AI advisory plus solution engineering for generative AI. We benchmark your knowledge, content, and process landscape, then build domain-tuned generative-AI systems — copilots, agents, document intelligence — that operate inside your data perimeter with the precision your operations demand.
Generic large-language models are useful for general knowledge — they are not enough for an industrial enterprise. Our generative-AI practice begins with benchmarking: which workflows, which document classes, which operator interactions are good candidates for AI augmentation, and at what accuracy threshold do they create real value.
From there our solution engineers build production-grade systems grounded in your bills of materials, SOPs, maintenance logs, and supplier contracts — using retrieval-augmented generation, fine-tuning, and tool-using agents that deliver answers and actions, not just text. Every deployment is governed for hallucination, observability, and human-in-the-loop checkpoints on high-stakes decisions.
A working catalogue of the systems, models, and platforms our engineers ship within this practice — selected for industrial reliability, observability, and scale.
Conversational assistants that read your manuals, work orders, and SOPs to guide technicians on the floor in real time.
Tool-using agents that read sensors, query systems, take actions, and escalate to humans only when policy requires.
Extract structured data from invoices, contracts, certificates, and engineering drawings at industrial scale.
Generate labelled training data for vision and language models when real-world data is rare or sensitive.
Enterprise-wide RAG over engineering wikis, post-mortems, lessons learned — the tribal knowledge.
AI-assisted PLC code drafting, technical specification, and CAD parameter exploration with engineering review.
Representative deployments across our industrial client base. Each grounded in production engineering — not concept slides.
Multilingual conversational assistant reading decades of maintenance manuals, work orders, and OEM bulletins to walk technicians through diagnosis and repair on equipment whose original engineers have retired.
Extract obligations, penalty clauses, escalators, and SLA commitments from thousands of supplier contracts. Surface conflicts, expirations, and negotiation leverage.
Conversational interface over historical defect logs, FMEAs, and process data — proposes ranked hypotheses with evidence trails, accelerating 8D and CAPA cycles.
Natural-language interface to demand, capacity, and inventory simulations. Executives ask "what if Tier-2 supplier X is offline for six weeks" and get fully-cited scenarios in seconds.
Generative agent proposes parameter sweeps for new product introduction, drawing on prior experiments and physics constraints, dramatically shrinking DoE cycle times.
Generate first drafts of technical files, validation reports, and audit responses grounded in your QMS and regulatory precedent — with redline review by humans.
Customer-facing agent that handles tier-1 service requests, places orders, schedules technicians, and escalates with full context only when policy requires.
Where real defect samples are too rare to train on, generate photorealistic synthetic defects with verified annotations to train production CV models.
Tools, frameworks, and platforms our engineers use day-to-day in this practice.
Every Pentaaxis engagement starts with a structured benchmarking conversation — no obligation, a senior engineer in the room, and a calibrated view of where AI moves the needle for your organization.