Modernization strategy, AI architecture, and capital sequencing
A mid-market manufacturer serving regulated programs was preparing to increase production and raise growth capital.
Talbot West embedded with leaders and operating teams across business development, program management, engineering, procurement, manufacturing, quality, finance, and IT. We mapped the company from RFP intake through delivery and cash collection, identified the constraints on higher operating volume, and defined the capabilities required to remove them.
- 01Define the modernization agenda
- 02Decide where AI belongs
- 03Trace dependencies
- 04Increase operating capacity
- 05Sequence capital
Define the modernization agenda
Leadership needed greater production capacity, faster commercial throughput, stronger management control, improved regulatory readiness, and a credible plan for deploying growth capital.
We translated those objectives into required capabilities and traced them back to operating constraints.
The analysis covered proposal and estimating workflows, engineering handoffs, procurement, production, quality, delivery, finance, risk, reporting, identity, access, and the ERP/MES environment.
We identified where manual work constrained throughput, where information fragmented across systems and spreadsheets, where management lacked reliable visibility, and where later capabilities depended on stronger data, process, or system foundations.
Decide where AI belongs
Leadership expected AI to matter but had material concerns about hallucination, sensitive information, intellectual property, commercial large language models, and defense-sector security requirements.
Talbot West evaluated AI use case by use case.
Bounded AI uses
Proposal-compliance extraction, technical-data processing, and inspection-planning support presented bounded tasks with identifiable sources and reviewable outputs.
Deferred uses
Other applications remained later in the roadmap because their data, process, or integration prerequisites were not ready.
Alternative mechanisms
We compared AI with process redesign, packaged software, deterministic automation, system integration, analytics, and custom engineering.
AI entered the roadmap only where it improved a defined capability relative to those alternatives.
Security requirements constrained deployment. We evaluated secure-cloud and on-premises approaches against data sensitivity, CMMC Level 2 requirements, ITAR-sensitive contexts, access controls, auditability, integration requirements, and operating cost.
Trace dependencies before funding
The investments formed a dependency chain.
Talbot West mapped those dependencies before sequencing the portfolio.
Early funding went to capabilities with clear operating value and sufficient readiness. Dashboarding, advanced AI, and other downstream capabilities stayed behind the data, system, governance, or integration work required to support them.
Connect technology to operating capacity
The prioritized capabilities addressed specific growth constraints.
Proposal capacity
Faster compliance analysis increased proposal capacity.
Procurement and execution
Faster BOM and technical-data processing shortened the path from award to procurement and execution.
Quality capacity
More efficient inspection planning increased quality capacity.
Management visibility
Reliable operational data improved management visibility and created the basis for later automation.
Shared operational data
ERP/MES maturity increased the number of downstream capabilities that could use shared operational data.
Connect operating capacity to capital
The company was preparing for growth equity.
Talbot West tied the modernization sequence to the capital questions leadership and investors needed answered:
Leadership could see what to fund first, what to defer, what each investment depended on, and which new capabilities each investment unlocked.