Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
A cybersecurity startup building autonomous digital employees that execute complex identity and access management workflows, managing millions of identities across dozens of enterprise customers.
As the multi-agent architecture scaled, abstraction layers hid prompts, reasoning paths, and retries behind a black box. This lack of visibility...
“Datadog LLM Observability gives us complete visibility into our agents’ reasoning. We stopped guessing. We can see the prompt, the retries, the tool calls, and the cost of every step.”
AI digital employees for automated identity security and governance.
Observability and security platform for cloud-scale monitoring and analytics.
Twine Security's Model monitoring is part of this use case:
Related implementations across industries and use cases
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
A cybersecurity startup building autonomous digital employees that execute complex identity and access management workflows, managing millions of identities across dozens of enterprise customers.
As the multi-agent architecture scaled, abstraction layers hid prompts, reasoning paths, and retries behind a black box. This lack of visibility...
“Datadog LLM Observability gives us complete visibility into our agents’ reasoning. We stopped guessing. We can see the prompt, the retries, the tool calls, and the cost of every step.”
AI digital employees for automated identity security and governance.
Observability and security platform for cloud-scale monitoring and analytics.
Twine Security's Model monitoring is part of this use case:
Related implementations across industries and use cases
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.