SolarisAI integration that reaches the systems other tools can't.
Connect SolarisAI to every CMMS, EAM, SCADA and AI agent your reliability team runs on. Turn machine-learning anomaly scores and predicted failures into an automatic work order, with condition data unified in an Industrial AI Data Fabric.
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Live demo · Claude querying SolarisAI + ops via Rayven MCP
Trusted by 240+ teams across Australia + globally
SolarisAI is brilliant at what it does. Useless at everything else your data + AI needs to touch.
SolarisAI scores the anomaly and predicts the failure, but the result stays in its dashboard while the CMMS waits. Health scores never reach finance, and the wider AI estate never sees the predictions.
The integration tool you've already tried probably can't fix it.
App-to-app. Useful, until it isn't.
Connectors for SolarisAI, Slack + a thousand other cloud apps. Cheap + fast for the easy half of integration. Where they hit a wall:
- CMMS that should raise a work order from a SolarisAI anomaly or predicted failure
- SCADA, historians and sensor feeds that must reach the SolarisAI models at once
- EAM and ERP needing asset-health scores tied to the asset and maintenance cost
- Data warehouses and AI agents needing live anomaly, health-score and prediction signals
SCADA, historians, CMMS, sensors + AI. One platform.
The integration platform built for what other tools can't (or won't) reach - plus an AI data fabric, MCP server + app builder layered on top.
- SolarisAI + every CMMS, EAM and SCADA system
- Sensors, SCADA, historians, CMMS, IoT + custom-built connectors.
- Files, legacy SQL, FTP + custom-built connectors
- Real-time bidirectional sync, tier-aware + rate-limit-safe
- AI Data Fabric, MCP, automation + custom apps included
SolarisAI + Rayven: AI, automation + tools that reach every system you run.
4 examples of what Rayven customers run on SolarisAI + integrated systems. Built in weeks, not months.
Anomaly raises the work order
A SolarisAI anomaly score or predicted failure raises a work order in your CMMS automatically, with the asset, predicted failure and evidence attached. The model output turns into scheduled maintenance.
Live signals feed the models
SCADA tags, historian trends and sensor readings stream into SolarisAI over OPC-UA and REST, so its machine-learning models score on the full live signal set rather than a batch export.
Health score meets the asset record
Asset-health scores and predicted failures post to EAM and ERP against the asset and cost centre, so reliability and finance judge the asset on one record.
Prediction outputs, AI-ready
Every anomaly score, health score and predicted failure streams into Rayven's Industrial AI Data Fabric. AI agents query fleet-wide risk and blend SolarisAI with other models across the estate in real-time.
Integration is the start with Rayven.
Here's what comes with it.
Rayven isn't just a SolarisAI connector. It's the operational software platform underneath - so once SolarisAI is connected, four more capabilities come online by default.
AI-ready data layer (AI Data Fabric)
SolarisAI data joined with ERP, IoT + legacy - contextualised, unified and structured so AI models, agents and tools can use it without ETL prep work.
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Live AI access (Rayven MCP)
Claude, ChatGPT + Gemini get live, governed access to SolarisAI and every other connected system. Your AI stops guessing - cites real SolarisAI records + numbers.
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Automation + AI agents
Workflows + AI agents act on SolarisAI data without human intervention - escalate at-risk accounts, trigger operational work, auto-update forecasts, draft customer comms.
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Custom apps + portals
Unified customer portals, ops dashboards, mobile field apps, partner portals - built on top of integrated SolarisAI data. No separate BI tool, no separate dev stack.
Learn more →
All on top of your existing stack. No rip + replace. SolarisAI stays SolarisAI. Rayven works on what you've already built. Specifically tuned for SolarisAI anomaly routing and health-score mapping into the CMMS.
Rayven is a five-layer platform ALL your integrations + much more
can run on.
Integration is one layer of Rayven. Data, execution, presentation + governance are the other four - all delivered as one platform on one commercial.
Pick the right tool for your stack.
