What is the Rayven AI Data Fabric?
The Rayven AI Data Fabric is the unified data + AI plane that connects every system, structures every data type, and powers AI capabilities across every layer of your operations - predictive ML, gen AI, AI agents, conversational analytics + AI-led execution. It is the data foundation production AI requires, plus the delivery engine to ship it. Learn more about the Unified Data Platform that powers it.
Why do I need a data fabric for AI?
Because AI is only as good as the data underneath it. Most AI projects fail because the data feeding the models is fragmented, stale + ungoverned. A data fabric unifies + structures your data in real time, so AI has the substrate it needs to actually work in production.
What is The Rayven AI Pilot?
The Rayven AI Pilot is a 6-12 week, fixed-scope engagement that takes one priority AI use case from scoping to production. Defined success metric, defined timeline, built-in conversion path to license + extension. The fastest way from “AI is on the roadmap” to “AI is in production”. Talk to us to scope your pilot.
What is “shadow AI” and how does Rayven solve it?
Shadow AI is what happens when staff start using AI tools (ChatGPT, Copilot, Cursor, custom GPTs) without IT, security or compliance oversight - pasting customer data, exposing IP, creating audit gaps. Rayven provides the sanctioned alternative: a governed AI environment with sovereignty, audit + access control built in. See how the Rayven Security layer enforces governance at every level.
How is Rayven different from C3.ai, Palantir AIP or DataRobot?
All three are AI-first platforms - heavy, consulting-led, slow to deploy. Rayven is an integrated platform where AI lives inside every layer. You get AI plus everything else operational software needs, on one platform - and you can build it yourself, have us build it, both, or pilot first. Time to production: 2-12 weeks vs. 6-18 months. Explore the full Rayven platform.
How is custom AI different from ChatGPT or Microsoft Copilot?
ChatGPT + Copilot are generic LLMs trained on the public internet. They do not know your products, customers, processes or data. Custom AI on Rayven is trained + grounded on your operational data, connected to your systems via the integration layer, governed by your rules + embedded in your workflows so the AI’s output drives real action - auditable + defensible.
What does “real-time model training” mean on Rayven?
Three things - all supported: (a) Online learning - models update as new data streams in; (b) Continuous retraining - scheduled pipelines retrain on fresh data + auto-redeploy; (c) Real-time deployment - models execute against live data, not batched exports. This is powered by the Rayven Data layer and delivered through the Execution layer.
What multimodal data can Rayven AI handle?
All of it: structured (databases, CSVs, APIs), documents (PDFs, forms, contracts), video (CCTV, drone, inspection), images (defect, satellite, vision sensors), audio (voice, calls, sensor sound), streaming (MQTT, Kafka, telemetry). All ingested into the same unified data fabric.
Can we use our own LLMs?
Yes. Rayven connects to OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock + open-source (Llama, Mistral, etc.) via the integration layer. LLMs are swappable per use case + governable per workflow. No vendor lock-in.
Where does my data go when using Rayven AI?
Wherever you decide. Rayven deploys on SaaS (managed Azure), private cloud (your AWS / Azure / GCP), on-premise, or edge. You control data residency, retention + sovereignty. No data goes to LLM providers without explicit configuration. Your data is never used to train external models. Read more about Rayven’s security + data sovereignty controls.
How do you handle hallucinations + AI mistakes?
Rayven AI is grounded on your data (retrieval, structured queries + tool use), versioned, audited + scoped. Every AI output is logged, explainable + source-traceable. Human-in-the-loop approval is configurable for high-stakes decisions. The Security layer enforces audit trail, access control + explainability across all AI workflows.
How does AI integrate with our existing systems?
Rayven has hundreds of connectors (SAP, Salesforce, Oracle, Microsoft, Snowflake + more) plus a custom integration framework. AI agents + models read from + write to your systems through the integration layer - bidirectionally, in real time. Explore the Rayven Integration Engine.
Can we white-label AI products built on Rayven?
Yes. Every AI capability can be deployed under your own domain, brand + visual identity - for internal teams, partners + customers. Ship AI as a product your customers use, under your name. Talk to us about white-label AI delivery.
Etiko, CEO, Machinery
Gavin, CEO
Margarita,
Rob, CEO
Jeffrey, Product Supervisor,
