What the documents look like
Multi-warehouse allocation and inventory synchronization decisions sit at the order routing stage and determine which warehouse ships an order. Source systems include WMS, OMS, ERP inventory and platform inventory interfaces. Day-to-day materials include allocation rules, inventory synchronization tables, transfer orders and stockout warnings. These materials update daily or hourly, and the available-to-sell quantity and allocation priority for one order can change several times within a single day. Any comparison therefore has to lock a single time cross-section.
Contract and transaction material comparison in this category aligns the parties, objects, periods, fields and authorization states found in allocation rules, inventory synchronization tables, transfer orders and stockout warnings, item by item. Quoted validity periods, transfer quantities and available-to-sell values that appear in the materials are fields still to be verified. A retrieval result or a filled-in form does not by itself establish that an authorization has taken effect.
Constraints at the context limits step
Context and token on this page refer to the input range and reference trimming applied when an AI dialogue node reads materials. The model maximum context is checked against actual model capability. The reply limit only restricts the length of a single reply, and the two cannot be used interchangeably. The knowledge base reference limit is controlled by tokens, so a long single passage may be trimmed, and the completeness of the supporting basis needs to be checked against question samples. The same question produces different input under empty history and under history, and the memory round setting changes what is sent to the model. When a fixed reply format such as json_schema is used, field completeness and successful parsing need to be verified; text length does not count as evidence of structural correctness. Retrieval by itself does not complete an authorization determination, and semantic recall and relevance scores do not carry permission or entity isolation.
Hypothetical exercise sample: the source material has three sentences. The first sentence reads "Allocation rule version A states that East China orders ship preferentially from the Suzhou warehouse, effective from 1 March 2025 to 31 March 2025." The second sentence reads "The inventory synchronization table shows that the Suzhou warehouse available-to-sell quantity on 20 March 2025 is 0." The third sentence reads "Transfer order T-0320 records that 200 units moved from the Hangzhou warehouse to the Suzhou warehouse on 20 March 2025, with status pending review." The draft sentence to be assessed is "The Suzhou warehouse has sufficient available-to-sell quantity on 20 March 2025, and East China orders can ship from the Suzhou warehouse." That draft sentence shares the object, period and field with the second sentence, and the values are mutually exclusive. The transfer order sits at pending review status and does not constitute a fact that inventory has already increased.
Configuration and implementation checks
| Configuration or check item | Value or action on this page | Basis and comparison method |
|---|---|---|
| AI model and maximum context | Choose a model matched to the material length | Check against actual model capability; the reply limit is not treated as the context window |
| Memory rounds | Hypothetical starting point for this exercise: retain a small number of history rounds | Compare the input for the same question under empty history and under history |
| Knowledge base reference limit | Hypothetical starting point for this exercise: enough tokens to cover one full material | Compare against the single-passage length and question samples, and observe whether trimming occurs |
| Reply format | Select json_schema and fill in the format requirements when fixed fields are needed | Verify field completeness and successful parsing; do not check text length |
| Minimum relevance | Set according to the conditions under which semantic retrieval or result reranking applies | This value is a filter threshold and is not a means of permission or entity isolation |
| Multimodal recognition | Enable only when the model supports it and the material contains images | Unsupported types are filtered before the request and are not sent to the model |
Three common errors
- Treating the reply limit as the full context window. Input the same inventory synchronization table and the same question, compare the two fields of model maximum context and reply limit, and observe whether the supporting basis is truncated early. The two have different meanings, and conflating them misjudges the readable range of the material.
- Treating a pending-review transfer order as inventory already increased. Input the status field of transfer order T-0320 and the available-to-sell field of the inventory synchronization table, compare the two values, and observe whether the draft sentence contradicts the second sentence. Pending review is not completed execution.
- Using a relevance score in place of authorization or entity filtering. Input the minimum relevance setting and the retrieval results, compare the score against the material's party and period fields, and observe whether an unrelated party or an unauthorized record is treated as verified. Retrieval does not complete authorization.
How to verify the setup
- Input the second sentence "The inventory synchronization table shows that the Suzhou warehouse available-to-sell quantity on 20 March 2025 is 0" together with the draft sentence, and compare the values for the same object, the same period and the same field. A mutually exclusive value means the draft sentence is not supported.
- Input the third sentence's transfer order status "pending review" together with the draft sentence's conclusion of sufficient inventory, and compare the status field with the inventory field. While the transfer order is not complete, an increase in inventory cannot be inferred, and the item is recorded as pending verification.
- Input the same question twice, once with empty history and once with history, and compare the context content sent to the model and the referenced token count. Observe whether the difference in history causes references to be trimmed. If the reference limit is insufficient, record the gap without asserting that retrieval necessarily returns an empty result.