SolarisAI integration looks different at every scale. Honest comparison of the four common paths - Rayven only wins on some of them.
The integration is the easy bit.
The platform + team behind it is the difference.
Platform + team. One commercial.
Not five vendors stitched together. Rayven is the platform AND the Australia-based expert team that scopes, builds + supports it. One commercial. No licence stacking, no finger-pointing.
Built for SolarisAI's machine-learning models.
Rayven reads SolarisAI anomaly scores, health scores and predicted failures over its REST API with API-key auth, mapping each to the asset natively. Score-to-priority mapping raises a real-time CMMS work order while live SCADA and sensor feeds reach the models via OPC-UA for full-signal scoring.
We stay after go-live.
No handoff. No disappearing. Rayven is a long-term partner when your SolarisAI evolves, your stack changes, or you push further. 24/7 support. Same team, same platform, same commercial.
Hosted your way, where you need.
Deploy as cloud, private cloud + on-premise - in Australia, the US, the UK, or anywhere else your SolarisAI data needs to live. Your residency, your rules, your local compliance environment.
The questions SolarisAI admins, RevOps + IT ask first.
If you're evaluating Rayven for SolarisAI integration, these are the things worth knowing before booking a call.
The 30-minute call covers
- Your SolarisAI + connected stack today
- What's reachable + which systems to bring in first
- Live walkthrough of Rayven against your scenario
- Time, scope + delivery estimate
- Honest read on whether Rayven's the right fit
What is SolarisAI integration?
SolarisAI integration is the practice of connecting SolarisAI to the rest of your reliability stack - CMMS, EAM, SCADA and AI - so its anomaly scores drive work and reach every system. Rayven delivers it as part of an Industrial AI Data Fabric, not a single-purpose connector.
How does Rayven connect SolarisAI to other systems?
Rayven uses SolarisAI's REST API for real-time sync. Anomaly scores, asset-health scores, predicted failures and asset metadata flow as first-class integration events into your CMMS. See the Rayven Platform for how integration and data layers fit together.
Can Rayven raise a work order from a SolarisAI anomaly?
Yes. A SolarisAI anomaly or predicted failure raises a work order in your CMMS automatically, with the asset and predicted failure attached. The model output becomes scheduled work rather than a dashboard alert.
Does Rayven replace SolarisAI?
No. SolarisAI stays your machine-learning prediction engine. Rayven connects its outputs to the CMMS, EAM and AI, feeds live signals in and unifies its scores with other techniques. Rayven complements SolarisAI by making its predictions actionable everywhere.
How long does SolarisAI integration take with Rayven?
Most SolarisAI integrations go live in 2-12 weeks. A single SolarisAI-to-CMMS or SCADA-to-SolarisAI flow runs in 2-3 weeks; a full multi-site prediction fabric runs 6-12 weeks. Choose DIY, done-for-you or hybrid delivery.
What are the technical specifics of SolarisAI integration with Rayven?
Rayven integrates SolarisAI through its REST API, authenticated with API keys. Machine-learning anomaly scores, asset-health scores, predicted failures and asset metadata are read in real-time and mapped against the asset, so a prediction carries failure mode and priority into the CMMS. Score-to-priority rules turn model outputs into correctly ranked work orders. Rate limits are managed through batching and back-pressure so scoring pulls never throttle out. Model thresholds, asset identifiers and health-score attributes are preserved with field-level mapping into EAM and ERP targets. Upstream, SCADA tags, historian trends and sensor readings reach the SolarisAI models via OPC-UA and REST for full-signal scoring rather than a batch export. SolarisAI outputs unify with vibration, oil and thermography verdicts against one asset model. Validated against the SolarisAI platform across sensor and process-data sources. Rayven reads condition data and triggers work; it never issues control commands to plant.
SolarisAI + AI integration.
In weeks, not months.
Book a 30-minute call. Walk away with a tailored plan - what's reachable, what to bring in first, time + scope.