We map legacy databases, build a governed semantic layer, and deploy AI your engineers validate — without replacing your MES, ERP, or core systems. Weeks, not an 18-month transformation program.
Governed AI on MES, ERP, and custom operational databases. Deepest experience in manufacturing — same playbook for healthcare ops, financial operations, and enterprise IT.
How we map legacy databases, build a semantic layer your SMEs validate, and deploy AI on read-only approved views — without replacing MES, ERP, or core systems.
Prefer to read? See the elevator pitch in our Ai4 section.
Video plays when assets/hero/pitch-90s.mp4 is added.
Antonio and Fernando will be at Ai4 Aug 4–6 at The Venetian. If your AI pilot stalled because teams don’t trust answers from raw operational data, let’s compare notes.
Elevator pitch
We map legacy operational databases, build a governed semantic layer your SMEs validate, and deploy AI on read-only approved views — without replacing MES, ERP, or core systems. Start with a 2-week diagnostic.
Pick your industry — see how we map legacy data, govern access, and deploy AI your teams can defend.
Typical entry: Prime Diagnostics on your MES in two weeks.
Same playbook as manufacturing: inventory, govern, then deploy.
Built for teams that need defensible numbers, not another dashboard experiment.
For environments where safety and auditability come first.
Reduce admin bottlenecks without ripping out systems of record.
When “we have an ERP” still means hundreds of undocumented tables.
Not another chatbot on raw tables. Infrastructure your operators and data teams can defend.
Governed semantic layer between your LLM and approved read-only views — traceable, SME-validated, explainable.
Engineers and analysts get answers in minutes instead of hours of SQL pulls and spreadsheet reconciliation.
Data dictionary, views, governance docs, and code — no subscription required to keep using your layer.
Whether you’re evaluating agents, RAG, or governance, this is the data trust layer underneath.
Business meaning for tables, views, and calculations — the context LLMs cannot infer from schema alone.
Approved read-only views with business logic baked in — your RAG surface and agent query boundary.
Every AI question logged — traceable to views, calculations, and the SME who validated them.
Engineers sign off before production use — so stalled pilots become trusted daily workflows.
AI never touches raw operational tables. Every query routes through a semantic layer and read-only approved views your SMEs validate.
Four phases — from first conversation to infrastructure your team owns. Most teams enter at Prime Diagnostics.
While enterprise programs spend 18 months in planning, most engagements ship governed infrastructure in weeks. You own every deliverable.
MES, ERP, and custom apps were built for transactions — with business logic buried in stored procedures, years of customizations, undocumented schemas, and tribal knowledge only a few people understand.
Connect AI directly to those tables and you get unreliable answers. Operators and engineers stop trusting the system. The pilot stalls.
The issue isn’t the technology.
The issue is that nobody mapped the database before plugging in the AI.
Prime AI exists because Antonio spent 18 years inside semiconductor and discrete manufacturing running MES and production systems. He knows where operational logic hides, why teams don’t trust raw-table answers, and what “governed” has to mean before AI goes live.
We don’t sell demos. We map your database, build the layer, and leave you with infrastructure your SMEs can defend — whether you’re in manufacturing, ERP-heavy finance, or enterprise IT.
Meet the teamWe don’t connect AI to raw operational tables. Every engagement routes through a semantic layer and read-only approved views—traceable, validated, and trusted by your SMEs.
30+ years enterprise systems on the founding team; deepest track record in manufacturing and MES. The same governed playbook applies to ERP, healthcare operations, financial ops, and custom enterprise apps.
Timelines vary by schema complexity and team availability.
When the engagement ends, the code, documentation, data dictionary, and semantic layer are yours. No vendor lock-in, no subscription to keep using what we built.
We prefer clients who can run without us—because those clients trust us enough to bring us back.
You don’t need another horizontal “AI for any business” vendor. You need governed infrastructure on the data you already run.
| Recommended Prime AI | Big 4 / SI | Horizontal AI | DIY + LLM | |
|---|---|---|---|---|
| Time to first value | 2-week diagnostic; ~10-week build | Often 12–18+ months | Fast demo, slow trust | Fast start, stalls on data |
| Operational data depth | MES, ERP, legacy apps — core specialty | Broad, variable bench | Generic connectors | Depends on internal team |
| Governance built in | Read-only views, audit trail, SME gates | Process-heavy | Often bolt-on | Rarely systematic |
| You own deliverables | Yes — code, dictionary, layer | Often license-dependent | Platform lock-in | Yes, if you finish |
| Founder in the room | Antonio on every engagement | Junior team common | Account manager | Your problem |
Most clients start with Prime Diagnostics — fixed scope, clear deliverables, low risk before a full build.
Where should you start?
2-week database inventory and data dictionary before any AI work.
~10-week semantic layer design, build, and governed deployment.
Ongoing optimization, new views, and strategic guidance.
Most teams start with Prime Diagnostics — fixed scope, clear deliverables, low risk before a full build.
The Foundation
Map your operational database before touching AI — MES, ERP, or custom apps.
