IBM A1000-137 Advanced Practice Exam: Hard Questions 2025

A bank is designing a virtual agent for loan servicing. Requirements: (1) meet strict latency SLOs for 95th percentile during peak hours, (2) minimize hallucinated or non-compliant responses, (3) allow rapid updates to policy/FAQ content without retraining, and (4) provide an audit trail of which source passages grounded each answer. Which architecture best meets these requirements?

A retailer is deploying a multi-channel assistant (web chat + voice). Web must support rich product comparisons; voice must keep turns short. The team wants a single orchestration layer but different response strategies per channel. They also need to capture conversation state consistently while allowing channel-specific NLU confidence thresholds. Which design is the best fit?

A healthcare provider must design an assistant that can answer benefits questions while meeting privacy requirements. PHI must not be sent to external services. The assistant should still leverage enterprise knowledge sources and allow agent handoff with full context. Which approach best satisfies these constraints?

A team uses Watson Assistant with search integration. In production, the assistant frequently returns "I couldn’t find an answer" for queries that are known to be present in the knowledge base. Logs show high search hit counts, but the final response is empty. Which is the most likely root cause and best corrective action?

An enterprise exposes a chat endpoint for multiple business units. They must enforce tenant isolation, support per-tenant rate limits, and ensure that one tenant cannot access another tenant’s logs or conversation transcripts. Which API and operational pattern best achieves this?

A developer integrates a Watson NLP service and observes intermittent 429 responses and occasional timeouts during load tests. The service team says capacity is sufficient and recommends client-side changes. What is the best remediation strategy to improve resiliency and throughput without violating service limits?

A team is training a classifier for customer email routing. They have 200k labeled emails, but label quality varies by region and the dataset is highly imbalanced (one class is 45% of all samples; several classes are under 1%). In pilot, overall accuracy is high but minority classes fail badly. Which evaluation and training strategy is most appropriate?

You are preparing documents for an enterprise RAG system. The corpus includes PDFs with tables, policies with frequent updates, and long technical manuals. The initial prototype shows correct retrieval but poor answer quality due to missing context and broken table content. What is the best data preparation approach?

After deploying an assistant, the team notices a steady drop in containment rate and an increase in "no match" events, but only for users in one geography. The NLU model was unchanged. Which is the most plausible root cause and the best next diagnostic step?

A production assistant must be updated frequently. The team wants to reduce deployment risk and ensure quick rollback if a new release increases errors. They also must preserve conversation continuity for in-flight sessions during deployments. Which deployment strategy best satisfies these goals?