iBASEt announced general availability of Solumina AI, positioning it as the only artificial intelligence platform purpose-built specifically for regulated aerospace and defense manufacturing environments. The platform debuts with four AI-powered modules—Solumina ScanAI, Solumina Digital SME, Solumina Intelligence, and Solumina PulseAI—which are embedded directly within the Solumina Manufacturing and Sustainment Operations Platform.
The release represents a direct challenge to ERP and PLM vendors that have adopted horizontal AI strategies by bolting general-purpose large language models onto existing systems. According to a Gartner prediction, by 2027 organizations will use small, task-specific AI models three times more than general-purpose LLMs due to faster response times, lower computational requirements and reduced operational costs.
How Domain-Specific AI Changes Manufacturing Operations
For technology executives managing complex aerospace manufacturing environments, Solumina AI fundamentally alters daily operational workflows by embedding intelligence directly into manufacturing execution systems rather than requiring data extraction to external analytics platforms. The architecture operates within secure, self-contained environments supporting air-gapped and restricted deployments, with embedded LLMs running in customer-controlled cloud or on-premises infrastructure.
The four modules address specific operational bottlenecks that persist across aerospace manufacturing. Solumina ScanAI converts paper-based work instructions and records into structured, compliant digital data integrated directly into workflows, reducing manual data entry while improving audit readiness and lowering cost of poor quality. As a result, Solumina Digital SME functions as an AI-enabled assistant that improves first-pass quality and accelerates workforce onboarding by delivering instant, context-aware guidance and best practices.
Solumina Intelligence enables faster decision-making through on-demand insights into throughput, schedule adherence, quality metrics, and operational risk without requiring data science expertise, allowing leaders to identify issues earlier and reduce schedule surprises. Solumina PulseAI provides AI-assisted dashboarding that increases shop floor visibility with at-a-glance overviews of production status, workforce readiness, skills, and certifications, enabling supervisors to proactively address workforce constraints.
Impact for Aerospace, Defense Markets
The broader market context reveals growing recognition that generic AI fails in aerospace due to complex workflows, compliance requirements, and supplier risks that demand domain-specific agents. Aerospace manufacturers face converging pressures including labor shortages, fragmented supply chains, growing compliance data volumes, and operational complexity.
When evaluating AI platforms for manufacturing execution systems, executives should prioritize solutions that demonstrate traceability to the manufacturing record, support restricted and air-gapped environments, and align with industry-specific compliance frameworks. The platform must integrate with existing PLM, ERP and MES infrastructure without requiring wholesale system replacement.
Best practices for integrating AI into aerospace manufacturing operations emphasize maintaining digital thread continuity from design through production to sustainment. iBASEt’s approach builds on model-based enterprise capabilities with persistent mapping of PLM objects, 3D models, and manufacturing data, enabling synchronized “tri-lighting” between 3D models, data collection and instructions during execution.
Common challenges include overcoming resistance to AI adoption in highly regulated environments where risk aversion dominates decision-making, establishing governance frameworks that balance automation benefits with audit requirements, and addressing workforce concerns about AI replacing human expertise rather than augmenting it. Organizations succeeding with domain-specific AI focus on use cases that demonstrably reduce repetitive work while preserving human oversight for critical decisions affecting safety and compliance.
What This Means for ERP Insiders
Vertical AI platforms threaten horizontal ERP AI strategies in regulated industries. iBASEt’s domain-specific approach exposes fundamental limitations in bolting generic AI onto broad ERP platforms, particularly where compliance, traceability, and industry-specific workflows are non-negotiable. Generic ERP AI assistants designed for cross-industry business processes cannot safely navigate aerospace’s AS9100 quality requirements, ITAR restrictions, or complex certification workflows without introducing compliance risk.
Embedded AI within operational systems reshapes integration architecture. By deploying LLMs directly within manufacturing execution platforms rather than extracting data to external analytics environments, Solumina AI demonstrates an architectural pattern that reduces latency, preserves security boundaries, and maintains data sovereignty in restricted environments. This approach contradicts the centralized data lake strategy many ERP vendors promote, where operational data flows to hyperscale cloud platforms for AI processing.
Task-specific AI models accelerate faster than general-purpose alternatives. The prediction that organizations will use task-specific AI models three times more than general-purpose LLMs by 2027 fundamentally challenges investment priorities for ERP vendors developing AI capabilities. Rather than pursuing ever-larger foundation models with broad capabilities, successful vendors will invest in curating high-fidelity domain datasets, building industry-specific ontologies, and training specialized models for manufacturing workflows.
