AI costs visible only in aggregate—regressions lurked for 24 hours. Observability cut detection to under an hour, saving $280K annually.
An AI-native security operations platform that ingests telemetry from more than 100 data sources, processing roughly 15 petabytes of customer data daily to automate threat detection, investigation, and response for enterprise customers.
With AI powering every investigation workflow, from enrichment and classification to reasoning and report generation, LLM costs grew rapidly...
“We treat AI agent costs and performance like any other production signal: instrumented, alerted, and continuously reviewed. Datadog gives us the visibility to operate AI systems efficiently at scale.”
AI-native protection platform for security operations and automated threat detection.
Observability and security platform for cloud-scale monitoring and analytics.
Artemis's Cost monitoring is part of this use case:
Related implementations across industries and use cases
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Keyword bots bottlenecked 100 agents supporting millions. Now, AI resolves FAQs, freeing staff to mine chat logs for product feedback.
Querying Wikidata required specialized syntax, locking out most AI systems. Vector search now lets LLMs navigate 100M+ entities in plain language.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
AI costs visible only in aggregate—regressions lurked for 24 hours. Observability cut detection to under an hour, saving $280K annually.
An AI-native security operations platform that ingests telemetry from more than 100 data sources, processing roughly 15 petabytes of customer data daily to automate threat detection, investigation, and response for enterprise customers.
With AI powering every investigation workflow, from enrichment and classification to reasoning and report generation, LLM costs grew rapidly...
“We treat AI agent costs and performance like any other production signal: instrumented, alerted, and continuously reviewed. Datadog gives us the visibility to operate AI systems efficiently at scale.”
AI-native protection platform for security operations and automated threat detection.
Observability and security platform for cloud-scale monitoring and analytics.
Artemis's Cost monitoring is part of this use case:
Related implementations across industries and use cases
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Keyword bots bottlenecked 100 agents supporting millions. Now, AI resolves FAQs, freeing staff to mine chat logs for product feedback.
Querying Wikidata required specialized syntax, locking out most AI systems. Vector search now lets LLMs navigate 100M+ entities in plain language.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.