NVIDIA NCP-AAI case studies
NVIDIA NCP-AAI · Put your knowledge to work in context.
The NVIDIA-Certified Professional Agentic AI (NCP-AAI) is a professional-level credential in NVIDIA's certification program. NVIDIA describes it as demonstrating the ability to build and govern advanced agentic AI solutions with multi-agent interaction, scalability, and ethical safeguards. It sits alongside other professional exams such as NCP-GENL (Generative AI LLMs) and NCP-AII (AI Infrastructure), each listed at 200 with a 2-hour duration. The exam is aimed at practitioners who design, scale, and govern agentic systems rather than at candidates seeking foundational knowledge; NVIDIA's associate-level credentials (for example NCA-GENL or NCA-AMAD) cover entry-level understanding at 125 and 1 hour. The NVIDIA NCP-AAI case studies are 5 cases and about 3,915 words.
1Support triage: supervisor with typed handoffs vs. free-form agent bus
Helios Support runs a four-agent assistant for a consumer-electronics retailer: a router, a billing specialist, a returns specialist, and a policy-QA agent. Volume is 6,000 tickets per day, and the p95 time-to-first-token target is 2.5 s.
789 words, about 4 min2Document-analyst throughput: TTFT collapses past 150 concurrent sessions
Meridian's document-analyst agent answers questions over a 2.4-million-page contract corpus. Every request carries a 9,000-token system and policy prefix, roughly 3,000 tokens of retrieved context, and 2–6 tool calls.
777 words, about 4 min3Claims agent with payout authority: indirect prompt injection and unowned thresholds
Northwind Mutual deploys a claims-triage agent that reads submitted documents and can call an approve payout tool for amounts up to 25,000 with no human in the loop. It handles 12,000 claims per week.
772 words, about 4 min470B agent on 4×L40S: KV pre-allocation, INT4 regression and the concurrency target
Atlas is deploying a 70B-parameter agent model on-premises on 4×L40S (48 GB each) using TensorRT-LLM in Triton. The workload is tool-heavy: median prompt 6,000 tokens, 300-token outputs, 15-turn cap, p99 prompt-plus-output 6,900 tokens.
785 words, about 4 min5Tool-layer backpressure: 500 agents against a 100 requests/second CRM API
Vertex Ops runs up to 500 concurrent agent sessions that call a CRM REST API to read and update customer records. The contract limits the tenant to 100 requests per second overall and 20 per second on write endpoints.
792 words, about 4 min