Mid-market manufacturers are caught in a technology gap that's getting wider.
You're running a $200M operation with 15 people in IT, an ERP that predates the iPhone, and a leadership team asking for operational dashboards by Thursday. A multi-year, multimillion-dollar transformation program is overkill. Generalist contractors don't understand manufacturing. You need someone in between who's done this before and can ship production software inside the constraints you actually operate in.
94% of mid-market manufacturers plan to increase technology investment over the next three years. The question isn't whether to invest. It's whether the investment produces working systems or another shelf of deliverables that never ship.
Five problems keeping manufacturing CTOs up at night. Probably the same ones on your list.
These are the specific, messy, real-world challenges manufacturing technology leaders face every week. Each one maps directly to our core capabilities: application development, data engineering, applied AI, and fractional technology leadership.
Legacy ERP modernization & systems integration
Your Epicor instance is fifteen years old. Your quality team runs on a separate system that doesn't sync with production scheduling. Half the company exports to Excel every Friday afternoon because that's the only way to get a cross-functional view. Sound familiar?
The answer isn't ripping and replacing your ERP. That's a three-year project with a 70% failure rate, and you don't have three years. The better path: integration and data layers that connect your existing systems into a coherent platform. Two-tier ERP strategies, API layers between legacy and modern systems, consolidated reporting that gives leadership the visibility they need without forcing a migration you're not ready for.
Companies delaying ERP modernization spend 15-25% more on annual IT maintenance than those actively modernizing. The cost of doing nothing is real, but the cost of doing it wrong is worse.
Shop floor data integration & OT/IT convergence
58% of manufacturers still monitor equipment performance manually. Nearly half manage inventory with clipboards and spreadsheets. The operational technology on your factory floor and the enterprise IT running your back office exist in separate universes. Your leadership team finds this unacceptable. So do we.
The solution starts with connecting legacy PLCs, SCADA systems, and MES platforms to your enterprise data layer. Edge computing for real-time data capture. Secure OT-IT connectivity that doesn't introduce new attack surfaces into environments that are already the #1 global ransomware target. The practical work of getting machine data off the floor and into dashboards your operators and executives can both use.
This is where AI becomes real for manufacturers. Not a chatbot on your website, but predictive maintenance that cuts costs by 25% and drops unplanned downtime by 30%. Quality inspection that catches defects at 90% accuracy. You can't get there without the data infrastructure, and that's the foundation this work creates.
Supply chain visibility & resilience platforms
78% of manufacturers cite trade uncertainty as their top concern. Tariffs are adding 5.4% to input costs. 73% say tariff management alone is pulling teams away from core priorities. And yet only 9% have actually shifted suppliers. The sector is running on adrenaline and hope, and that's not a strategy.
The solution is an integrated platform that connects procurement, logistics, and production planning into a single operational view. Not another dashboard that shows you what happened yesterday, but systems that model what happens if your primary steel supplier can't deliver next month. AI-enabled visibility tools are the top supply chain investment priority in 2025 for good reason: you can't optimize what you can't see.
For manufacturers navigating reshoring decisions, the technology question is inseparable from the business question. Reshoring only works with automation, workforce optimization tools, and supply chain replanning, all of which require modern systems.
Quality management & regulatory compliance systems
Quality control is the leading application for AI in manufacturing for the second year running, and 50% of manufacturers are investing in quality improvements. But for regulated manufacturers dealing with FDA, ISO, ITAR, or the new CMMC cybersecurity requirements for DoD contractors, the compliance data burden is intensifying at exactly the moment they can least afford to handle it manually.
The right quality management system isn't bolted onto the side of your ERP as an afterthought. Automated inspection workflows. Traceability systems that satisfy auditors without creating a second full-time job for your quality team. Document management that handles regulatory versioning. The CMMC Final Rule now mandates cybersecurity certification for defense contractors with scoping that extends into OT environments, and most mid-market manufacturers aren't ready.
Post-acquisition technology integration & value creation
When a company acquires a manufacturer, a predictable sequence of technology problems unfolds. Leadership needs KPI dashboards yesterday. The acquired company runs JD Edwards while the parent runs Dynamics NAV. Critical process knowledge lives in the heads of three people who might not stick around. One Fortune 100 company found 600+ unauthorized applications in use during post-acquisition discovery. Only 20-30% of acquisitions actually replace ERP systems. The rest need integration layers.
