Pre-built AI
Ready to Deploy at Scale
Go live in days, not months with our ready-to deploy and production‑grade Predictive Maintenance, Digital Twins, Vision Analytics and Conversational AI for Critical Industries.
Pre-built AI models remove the slow, risky parts of AI adoption: data wrangling, custom pipelines, endless tuning and compliance fire drills; so, you can get to outcomes faster. They are lightweight, production‑proven, and portable across your stack, with built‑in guardrails, validation, and documentation. Instead of assembling teams to reinvent core capabilities, you configure, integrate, and deploy to go live in days, not months. Designed for the edge and for real industry needs, these models balance speed with control. Choose fully pre‑trained or bring your data to customizable pipelines, align with regulatory requirements out of the box, and monitor performance with transparent metrics. For Manufacturing, Retail, Utilities, Oil & Gas, Ports & Terminals, and Smart Cities, you get battle‑tested patterns for Conversational AI, Predictive Maintenance and Digital Twins; so you start from best practices, not a blank slate.
From pre-built models to enterprise value - delivered fast, safely and at scale.
Lower Talent Burden
You don’t need a large in‑house data science/ MLOps team to get results. Pre‑built models encapsulate the hard parts - algorithms, feature engineering, scoring code—so your teams configure and deploy instead of building from scratch.
Compliance Ready by Design
Regulatory needs vary by region and industry. Pre‑built models are engineered with safeguards and governance patterns aligned to common standards, making it easier to deploy responsibly across jurisdictions.
Flexible for Your Stack and Data
Choose between fully pre‑trained models or customizable pipelines you can adapt to your data. Lightweight, portable packages integrate with legacy systems and scale in the cloud—without re‑architecting your environment.
Proven for Your Verticals
Manufacturing, Retail, Utilities, Oil & Gas, Ports & Terminals, and Smart Cities benefit from battle‑tested patterns for Conversational AI, Predictive Maintenance, and Digital Twins and many more - so you start from best practices, not a blank slate.
Human‑in‑the‑loop Control
Keep experts in charge of high‑impact decisions with review queues, approvals and escalation paths to balance automation with safety, transparency and accountability.
Trustworthy and Observable AI
With built‑in validation, monitoring, and transparent model documentation, you can track performance, reduce bias, and maintain quality as you evolve—supporting people‑in‑the‑loop where it matters.
Pre-built models for Real-time Operations
Our catalogue focuses on the outcomes that matter in Manufacturing, Retail, Utilities, Oil & Gas, Ports & Terminals and Smart Cities. Each model is production ready with pre validated data schemas, guardrails, and deployment patterns - so you plug into your stack, tune to your data, and go live in days, not months.
Below are a few high impact models; spanning Conversational AI, Predictive Maintenance and Digital Twins and more. They were built to reduce risk, speed time to value, and scale confidently across sites and regions. We’ll show what each model does, the inputs it needs, and how it deploys (API, web, or on prem) so you can pick the fastest path to impact.
Pre-Built AI Models
Agentic AI
Autonomous agents that understand goals, reason across systems, and take safe, compliant actions.
Outcomes:
- Automate multi step processes beyond single tasks
- Surface overlooked insights across silos
- Reduce response times in critical operations
Inputs: Operational data streams, control room systems, sensor feeds, enterprise knowledge bases
Deployments: Orchestrator dashboard, APIs, integrations with workflow tools, edge + cloud hybrid agents
Integrations: SAP, Maximo, OSIsoft PI, ServiceNow, Teams/Slack, SCADA systems
Time to Go-live: 14 – 30 days
Safety & Control: Human in loop, escalation rules, approval gates, policy guardrails, audit logs
Example use cases:
- Automated incident response in Utilities
- Oil & Gas anomaly detection + mitigation
- Port operations: scheduling, logistics, exceptions
- Smart Cities: traffic optimization, emergency routing
Digital Twin
Real time operational twins to simulate, forecast, and optimize complex assets and sites.
Outcomes:
- Reduce downtime and energy costs
- Optimize throughput and resource use
- Test scenarios before deploying
Inputs: Sensor/SCADA, historian, ERP/MES, maintenance logs, weather
Deployments: Edge/on prem, cloud API, control room dashboard
Integrations: OSIsoft PI, Ignition, SAP, Azure IoT, Kafka
Time to Go-live: 10 - 20 days
Safety & Control: Read-only sims, approvals for autonomous actions
Example use cases: Plant tuning (Manufacturing), grid balancing (Utilities), yard ops (Ports)
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Predictive Maintenance
Predict failures early and schedule fixes to cut unplanned downtime.
Outcomes:
- Fewer failures and truck rolls
- Higher asset uptime
- Lower spare parts cost
Inputs: Vibration, temperature, pressure, cycles, error codes, CMMS
Deployments: API to CMMS, edge scoring, operator UI
Integrations: Maximo, SAP PM, ServiceNow, OSIsoft PI
Time to Go-live: 7 - 14 days
Safety & Control: Confidence thresholds, HITL review queues
Example use cases: Rotating equipment (Oil & Gas), line assets (Manufacturing), fleets (Smart Cities)
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Conversational AI
Domain tuned assistants for ops, support, and field teams.
Outcomes:
- Faster responses and resolutions
- Lower ticket load
- Consistent, compliant answers
Inputs: Knowledge base, SOPs, manuals, tickets, telemetry summaries
Deployments: Web widget, mobile, Slack/Teams, API
Integrations: Zendesk, ServiceNow, SharePoint, Confluence, Teams/Slack
Time to Go-live: 3 - 7 days
Safety & Control: Grounding, redaction, audit trails, escalation
Example use cases: Technician assistant (Utilities), port ops (Ports), store copilot (Retail)
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Vision Analytics
Computer vision for safety, quality, inventory, and site awareness.
Outcomes:
- Fewer defects and incidents
- Real time alerts and insights
- Better inventory accuracy
Inputs: CCTV/edge cameras, drone imagery, line cameras
Deployments: Edge inference, VMS integration, cloud batch
Integrations: Milestone, Genetec, ONVIF, custom RTSP
Time to Go-live: 10 - 21 days
Safety & Control: Privacy zones, retention policies, audit logs
Example use cases: PPE/compliance (Manufacturing), yard analytics (Ports), shelf availability (Retail)
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Custom Models
Bring your data and we tailor pre-built pipelines to your problem.
Outcomes:
- Fit-for-purpose accuracy
- Faster than net new builds
- Governed, maintainable MLOps
Inputs: Your domain data and systems of record
Deployments: Your preferred target (cloud/on prem/edge)
Integrations: Aligned to your stack and policies
Time to Go-live: 14 - 30 days
Safety & Control: Model cards, approvals, versioning, rollback
Example use cases: Demand sensing (Retail), microgrid optimization (Utilities), berth scheduling (Ports)
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