What happens:
Result: A data dictionary and semantic foundation for all AI work.
The Implementation
Design, build, and deploy governed semantic views and access controls.
What happens:
Result: A working semantic layer engineers use daily—traceable and governed.
The Partnership
Continuous optimization and capability expansion as operations evolve.
What happens:
Result: Your semantic layer and AI capabilities evolve with the business.
Composite case patterns — not attributed to a named public client.
We’re a boutique. Antonio’s 18 years on the shop floor grounds our manufacturing work; the same governance model applies wherever legacy operational data blocks trusted AI. Prime Diagnostics lets you validate the approach in two weeks — with deliverables you keep regardless.
6–8 hrs/week → minutes per query
Reducing Engineer Time Spent on Data Pulls
Engineers answer operational questions in minutes instead of hours. Data is consistent org-wide.
The situation
Mid-market discrete manufacturer. Engineers spent 6–8 hours weekly pulling MES data and reconciling spreadsheets.
The problem
400+ tables, no documentation, no trusted relationships. Engineers didn’t trust the data.
What we did
The result
Questions answered in minutes. Consistent data org-wide. No spreadsheet reconciliation.
Stalled AI project → trusted daily use
Building Trust in AI-Generated Insights
Engineers trust AI insights because they understand how answers are calculated.
The situation
Food manufacturer wanted AI for yield and defect analysis. Generic tools produced answers engineers didn’t trust.
The problem
AI connected directly to production tables. Answers contradicted engineer ground truth. The project stalled.
What we did
The result
Trusted insights for root cause analysis and process optimization.
Days of reconciliation → governed daily views
Trustworthy Numbers Without Replacing ERP
Finance and ops teams query approved semantic views instead of rebuilding spreadsheets from raw extracts.
The situation
Regional financial operator on a heavily customized ERP. Month-end and ops reporting required manual pulls, pivot tables, and email chains.
The problem
Leadership wanted AI-assisted analysis, but calculation rules lived in reports, macros, and tribal knowledge — not in a model the LLM could safely use.
What we did
The result
Trusted daily and weekly views; AI answers trace back to approved calculations — without an ERP replacement project.
Prime Diagnostics produces a living data dictionary — not a slide deck. Prime Build turns that into semantic views your team queries daily.
You see what exists, what it means, what’s sensitive, and what to build next — with full audit logging and SME sign-off before production.
View 10-phase methodology
Typical for 400–800 table schemas. Actual timeline depends on schema size, data access, and SME availability.
Phase-level detail and cross-cutting foundations live on our Methodology page.
We’ve modeled and deployed against major MES, ERP, and AI platforms. Your stack stays yours; we build the governed layer on top.
Same methodology — applied where your operational truth lives.
30 years of enterprise systems experience, including 18 years inside semiconductor and discrete manufacturing—building, debugging, and improving the systems that ran production. He knows why MES databases are structured the way they are and where business logic hides.
The Prime AI rule: operational databases need context before they can serve AI. Every engagement starts with your systems, constraints, and definition of truth.
Fernando builds the infrastructure that turns manufacturing expertise into a scalable business—spanning product, engineering, and how those two should talk to each other. He holds a Bachelor of Science in Web Design and Engineering from Santa Clara University and is pursuing a Master’s in Computer Science through Harvard Extension School.
Background includes enterprise platforms at Disney and product-scale work at La Mer (Estée Lauder). At Prime AI, he turns deep operations expertise into repeatable, governed delivery.
We’d rather be clear on fit than chase the wrong conversation.
We’ll tell you honestly if Prime Diagnostics is the right first step.
Horizontal AI vendors and Big 4 programs may be a better match.
Manufacturing is our deepest credibility — especially MES. The same governed playbook applies to ERP, healthcare operations, financial ops, and custom enterprise apps. If your AI initiative depends on messy legacy operational data, we can help.
If you have a real operational database (production, logistics, finance ops) and need governed AI on it, we can help. If you only need a product copilot or doc RAG on SaaS tools, we’re usually not the right fit — and we’ll say so on the discovery call.
Platforms give you access. They don’t map your stored procedures, custom fields, or tribal knowledge. We build the semantic layer and governance your team needs to trust answers — on top of what you already own.
Table inventory, relationship map, first-draft AI data dictionary, sensitive-data flags, and a prioritized roadmap. You keep everything — it’s yours even if you don’t continue to Prime Build.
Read-only database access, approved views only, query logging, and SME validation gates before production use. We align with your IT and compliance team — not around them.
Yes. Antonio and Fernando attend Aug 4–6, 2026 at The Venetian, Las Vegas. Book time or mention Ai4 in your message.
Eight questions to ask before connecting an LLM to MES, ERP, or custom databases — plus what “governed” actually means in practice.
Request the checklist on your discovery call — we’ll walk through it together.
Get the checklistPrime Diagnostics gives you a data dictionary, relationship map, and roadmap — deliverables you keep even if you don’t continue. No 18-month program. No platform lock-in.
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