Give production, maintenance and warehouse teams a clearer route to approved knowledge. Use GenAI, LLMs and RAG to search SOPs, equipment manuals and operating records, with source references and agreed access boundaries.
Request a discovery callFocus the assistant on a defined team and the questions they repeatedly need to answer. Data security and integrity shape how sources are selected, accessed and updated.
Help production and warehouse teams find approved procedures, process steps and escalation guidance. Show the relevant source and revision alongside the answer.
Make equipment manuals and approved troubleshooting notes easier to search. Help technicians locate relevant guidance while keeping maintenance decisions with qualified staff.
Find quality procedures and summarize approved shift notes with source references. Help the next team understand open issues, required checks and responsible owners.
Scope a read-only pilot around one approved collection and one input route. Agree the questions, expected answers and source requirements before building.
How we workExplore a sample knowledge assistant
Try three situations: a supported answer, a question the documents cannot answer, and a simulated access restriction.
Scripted illustration · synthetic documents
What should I do if the carton totals do not match?
Supported by a sample source
Place the receipt on hold. Record the printed and counted quantities, then ask the shift supervisor to review and resolve the discrepancy before confirming the receipt.
The staff member can open the cited passage and check the answer before acting.
These predefined responses demonstrate intended behaviour. No live LLM, retrieval, document upload or access enforcement runs here. A customer pilot evaluates answer quality, missing evidence and permissions against agreed test cases.
Fit the work to your existing systems
Start with a read-only knowledge workflow. Your existing AI or search platform may be the right foundation; we assess that before recommending a custom build.
One document collection, a knowledge owner and an agreed input route. Check formats, versions and update frequency.
Map who can see each source and how those permissions reach retrieval. Verify the controls in the selected environment.
Test representative questions, source support, citation correctness and situations where an answer should be withheld.
Agree source updates, regression checks, operating costs and a support owner before a production rollout.
A knowledge owner, approved documents, representative questions and an IT contact for permissions and source access.
The implementation route, data handling, access tests, answer-quality criteria, update process and handover.
Verify source permissions and updates, quality monitoring, retention, deployment controls and support responsibilities.
The sample RAG conversation illustrates the intended behaviour. It does not connect to your sources, run an LLM or enforce real user permissions.
The two-page RAG pilot brief outlines the proposed scope, evaluation, responsibilities and commercial next steps. We tailor the document collection and questions to your industrial workflow.
Understand the sources, customer effort and decisions that shape an industrial RAG engagement.
Retrieval-augmented generation connects a large language model to relevant information from an approved collection. An industrial assistant can use SOPs, manuals and team knowledge to help compose an answer with source references. Retrieval can still miss information, and a cited answer can still be wrong, so the pilot evaluates both.
The proposed knowledge pilot is read-only. Staff review guidance and follow your existing operating and safety procedures. Equipment control, autonomous system updates and changes to approved procedures are outside this scope.
Start with one approved document collection and one agreed input route: upload or a scoped connector. We review format, language, volume, equipment references, document ownership and update frequency before confirming the scope. Additional collections and connectors are scoped separately.
Before sample evaluation, we agree what data can be used, where it is processed, what the model provider receives, who can access it, and retention and deletion requirements. Document versions, source references and permission checks are part of the agreed design and evaluation.
We design and test an insufficient-evidence response and a route to the responsible person. The evaluation includes unanswerable questions, conflicting or outdated sources, wrong equipment references and access boundaries. These limitations should be visible before rollout.
Yes. Scoping checks your current tools first. Custom work is useful when your knowledge workflow, source handling, access requirements or integration needs are not adequately met by the existing setup.
Nominate an operations owner and an IT contact. Supply approved representative documents and questions with reviewed expected answers. We agree scope, review time, fees and any model, cloud or software charges before work starts.