This is a predictable cycle. The 100-day plan, the bolt-on integration playbook, the carve-out technology separation that costs 1-2x annual tech operating expenses. The answer is consolidated reporting and data platforms that give leadership the visibility they need without forcing a rip-and-replace ERP migration that blows the timeline and the budget.
The Technical Due Diligence assessment is the starting point. RSM documented a case where a target's custom ERP couldn't support integration with the platform company, and $30M in upgrade costs weren't identified until after close. A thorough pre-close assessment finds those surprises before they become expensive.
Great fit
- Running legacy ERP systems that don't connect to modern tools or each other
- Shop floor data trapped in disconnected MES, SCADA, or manual processes
- PE portfolio companies needing post-acquisition technology integration
- Manufacturing operations ready for AI but lacking the data foundation
Not the right fit
- Looking for ERP vendor selection or implementation of off-the-shelf packages
- Need a multi-year, enterprise-wide transformation program
- Single-site operations with simple technology needs
- Companies that need staff augmentation without technical leadership
77% of manufacturers say they've adopted AI. Only 6% are seeing real results.
The gap between AI aspiration and AI reality in manufacturing is wider than in almost any other industry. 56% of manufacturers aren't even sure their ERP can support AI integration. 47% struggle with fragmented data, the prerequisite AI needs before it can do anything useful. We don't sell "AI strategy." We fix the data foundation, connect the systems, and deploy proven models against specific operational problems.
Maintenance cost reduction
Predictive maintenance models trained on your equipment data. Not a vendor's generic algorithm, but models that learn the specific failure patterns of your specific machines. 30% decrease in unplanned downtime.
Defect detection accuracy
Computer vision and ML for quality inspection. AI catches what human eyes miss at 2 a.m. on the third shift. 35% improvement in product quality. This is the leading AI application in manufacturing for a reason.
Revenue growth for automators
Manufacturers that increased automation in response to labor shortages grew revenue at 9.6%, compared to 7.1% for those that didn't. With 3.8 million new workers needed by 2033, automation is the math that works.
Forecast error reduction
AI-driven demand forecasting trained on your sales, seasonality, and supply chain data. Better forecasts mean less overstock, fewer stockouts, and production schedules that reflect what's actually happening in the market.
We speak EBITDA, not just API.
47% of PE returns now come from operational value creation. PE firms with dedicated operating partners achieve 1.7x higher EBITDA improvements. We understand the 100-day plan, the bolt-on integration timeline, and the exit readiness checklist. Every engagement we run for a PE-backed manufacturer maps back to value creation metrics your board cares about.
Post-acquisition visibility
KPI dashboards, financial reporting infrastructure, and operational visibility built on the timeline your deal requires. We start with the data layer and deliver reporting your operating partner can use within the first sprint.
SG&A savings from bolt-on integration
Bolt-on acquisitions target these savings through function consolidation, but technology compatibility is frequently overlooked. We build the integration layers that make consolidation actually possible without forcing an ERP migration.
EBITDA improvement through AI
PE firms are capturing these improvements through targeted AI implementations in under a year. We identify the highest-ROI use cases in your portfolio companies and build them, with measurable baselines so you can prove the return.
Technical due diligence
Pre-close technology assessment that finds the expensive surprises before they become your problem. Technology debt, cybersecurity gaps, integration complexity, data quality, and team capability. 1-2 weeks, clear deliverable.
Not sure where to begin? Most manufacturing CTOs aren't either.
Our assessment offerings are designed to be easy to say yes to: fixed scope, fixed price, short timeline, and tangible deliverable. Most of our platform engagements start with one of these. Some clients take the roadmap and run with it internally. Most ask us to keep building.
Start with a Data Readiness AssessmentProduct Design Sprint
Turn a business idea or known operational problem into a validated product concept. User research, rapid prototyping, technical feasibility, and a buildable specification in weeks.
Data Readiness Assessment
Audit your data architecture, map integration gaps between ERP, MES, and quality systems, and produce a prioritized modernization roadmap with AI readiness scoring.
AI Opportunity Assessment
3-5 high-impact AI use cases for your specific manufacturing operation. Predictive maintenance, quality inspection, demand forecasting, and scheduling optimization. Feasibility and ROI analysis included.
Technical Due Diligence
Pre-acquisition or internal technology assessment. Technology stack, team capability, technical debt, integration complexity, and cybersecurity posture. The findings that should inform your next move.