OPENLOCK · PRACTICAL GUIDE
How does OpenLock complement a data warehouse or RAG system?
A data warehouse stores and organizes data for analysis. A retrieval-augmented generation (RAG) system retrieves information to help a model answer a question. OpenLock’s intended contribution is the engineering and operation of approved business definitions, relationships, evidence, and access across the information those systems use. An engagement should assess what existing infrastructure already does well.
Separate the roles before choosing another component
| Component | Primary role | What to examine |
|---|---|---|
| ERP, CRM & source applications | Operate the business and maintain authoritative records. | Which system owns each fact, and what extraction is approved? |
| Warehouse or lakehouse | Store, transform, and query data for analysis and applications. | Which quality, semantic, lineage, and access controls already exist? |
| RAG system | Retrieve relevant information and provide context to a model. | Does retrieval respect access, document applicability, and source freshness? |
| OpenLock’s intended foundation & service | Connect approved information, preserve reviewed meaning, and maintain governed access. | Which missing definitions, cross-source relationships, or operating responsibilities justify the work? |
These boundaries are not exclusive. Warehouses and retrieval products can already provide governance, lineage, semantic models, and other relevant features. OpenLock should not duplicate a working capability simply to introduce another layer. Supported connections and reuse of existing infrastructure require evaluation; no universal connector compatibility is claimed.
Example: “Can we fulfill this customer’s order?”
Hypothetical architecture example: the order is in an ERP, the applicable bill of materials is represented in engineering records, current stock is in inventory tables, and a customer-specific substitution restriction is in an approved document. A warehouse query can calculate demand and supply if the identifiers, units, revisions, and eligibility rules are already modeled correctly.
Retrieval can find the substitution restriction, but a similar-looking document may apply to a different customer or an expired specification. A useful answer needs the right document version linked to the right customer and product, plus a reproducible quantity calculation and an access check on the combined result.
OpenLock’s intended role is to help establish and operate those connections. The chosen application can retrieve the applicable evidence and call an approved calculation interface. The model can explain the returned result. If the revision is ambiguous or a stock refresh is late, the response should show that limitation or request review rather than imply certainty.
Use decision criteria grounded in the gap
- Definitions and joins already work: start by reusing the warehouse’s tested models and existing operating team.
- The question is limited to approved documents: a carefully permissioned RAG implementation may be sufficient.
- The question crosses transactions, documents, and inconsistent identifiers: assess mapping, source authority, applicability, and reconciliation before expanding retrieval.
- The initial answer works but changes cause repeated failures: clarify monitoring, change review, and recovery responsibilities.
Validate the complete answer path
Check source extraction, joins, filters, document selection, calculation, permission enforcement, and answer presentation together. Test a current and expired document with similar wording, two delivery branches under one billing account, a user denied access to part of the answer, and a deliberately stale data source. Preserve expected answers and record why a refusal or qualified answer is correct.
Governed inputs reduce some causes of error; they do not guarantee model correctness, eliminate retrieval misses, or make every application safe to take action. Transactional changes require a separate authorized workflow. Start with the readiness assessment and the platform’s development and integration scope.
Technical reference
The original Retrieval-Augmented Generation paper by Lewis and colleagues describes combining retrieval with generation. The architecture comparison and hypothetical workflow here describe OpenLock’s intended approach, not a benchmark or a tested integration with a particular vendor.