Industrial AI & Decision Systems
Your data.
Your operations.
Actual answers.
From fragmented data to better operating and capital decisions.
We design and deploy systems that connect enterprise data, automate governed workflows, and combine AI with engineering, operational, and financial analysis. Built for industrial environments where decisions must be traceable and the economics have to hold.
PhD chemical engineering. Chicago Booth MBA. Senior industrial operator and former Silicon Valley CEO. Credible in the architecture review and the board meeting.
The Problem
Your systems hold the data.
Your teams still assemble the decision.
Industrial businesses rarely lack data. They lack a reliable path from ERP records, operating systems, documents, models, and external sources to an answer that can survive technical and financial review.
AI is not the right tool for every problem. The objective is a working decision system, whether the right method is rules, optimization, retrieval, computer vision, statistical modeling, or a combination.
Industrial decision systems
AI is one component.
The decision is the product.
A useful system connects source data, operating rules, domain models, and workflow controls to a decision someone owns. It shows where the answer came from, what assumptions govern it, and where human review belongs.
We use retrieval, agents, computer vision, optimization, geospatial analysis, and conventional software where each method fits. The architecture follows the business problem, not a preferred tool.
Services
What we build
Outcome-led systems from architecture through production deployment, built around the decision, workflow, and control environment.
Enterprise Data Integration
Governed pipelines across ERP records, databases, APIs, documents, and external sources. Common data models make transformations, permissions, and refresh status explicit.
Workflow & Compliance Automation
Eligibility checks, document processing, dispatch, reporting, approvals, and alerts. Rules and AI handle the repeatable path; accountable people retain judgment.
Knowledge Systems
Retrieval-augmented generation, multimodal search, and source-aware interfaces over private documents and data. Evaluation and access controls are designed with the system.
Industrial Analytics & Decision Models
Reproducible engineering and financial models for project development, operating choices, scenario boundaries, and investment gates.
Operational Intelligence
Scheduled monitoring, exception scoring, geospatial screening, alerts, and management views that turn changing external and internal data into an owned response.
Secure Deployment & Handoff
Cloud, VPC, hybrid, or local architectures that support customer security controls. Deployment includes monitoring, documentation, source code, and a defined operating owner.
When to call VaultIntel
Three situations where we fit
The strongest fit is a material decision or recurring workflow where fragmented evidence, operating judgment, and economic consequence meet.
Manual reconciliation has become part of the process
Orders, eligibility rules, operating data, documents, and reports cross systems. Analysts rebuild joins or route exceptions manually. We connect the sources, automate the standard path, and preserve accountable review.
A capital decision spans engineering and economics
Process design, carbon intensity, infrastructure, incentives, commodity exposure, and financing assumptions live in separate models. We connect them to stage-gate scenarios and investment decisions.
The answer must survive technical or commercial review
Eligibility, emissions, compliance, or incentive claims depend on source records and reproducible logic. We build traceable calculations and controlled reporting for operating, management, and diligence review.
Case Studies
Selected systems, working in production
Seventeen years of fragmented community knowledge, made usable as a source-linked research system.
This independent community project preserves a biochar research archive spanning five email groups, technical attachments, field reports, and images. The material was valuable but fragmented across long threads, inconsistent terminology, and disconnected media.
The production system supports meaning-based and multilingual questions across text, images, and PDF pages while retaining links to the original messages and discussion context. The technical case study documents the evidence boundary, retrieval design, measured runtime, and operating-cost basis.
Eligibility, dispatch, and reporting across 83 active municipal program codes, connected in production.
An organics operator needed to apply address-specific municipal program rules at checkout, then move each approved order through dispatch and reporting. Customer-entered city names alone could not distinguish incorporated jurisdictions from eligible unincorporated areas.
The anonymized production platform uses geocoding and authoritative boundary data to validate eligibility, 83 active coupon codes to apply program rules, workflow orchestration to generate and route dispatch records, and a reporting service over Firestore event data. Three independently deployed services preserve operating traceability and limit failure domains.
Process
How we engage
Each engagement follows explicit decision gates. Work can stop after assessment if the economics or evidence do not support implementation.
Initial engagement
Decision Workflow Assessment
A bounded engagement focused on one material decision or workflow. We map the current state, quantify the economic stakes, inspect evidence and control constraints, and identify the least-complex intervention that can materially improve the outcome. Company-wide adoption and implementation remain separate decisions.
Decision brief
- Current-state workflow and decision map
- Value, feasibility, data, and control assessment
- Recommended target state and intervention
- Bounded implementation scope and decision gates
A build proceeds only through a separate go/no-go decision.
Decision & Evidence
Define the operating or management decision, current workflow, economic stakes, source evidence, accountable owner, and conditions for success.
Recommendation & Scope
Select the right intervention and map integrations, methods, permissions, failure modes, human review, and lifecycle requirements. Produce a bounded architecture and commercial scope.
Build & Integrate
Build against representative customer data and connect the actual systems, rules, and interfaces required for the operating workflow.
Validate & Handoff
Test against agreed criteria, document known limits, deploy monitoring, train the operating owner, and hand over source code and runbooks.
Technology
Vendor-neutral.
Architecture-specific.
We work within the customer environment and select components for the data, control, operating, and lifecycle requirements.
Deployment Environments
Data & Intelligence
Delivery & Analysis
About
Rick Wilson
I build decision systems for industries I have spent a career operating in: energy, industrials, sustainable materials, regulated operations, and enterprise finance. The work starts with the operating and economic decision, then applies the right data architecture, analysis, automation, and AI.
A PhD in chemical engineering and an MBA in finance from the University of Chicago Booth School of Business provide an unusual vantage point: I can sit in the architecture review and the board meeting. I have led refinery research, engineering, supply chain, business development, industrial startups, and sustainability programs.
Engagements are bounded and accountable. Clear scope, documented controls, working software, and an explicit handoff.
Selected Decision Systems
Methods connected to material decisions
Anonymized examples from industrial development, operations, and applied engineering.
Integrated CI, Incentive & Value-in-Use System
A first-of-kind low-carbon pathway cannot be evaluated in disconnected engineering, carbon, policy, market, and financial models.
A reproducible Python-to-Excel decision chain links process basis, life-cycle carbon, incentive logic, utility and CHP scenarios, market value, and capital cases. Controlled versions and generated review outputs maintain one assumption trail from engineering through the investment gate.
Industrial Formulation Optimizer
Variable ingredient assays, delivered prices, availability, and product specifications create a constrained formulation problem that static recipes cannot solve.
A deployed, tenant-isolated linear-programming service identifies the lowest delivered-cost feasible blend, explains binding constraints, and produces a traceable result for operating review. Customer assays, prices, formulations, and identities remain segregated.
Vision-to-Engineering Feed Composition Pipeline
Feedstock composition arrives as photographs and irregular source material, while engineering models require structured inputs with visible provenance and uncertainty.
This FEL-1 pilot converts images into provenance-tagged composition estimates and a replayable engineering workbook. It records source files, model inputs, uncertainty, and calculation lineage; laboratory validation remains a gate before design use.
Discuss a business problem.
Bring the decision, workflow, data constraints, and economic stakes. We will determine whether a Decision Workflow Assessment is warranted.
If AI is not the right method, we will say so. A smaller rules, data, or optimization system may be the better answer.
Best fit: bounded, high-value systems with an accountable owner and a clear operating or management decision. Engagements are scoped, documented, and handed over.
For the first email, describe the decision and constraints without confidential, regulated, or export-controlled information. We can establish an appropriate exchange process before reviewing sensitive material.