Artificial Intelligence | Monitoring & Observability

AI Monitoring

Monitor drift, hallucinations, costs, and security of your AI systems in real time: prodot builds your AI monitoring dashboard—with an audit trail for the EU AI Act, coverage of the OWASP LLM Top 10, and ISO 42001-compliant documentation.

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✓ 80+ AI experts ✓ 25+ years of technology expertise ✓ ISO-certified ✓ Made in Germany

Why Traditional IT Monitoring Isn't Enough for AI

51 percent of companies that use AI in production have already experienced negative consequences—most commonly due to hallucinations and model inaccuracies (McKinsey State of AI 2025). Industry analyses estimate the global cost of AI hallucinations at around $67 billion annually; verification efforts alone result in over four hours of overhead per employee per week.

At the same time, AI pilot projects are abandoned at an above-average rate: 46 percent of proof-of-concepts will not reach production by 2025 because drift, cost spikes, or security incidents are detected too late. Traditional APM tools measure latency and HTTP status—but they do not measure whether an LLM is currently hallucinating, whether an agent has fallen victim to prompt injection, or whether a model update from OpenAI or Anthropic is silently degrading your responses.

AI monitoring is therefore a distinct observability discipline. It measures drift, factual accuracy, token consumption per use case, prompt injection attempts, bias indicators, and audit trail completeness. The EU AI Act requires at least six months of logging for high-risk systems, while ISO/IEC 42001 mandates a documented management system. Anyone going live without this discipline accepts risks that aren’t visible in traditional IT risk frameworks.

prodot builds your AI monitoring—regardless of whether you operate the system yourself or use a managed service. We give you the cockpit, not the black box.

Observability Instead of a Black Box

You can see what your AI is doing, why it’s doing it, and what it costs. prodot builds monitoring dashboards with measurable quality scores for each use case—even if operations are handled internally or by a third-party provider. No lock-in, full transparency.

EU AI Act, OWASP, and ISO 42001

Audit trail with a minimum of six months of logging, EU AI Act risk classification by use case, OWASP Top 10 coverage for LLMs, and ISO/IEC 42001-compliant documentation. Compliance is measured, not just promised.

25 Years of Operational Experience

prodot has been operating mission-critical software for over two decades—for mid-sized companies and large enterprises in the mechanical engineering, insurance, energy, and logistics sectors. AI is a new class of workload, but the observability principles behind it are well-established.

Drift and Quality Tracking

Goldsets, the LLM-as-Judge method, and embedding drift indicators detect when model updates change your responses. You can see quality trends for each use case over the course of weeks—instead of waiting until an escalation ticket is filed to react.

Hallucination and Factual Accuracy Scoring

Grounding checks against RAG sources, citation validation, and automated factual accuracy assessment. Hallucinations are detected—not just identified by the end user—including analysis by use case and model version.

Prompt Injection & Security Monitoring

Detection of prompt injection, jailbreak attempts, data leakage, and excessive agency patterns in accordance with the OWASP Top 10 for LLM Applications 2025. Output filters, alerting, and incident trails are integrated into your security operations.

Cost and Performance Telemetry

Token consumption per use case, model, and employee—with trend visibility and budget alerts. Model routing recommendations reduce costs without compromising output quality. You control AI costs instead of being at their mercy.

EU AI Act & ISO 42001 Audit Trail

Structured audit trail with a retention period of at least six months, risk classification by use case, Fundamental Rights Impact Assessment, and ISO 42001-compliant management system documentation. Compliance is auditable, not just claimed.

Integration into Your Observability Stack

Integration with Datadog, Grafana, Splunk, or Microsoft Sentinel—instead of using separate tools. AI metrics end up right where your SRE and security teams are already working. We integrate tools like Langfuse, Arize Phoenix, or W&B Weave wherever it makes sense.

What AI Monitoring Actually Does

Identify risks before damage occurs: Drift, hallucinations, and security incidents become visible before they escalate to the customer or the board of directors.
Keepingcosts under control: Token telemetry and model routing prevent AI operating costs from increasing unnoticed by a factor of several—you take control instead of just paying the bill.
EU AI Act compliance: Six-month logging, risk classification, and documentation are generated as byproducts of monitoring—not during frantic audit weeks.
Model updates without surprises: Regression tests automatically trigger when vendor updates degrade your responses—before production users notice.
No tool silos: Integration with your existing observability stack—your SRE and security teams don’t need a second set of tools.

prodot Business Intelligence Consulting for Businesses

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Your contact person

Daniel Ludewig

sales@prodot.de

0203 3965080

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Questions & Answers

What is the difference between traditional APM and AI-powered monitoring?

APM tools like Datadog or New Relic measure latency, HTTP status, and infrastructure health—they’re indispensable, but not sufficient for AI systems. AI monitoring also measures semantic quality: hallucinations, drift against gold sets, factual accuracy against RAG sources, prompt injection attempts, token consumption per use case, and EU AI Act logging requirements. prodot integrates AI metrics into your existing APM stack upon request—instead of building a parallel ecosystem of tools.
Do we have to run the AI on prodot to use monitoring?
How does prodot address the EU AI Act in its monitoring?

We classify each use case according to the EU AI Act risk class and determine the corresponding logging and documentation requirements. For high-risk systems, we establish the required audit trail with a retention period of at least six months, a Fundamental Rights Impact Assessment (FRIA), and post-market monitoring. In addition, we can implement an ISO 42001-compliant AI management system that structures the requirements for governance, risk, and continuous improvement.
What tools does prodot use for AI monitoring?

We take a technology-agnostic approach: We use open-source tools such as Langfuse, Arize Phoenix, and Weights & Biases Weave, as well as commercial platforms (Arize AX, Portkey, IBM Instana GenAI Observability). For integration into existing stacks, we use Datadog, Grafana, Splunk, or Microsoft Sentinel. The choice of tools is based on your compliance and hosting requirements—not on any vendor loyalty on our part.
How much does AI monitoring cost?

A compact monitoring setup for one to two production use cases starts at around 15,000 to 30,000 euros for the initial setup. Ongoing operations (including dashboards, alerts, monthly quality reports, and audit trail maintenance) range from 2,000 to 5,000 euros per month—depending on the number of use cases, logging volume, and level of compliance. We work with fixed packages per tier—no open hourly rates that increase with every incident.

prodot | AI service provider based in Duisburg

Who We Are

prodot combines over 25 years of software excellence with artificial intelligence—from consulting to productive AI solutions for medium-sized companies. Everything from a single source.

As an AI and software service provider, we bring AI into your business in a productive way. Our team of over 80 experts at our Duisburg location and throughout Germany makes this possible.

We place special emphasis on secure and responsible AI solutions that deliver long-term value for you. Our ISO certifications also attest to this quality and attention to detail.

AI Monitoring

Why Traditional IT Monitoring Isn't Enough for AI

prodot – AI Monitoring as a Discipline in Its Own Right