Sold by: Rhino.ai
Deployed on AWS
Rhino.ai is an AI-powered platform which delivers faster modernization, lower costs, reduced tech debt, and higher-quality enterprise applications through automated discovery, documentation, and requirements generation with full traceability and flexibility. It automatically extracts code, documents, and workflows, organizes the most important business application context and logic into a patented platform-agnostic representation where the application can be re-engineered, and outputs agent-ready, modern application requirements suitable for microservices-based open-source implementations as well as low-code platforms like ServiceNow, Appian, etc.
Overview
Rhino.ai is an AI-powered modernization platform that turns legacy black boxes into fully understood, agent-ready applications. It accelerates transformation, reduces costs, cuts technical debt and improves application quality by automating discovery, documentation and requirements generation with full traceability and flexibility.
Comprehensive Discovery & Documentation Rhino.ai rapidly analyzes and documents complex legacy enterprise applications--including SaaS, low-code and traditional codebases--to build complete visibility across your technology landscape. Its agentic AI extracts business logic automatically from existing code, documentation, databases and workflows, capturing hidden dependencies and inefficiencies. Rhino.ai analyzes legacy code bases, SaaS platforms, natural-language documentation and process manuals, giving you multi-perspective clarity. The platform extracts requirements, process flows and knowledge from technical specs, user manuals and process documents, and it tracks code structures, database schema and APIs across your portfolio.
Intelligent Documentation & Traceability Discovery results are organized into comprehensive deliverables that support multiple personas. Rhino.ai generates universal application documentation, user stories, test cases and process flowcharts, along with functional documentation, technical architecture mappings, business-rule extractions, modernization roadmaps and implementation-ready specifications. These artifacts are available in structured, machine-readable formats so both human teams and AI agents can consume them. Fine-grained extraction control and coverage statistics provide audit-level evidence that nothing was missed, and source-to-requirement linking delivers unparalleled trust and traceability.
Platform Architecture & Universal Application Notation At the heart of Rhino.ai is a three-phase platform architecture. In the Understand & Extract phase, AI scans code, documents, SaaS applications and rules to analyze existing systems and identify hidden logic, dependencies and inefficiencies. The Organize & Structure phase captures extracted insights in a structured repository known as Universal Application Notation (UAN). UAN standardizes business logic, giving users the power to refine existing logic before moving forward so they modernize instead of merely migrating. Finally, the Generate & Transform phase converts legacy workflows into scalable applications, supporting SaaS platforms like ServiceNow and Appian, open-source microservices and external agents. UAN outputs can produce both modern applications and comprehensive documentation.
Deployment & Control The Rhino.ai platform supports flexible deployment models: choose an enterprise-grade SaaS offering or install Rhino.ai in your self-managed environment and bring your own language model. Rhino.ai does not access your databases or any data in your environment; your data stays entirely under your control. You maintain control over security policies, compliance requirements and access controls. You can also use your preferred AI models (OpenAI, Azure OpenAI, Anthropic or your own fine-tuned models), and Rhino.ai comes with a full set of audit trails, citations, and other capabilities which provide full trust and transparency.
Human & AI-Ready Deliverables With Rhino.ai, you can update requirements or create new ones, produce user stories, test cases, ERDs and flow diagrams to accelerate implementation. Rhino.ai's documentation is ready for both human teams and AI agents. Development teams receive clear, implementation-ready documentation and detailed architecture diagrams for informed decision making. AI agents like AWS Kiro, Windsurf, Cursor, as well as low-code platform agents like Appian Composer, ServiceNow Now Creator, and Outsystems Mentor can immediately consume the Rhino.ai output to power the generation of the new, modernized application.
Flexible Output & Agentic Transformation Beyond documentation, Rhino.ai offers multiple modernization paths. It can transform legacy code and SaaS apps to modern microservices or SaaS architectures with minimal disruption. Its automated code and SaaS analysis modernizes to modern microservices or SaaS architecture and converts applications to be AI-ready. Rhino.ai also supports replacing outdated processes with agents through agentic workflows, process automation and human-agent collaboration. Rhino.ai gives organizations a secure, flexible and comprehensive modernization platform--delivering faster modernization, lower costs, reduced technical debt and higher-quality applications through automated discovery, documentation and requirements generation with full traceability and flexibility.
