Cloud platforms that bring building systems, asset telemetry and services into one operating picture your portfolio can grow on.
- Platform architecture for connected building systems
- Asset and sensor data integration
- Engineering for scale, reliability and secure operation
One harmonized ontology across assets, suppliers, parts and contracts, built for AI to consume as readily as your systems.
- Asset and vendor data harmonization at scale
- Semantic and LLM-layer record matching
- Pricing and contract data normalization
AI-assisted triage, routing and resolution that keeps ticket queues falling while the portfolio grows.
- AI triage and routing of work orders
- Knowledge-grounded service desk assistants
- Resolution ahead of the ticket
Contracts, SLAs and compliance documents extracted, tracked and surfaced before deadlines instead of after incidents.
- Contract and SLA extraction at scale
- Obligation and renewal tracking
- Exception routing to human reviewers
Sourcing and spend analysis as an on-demand answer rather than a weeks-long manual exercise.
- Spend and supplier analysis on demand
- Category and sourcing insight
- Decision support grounded in your data
RAG-grounded assistants that give technicians cited answers from manuals, histories and contracts, wherever they are.
- Copilots grounded in your documentation
- Cited, auditable answers by default
- Built for mobile, on-site use
Connected Spaces · 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 portfolio
Our Approach
- Cloud platform architecture for connected devices
- Device and service integration across the ecosystem
- Engineering for scale, reliability and secure operation
Outcomes
Asset 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
Service Operations· Delivered in Food Services · AI Validation and Support Relief
The Challenge
- Manual, error-prone operational data entry
- Content slow and costly to produce
- Bad data driving support tickets
Our Approach
- AI validation of data before it reaches operational systems
- AI content generated on demand
- Cloud signage and systems integration
Outcomes
Production-Grade Delivery
Human in the Loop, Always
Uptime as a Design Input
Production, Not Pilots
Discover
Design
Build
Run & Scale
Yes. We build platform-native in your cloud accounts, and systems ship with the controls your auditors expect: access management, logging and audit trails designed in from the architecture stage, not retrofitted.
Agents draft, extract and propose. Your subject matter experts approve. Review checkpoints are part of the system architecture, agreed in the Design phase, so oversight is enforced by the workflow rather than by policy documents.
Evaluation criteria are agreed before build and run continuously in production. Guardrails, observability and cited sources keep every AI decision path measurable and traceable back to the material it came from.
We design for your data staying in your environment and under your control. Retrieval-grounded systems answer from your governed sources and cite them, so responses stay explainable to your teams and your partners.
With one use case. A senior architect maps it with your team, and you get a value case leadership can sign before any build begins. The four-phase path above is the whole journey.
