guardrail monitoring**, including full traceability of AI requests in regulated environments ;
- **Cloud and model provider flexibility**, avoiding lock in while remaining fully compatible with AWS native services ;
- **Operational excellence**, enabling rapid incident detection, root cause analysis, and continuous optimization.
**Benefits :**
- Accelerate AI industrialization on AWS: Move from POCs to production grade, fully observable AI deployments with confidence ;
- Control and optimize AI costs: Improve visibility and financial governance across LLM usage patterns ;
- Deliver high performance and reliable AI services: Maintain fast, resilient, and high quality user experiences across business critical workflows ;
- Reduce operational and business risk: Detect performance issues, drift, or anomalies before they impact production ;
- Strengthen AI security and compliance: Ensure safe, auditable, and regulatory aligned AI operations on AWS ;
- Support informed executive decisions: Provide clear metrics to evaluate AI value, risk, and business impact.
**For who ?**
- Large Enterprises and Mid Sized Companies deploying AI / LLM use cases ;
- Organizations running AI or LLM workloads on AWS ;
- Highly regulated industries requiring security, auditability, and compliance ;
- Enterprises requiring cost governance for LLM usage ;
- Companies building AI driven customer or internal services.
Highlights
Highlighted by the publisher on AWS Marketplace.
1. End to end observability for AI and LLM workloads on AWS Full visibility into model performance, latency, token usage, and drift across Amazon Bedrock, SageMaker, EKS/ECS, Lambda, and EC2 environments.
2. Faster industrialization of GenAI use cases on AWS Accelerate the move from POCs to production with standardized dashboards, intelligent alerts, drift detection, and enterprise grade operational excellence.
3. AI cost, performance, and risk governance powered by AWS and Dynatrace Real time monitoring of consumption, security guardrails, compliance, and incident root cause analysis using AWS native services combined with Dynatrace LLM Observability.
Agent build and provenance
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