Cloud platforms that bring products, equipment telemetry and services into one operating picture your lines and fleets can grow on
- Platform architecture for connected products and equipment
- Telemetry and service data integration
- Engineering for scale, reliability and secure operation
One harmonized ontology across parts, suppliers, pricing and bills of materials, built for AI to consume as readily as your systems.
- Parts and supplier data harmonization at scale
- Semantic and LLM-layer record matching
- Pricing and contract data normalization
Agentic analysis across plant, quality and enterprise reports, turning scattered documents into decisions with sources attached.
- Document understanding across operational reports
- RAG grounding against your enterprise knowledge
- Validated, self-checked analysis outputs
Specifications, certifications and supplier documents extracted, tracked and surfaced before audits instead of during them.
- Spec and certification extraction at scale
- Obligation and renewal tracking
- Exception routing to human reviewers
AI-driven test generation across embedded software, applications and integrations, for release confidence at industrial scale.
- End-to-end test architecture across the stack
- AI test generation for deeper coverage
- Automation woven into release pipelines
RAG-grounded assistants that give technicians cited answers from manuals, histories and specs, at the line and in the field.
- Copilots grounded in your documentation
- Cited, auditable answers by default
- Built for mobile, on-site use
Connected Products· Smart Home · Cloud Platform for Smart Home Solutions
The Challenge
- A growing fleet of connected devices
- Device, user and service data across many touchpoints
- A platform expected to scale with the product line
Our Approach
- Cloud platform architecture for connected devices
- Device and service integration across the ecosystem
- Engineering for scale, reliability and secure operation
Outcomes
Product Data · Delivered in Food Services · Catalog Harmonization at Extreme Scale
The Challenge
- The same product described differently across every source
- Manual, time-intensive matching across catalogues and formats
- Complex pricing across millions of combinations
Our Approach
- Document processing capturing product and pricing data at scale
- Attributes normalized to a unified ontology
- Record matching with attribute, semantic and LLM layers
Outcomes
Decision Intelligence· Delivered in Enterprise Advisory · Agentic CIO Advisor
The Challenge
- Enterprise data scattered across many reports
- Limited access to senior-level expertise
- Manual analysis slowing strategic decisions
Our Approach
- Document understanding across unstructured reports
- RAG grounding against an enterprise knowledge base
- An orchestrator running analysis, validation and synthesis
- A reflection agent self-checking every output
Outcomes
Production-Grade Delivery
Human in the Loop, Always
Volume as a Design Input
Production, Not Pilots
Discover
Design
Build
Run & Scale
No. We work across the systems your plants already run and harmonize the data between them.
Yes. Document AI reads the specs, certificates and records you already hold, and the ontology reconciles naming that drifted apart over decades.
Nothing silent. Copilot answers carry their source, and anything that acts on operations runs behind validation and human sign-off.
The architecture is planned around site realities: copilots built for mobile use, and integrations designed for how your plants actually connect.
Data stays in your environment under your access controls, with partner-level separation designed into the data model.
