Ship an AI assistant grounded in your operations data.
Operators, field techs, and maintenance engineers need conversational access to manuals, work orders, P&IDs, and live asset data. Building a production-grade RAG stack with vector embeddings, secure retrieval, and grounding takes months. Flex83 ships it as platform capability.
A production-grade industrial copilot is harder than the demo.
The demo is easy. The production system — with tenant isolation, document security, citations, and live operational context — is what kills most pilots.
8–12 mo
Vector index, chunking, embedding, retrieval, grounding, citation, eval, monitoring — eight production systems your team has to build, integrate, and maintain.
70%+
Industry analysts consistently report most enterprise GenAI pilots stall in production. The blocker is rarely the model. It’s the surrounding platform.
$260K
An OEM’s industrial customers won’t share documents. Your copilot has to retrieve from each tenant’s corpus — never another’s — with audit trails.
The RAG stack, productized — with multi-tenancy built in.
Flex83 ships every primitive a production RAG system needs: Knowledge Hub for document ingestion, FlexVector for embeddings, Cortex AI for grounded generation, per-tenant document isolation, and audit-grade citations on every answer.
Your team builds the prompts and the product. Flex83 runs the retrieval.
Ingest, chunk, and index PDFs, manuals, work orders, and structured data.
Production vector store with per-tenant isolation and metadata filters.
Grounded LLM with citation, eval hooks, and configurable model backends.
Every answer cites the source document, work order, or live asset.
Per-tenant corpora — no cross-tenant leakage, ever, by construction.
Every query, retrieval, and answer logged for compliance and review.
From document upload to grounded answer — in one platform.
A reference architecture for shipping a production RAG copilot on top of Flex83.
Knowledge Hub pulls manuals, work orders, and P&IDs per tenant.
FlexVector chunks, embeds, and indexes with tenant-scoped namespaces.
Cortex AI retrieves the right context, including live telemetry.
Grounded LLM produces an answer constrained to retrieved sources.
Citations link to source docs; the query is logged for compliance.
From AI demo to production copilot.
Three things that change when RAG ships as platform capability instead of project code.
Ship a branded copilot per customer
Per-tenant document isolation, per-tenant theming, per-tenant model behavior. Your customer sees your AI — not Flex83’s.
Trustworthy answers, not hallucinations
Grounded retrieval with citations on every answer. If the source isn’t in the corpus, the copilot says so — rather than inventing.
Live telemetry, not stale knowledge
Cortex AI retrieves both documents and live asset data. Operators ask “what’s wrong with pump P-204?” and get current state plus historical context.
Production AI on industrial data.
Per-tenant document isolation — by platform construction
Every answer grounded in a retrievable source
Configurable LLM backends — not locked to one vendor
Full query and retrieval log per tenant
Stop pilot-purgatory. Start shipping grounded AI.
Talk to a Flex83 platform expert about your industrial AI roadmap. We’ll walk you through Knowledge Hub, FlexVector, and Cortex AI — and what it takes to ship a production copilot per customer tenant.