Raven.ai’s implementation process is designed to be fast, guided, and minimally disruptive to production. Although the company does not publicly state an exact total deployment time, its documentation and installation guides show a clear step‑by‑step setup structure that supports a rapid rollout.
1. Initial Setup & Preparation
The process begins with preparing the plant for installation using Raven’s “implementation checklists and guides,” ensuring that network, hardware, and sensor requirements are in place.
2. Connecting Hublets or IO‑Link Devices
Raven’s hardware units (Hublets or IO‑Link Masters) are installed to capture machine signals. Each Hublet can monitor up to four digital signals, while IO‑Link Masters support up to eight IO‑Link or analog signals, or sixteen digital signals. Power and network are set up via Wi-Fi or Ethernet depending on the device.
3. Establishing Network Connectivity
The devices are connected either through Wi-Fi (Hublets) or hardwired Ethernet (IO‑Link Masters). Raven provides Wi‑Fi adapters or Hublet-based alternatives if certain connectivity options are unavailable.
4. Deployment of Operator Smart Assistant Tablets
Tablets used as Smart Assistants are connected via Wi-Fi or USB‑C Ethernet adapters. These give operators the interface to tag downtime and provide context.
5. Data Capture Activation
Once hardware is installed, Raven begins pulling machine signals to create a live timeline of production events. Contextual data is added using automated downtime prompts and operator input.
6. Analytics and Dashboard Configuration
Raven’s reporting platform begins to display real-time data, historical trends, and contextualized timelines. This gives teams instant visibility as soon as initial data flows stabilize.
7. Training & Continuous Improvement Rollout
Frontline, supervisors, and leaders are guided in using dashboards, alerts, and Smart Assistants to drive continuous improvement. This phase blends onboarding with operational use.
Raven.ai heavily emphasizes fast deployment and “getting started quickly,” but does not publish the exact installation duration in days or weeks. The presence of quick‑install guides, simple wiring requirements, and browser‑accessible dashboards suggests a rapid implementation, often achievable in a short time frame depending on the site’s machine count and network readiness.
Raven.ai provides a high degree of customization across data capture, context, analytics, and reporting. Multiple verified data points confirm this flexibility:
Raven.ai offers a reporting platform with customizable dashboards accessible from any browser. Users can tailor visualizations, performance metrics, and historical analyses to match operational priorities.
The platform integrates with PLCs, sensors, machine signals, ERP systems, and MES systems. This allows manufacturers to build a data environment tailored to their factory setup.
Businesses can choose Hublets, IO‑Link Masters, or mixed setups depending on machine type, signal availability, and network constraints. This ensures compatibility with different manufacturing footprints.
Raven captures 100% of production time through customizable downtime labeling and operator input. Each manufacturer can tailor downtime categories, tagging rules, and workflow requirements to match their processes.
Raven supports expansion across multiple machines, production lines, and full facilities, allowing companies to scale the deployment as their needs evolve.
Operator Smart Assistants can be configured to prompt workers only under specific conditions or for certain machine states. This minimizes operator workload while maximizing contextual accuracy.
Raven’s machine learning engine, Raven Brain™, performs tailored analysis based on the manufacturer’s machine data and operational patterns, helping plants identify unique root causes and improvement opportunities.
Whether plants use Wi-Fi, hardwired Ethernet, USB‑C adapters, or mixed environments, Raven adapts to existing IT and OT infrastructure without requiring full replacements.
Raven.ai does not publicly list specific setup fees or maintenance charges, but available pricing documentation provides strong clues about cost structure.
Raven.ai offers tiered plans—Core, Action, and Premium—and notes that pricing scales based on factories, assets, and digital transformation goals. This implies that additional costs may vary depending on integrations, the number of machines, and deployment complexity.
All plans include support from Raven’s Customer Success team, technical documentation, and installation guides, suggesting that basic support and implementation assistance are included, not billed separately.
A key cost indicator comes from GetApp, noting that Raven’s basic bundle starts at $199 per machine per month, and higher-tier plans include add‑ons and customization, which likely influence total cost. However, no published fees for setup, maintenance, or premium support appear in any verified source.
Raven.ai provides extensive training and support resources to help manufacturers onboard quickly and maintain smooth operations.
The platform offers documentation, in‑person training, live online training, videos, and webinars, according to SelectHub’s verified listing.
Support offerings include email, phone, chat, FAQ, forum access, help desk, knowledge base, tickets, and 24/7 live support, covering all major support channels manufacturers typically need.
Additionally, Raven’s pricing page confirms that all plans include help guides, technical support, step‑by‑step documentation, and a dedicated Customer Success team composed of experienced manufacturing professionals. This team helps with onboarding, continuous improvement strategy, and maximizing frontline adoption.
Raven's installation hub also provides how‑to documentation, installation manuals, and quick‑install guides for connecting machines and setting up Smart Assistants, supporting smooth deployments.
Raven.ai does not publish a fixed update schedule (e.g., weekly or monthly), but their support and product ecosystem clearly shows that the platform is updated continuously, with changes documented through their support resources.
Raven provides a Change Log where platform updates and new features are regularly posted, indicating an ongoing update cycle that evolves as new improvements are rolled out. Users can access these update notes through the “What’s New in Raven?” section of the support portal, which highlights product changes as soon as they are released.
Updates are managed through cloud deployment, meaning improvements to dashboards, Smart Assistants, reporting features, and analytics are delivered automatically without requiring plant‑level reinstallations. Their installation resources and support pages show that hardware components (like Hublets or IO‑Link devices) integrate seamlessly with software updates, making version management largely centralized and automated.
Raven.ai’s pricing and plan structure is explicitly designed for scalability. Their pricing page states that plans “align with your digital transformation goals, processes, number of factories and assets,” meaning the platform supports both scaling up and scaling down depending on machine count or facility needs.
Users can move from Core → Action → Premium tiers to unlock additional features such as real‑time alerts, gamification, integrations, and Automated Downtime Labeling. This upward scaling is designed for organizations expanding continuous improvement programs or adding more connected assets.
Raven also offers a Pilot Program, which lets companies start small (up to 5 assets) and expand after demonstrating ROI. This is a direct indicator of scalable licensing.
No public policy specifies penalties or minimum commitments for reducing machines or downgrading tiers. However, because pricing is tied to per-machine/per asset subscriptions, organizations can reduce costs by removing connected assets or shifting to a lower tier if their needs decrease.
Higher tiers include integrations and automation capabilities, meaning companies can scale their digital infrastructure as their maturity increases rather than adopting everything at once.
Based on Raven.ai’s official Terms of Service, the platform provides clear conditions for subscription renewal and cancellation.
The standard subscription length is 1 year, unless otherwise specified in a proposal or quote.
Contracts automatically renew unless the customer provides a notice of non‑renewal.
The Terms specify a mandatory non‑renewal notice period of at least 60 days before the end of the current term.
To stop auto‑renewal, customers must send a written non‑renewal notice no later than 60 days before renewal.
If no notice is given, the subscription automatically renews for another full term.
Payment is due within 30 days of receiving the invoice.
These timelines indirectly affect cancellation, since renewal triggers a new invoice.
If a customer signs a separate “Cover Page” agreement, those terms override the general Terms of Service.
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