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If your agent returns zero memories for a new vendor, that result does not identify the cause by itself. The record may not have been saved or indexed, the query may be using a different scope or restrictive filters, retrieval may not have run, or the agent may have retrieved the memory but failed to use it in its answer. Trace the path in order: ingestion → storage and indexing → scope and filters → retrieval trace → agent response. Without the backend, configuration, vendor identifier, and runtime trace, there is no reliable way to name the specific fault.
First determine where the vendor memory disappears
Use the earliest point in the pipeline where the vendor record cannot be found to focus the investigation. A successful import or an agent response alone is not enough to establish that every stage worked: some systems skip invalid records, and a response that says “no memory” does not prove the retrieval system returned no records.
- Check the submitted record. Inspect the source conversation, event, or record sent to memory. Confirm that it includes the vendor’s exact name, relevant aliases, and—if available—a stable identifier such as a domain or vendor ID. If the platform extracts memories or metadata from conversations, check that its extraction strategy and metadata schema are configured. In Amazon Bedrock AgentCore Memory, a strategy without a metadata schema does not perform schema-based metadata extraction: AgentCore Memory metadata.
- Verify the write and indexing results. Inspect ingestion or import job status, indexing completion, validation errors, and any error sink. Salesforce recommends checking index-job completion and comparing source-record counts with indexed records: Salesforce Agentforce RAG troubleshooting. Google Agent Retrieval can send malformed imported records to an error sink while processing other records, so a completed import does not necessarily mean every record was stored: Google Agent Retrieval troubleshooting.
- Confirm the query’s scope. Check that retrieval uses the same user, client, tenant, namespace, or other scope used when the memory was written. Resolve any namespace template exactly as configured. In AgentCore, a namespace isolates records, while strategy selection and metadata filters can further narrow retrieval; those are product-specific controls, not universal memory settings: AgentCore Memory metadata.
- Temporarily relax filters. Compare the production query with a broader diagnostic query. Check that every filtered metadata key is indexed and that stored values match the filter in both value and type. When predicates combine with AND logic, one mismatch can exclude the record. Salesforce also warns that prefilters can prevent relevant content from being retrieved: Salesforce Agentforce RAG troubleshooting.
- Search the exact name and identifier. Try the literal vendor name, spelling variants, domain, and stable ID. Compare vector search with keyword or hybrid retrieval on the same query and data if the platform supports those options. This helps identify whether semantic matching is missing an exact name or code. Salesforce describes comparing vector and hybrid results in its Retriever Playground: Salesforce Agentforce RAG troubleshooting. Cloudflare documents recall across keyword indexes, topic keys, semantic vectors, and raw messages: Cloudflare Agent Memory.
- Inspect the retrieval trace. Establish whether the backend returned no records, whether a source failed, and whether the agent invoked or selected the retrieval action. In Azure AI Search’s documented API, a source queried successfully with zero matches is distinct from a source failure; failures can involve malformed filters, configuration drift, permissions, throttling, timeouts, or temporary availability problems: Azure AI Search troubleshooting. Also check when retrieval runs: AWS notes that a new session may retrieve memory speculatively before planning, so the planning trace may not show a
memoryRetrieveaction even when retrieval occurred: Amazon Bedrock agent memory. - Compare retrieved records with the final answer. If the trace contains the vendor memory, the fault is likely after retrieval. Compare the returned records or chunks with the grounded prompt and response; inspect ranking, context and output limits, agent instructions, and the selected action. Salesforce recommends investigating agent, retrieval, and generation layers separately. Azure AI Search notes that a found document can still be absent from the final response when its content exceeds the output budget: Azure AI Search troubleshooting.
Match the symptom to the next check
| What you observe | Where to look | Next check |
|---|---|---|
| Vendor is absent from a broad backend search or listing | Write path, validation, extraction, or indexing | Inspect the ingestion event and write/import errors; compare source and index counts. AgentCore, Salesforce, and Google document product-specific checks. |
| Vendor appears in storage but not through the app query | Namespace, strategy, filters, or permissions | Retry with the same scope and relaxed filters; verify indexed fields and access rights. AgentCore, Salesforce. |
| Exact vendor name or domain fails in semantic search | Query representation or retrieval mode | Compare exact keyword, hybrid, and vector searches using the same query and data. Salesforce, Cloudflare. |
| Trace reports a source error instead of zero matches | Request, configuration, permissions, or dependency | Inspect the per-source error for an invalid filter, configuration drift, authorization failure, throttling, timeout, or availability issue. Azure AI Search. |
| Trace contains the memory, but the agent says it has none | Orchestration, ranking, context limits, or generation | Compare retrieved records with the prompt and final response; verify the expected action ran. Salesforce, Azure AI Search, Amazon Bedrock. |
Compare retrieval methods without changing several variables
When your platform offers alternatives, run the same vendor query against the same data with one change at a time:
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- Filtered versus temporarily unfiltered: tests whether a scope or metadata predicate is excluding the memory.
- Vector versus keyword or hybrid: tests whether exact names, domains, or codes are poorly represented by semantic matching.
- Backend results versus agent context: tests whether records returned by search are passed into the agent’s prompt.
- Agent context versus final response: tests whether the record reaches the model but is omitted because of ranking, instructions, or output limits.
Inspect the returned records or chunks, not just whether the final answer sounds correct. Cloudflare’s documentation captures the intended behavior when recall finds no match: “If no memories match the query, recall() returns an empty answer rather than hallucinating a response.” That behavior is specific to Cloudflare’s documented memory system, not a guarantee about every agent framework: Cloudflare Agent Memory.
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