Highlights
- Extracts detailed functional and technical understanding from the widest variety of legacy code and low-code platforms on the market
- Generate comprehensive documents with flexible options for structure, detail, tone and more so you can tailor your results to executive, analyst, or technical audiences
- Update requirements or create new ones, produce user stories, test cases, ERDs, and flow diagrams to accelerate implementation of your reimagined application
Details
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Delivery method
Supported services
Delivery option
Helm Chart
Latest version
Operating system
Linux
Deployed on AWS
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing and entitlements for this product are managed through an external billing relationship between you and the vendor. You activate the product by supplying a license purchased outside of AWS Marketplace, while AWS provides the infrastructure required to launch the product. AWS Subscriptions have no end date and may be canceled any time. However, the cancellation won't affect the status of the external license.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Vendor refund policy
Please contact support@rhino.ai
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Delivery details
Helm Chart
Supported services: Learn more
- Amazon EKS
- Amazon EKS Anywhere
Helm chart
Helm charts are Kubernetes YAML manifests combined into a single package that can be installed on Kubernetes clusters. The containerized application is deployed on a cluster by running a single Helm install command to install the seller-provided Helm chart.
Version release notes
The 2.08.0 release expands Rhino's Copilot into a fully integrated, end-to-end system across documents and UAN workflows, introducing editable document generation, unified Copilot experiences, improved citation handling and major stability, performance, and security improvements.
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Copilot Expanded Copilot into a fully integrated, unified experience across Custom Docs, UAD, and UAN, enabling users to explore Rhino's understanding in the UAN Editor and seamlessly create, edit, and regenerate documentation.. Introduced "Ask Copilot" for section-specific chats in UAD and Custom Documents. Brought entity awareness to chats in the UAN Editor. Improved contextual navigation in the UAN editor to quickly locate and access precise entity details Improved response quality with context-first answers, length calibration, as needed citation visibility.
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Custom Documents Expanded Custom Documents into a fully editable document system with structured authoring capabilities. Enabled document creation, naming, renaming, and global as well as section-level editing. Added drag-and-drop reordering with hierarchy preservation and collapsible parent sections across UAD and Custom Docs. Improved editing experience with left-side navigation, vertical toolbar, and save/unsaved changes handling. Enhanced export capabilities with Mermaid diagram support and inclusion of unsaved in-progress edits.
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UAN, Assertions and Citations Completed end-to-end citation support for UAN objects with persistence and UI visibility.
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Quality Improvements and Fixes Enhanced MCP system with improved tool selection, pagination, and agent guidance. Fixed fine-grained assertion controls including hidden flags and report-level visibility. Fixed Copilot streaming errors, event loop issues, and multi-step execution inconsistencies. Resolved issues with unsaved document state handling and lazy-loaded section edits. Fixed document generation failures, section reset issues, and broken navigation links. Improved layout consistency, table editability, and document interaction reliability.
The 2.08.1 release introduces native Amazon Nova and AWS Bedrock model support across the Rhino platform - GPT-4.1 availability in Copilot and Custom Documents, and improved platform resilience at startup.
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Amazon Nova & AWS Bedrock Support Rhino can now connect directly to Amazon's AI service (AWS Bedrock), so you can use Amazon's models without any extra setup or workarounds. New models available Amazon Nova Pro, Nova Lite, and Nova Premier are now supported and ready to use for Copilot and in generating Universal Application Document, User Stories, and Appian Composer Stories. The Test Cases document has been removed.
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Quality Improvements & Fixes Improved startup reliability: Rhino no longer crashes if an AI model is misconfigured or unrecognised. Instead, it disables just the affected feature and continues running normally. Private deployment support: Organisations running Rhino in a restricted network environment can now point it to their own internal Docker registry during the build process.
Additional details
Usage instructions
- Obtain license file and license keys from Rhino.
- Stage the license file as a Kubernetes ConfigMap
- Stage the license keys as a Kubernetes Secret
- If you wish, deploy a DB password secret to your namespace and set global.postgresql.auth.existingSecret and related keys
- Set the license parameters to match your config map and secrets in Helm values
- Set frontend.service.url to your desired URL exposing the Rhino application
- Configure the frontend.service parameters as desired (node port, load balancer) to expose the web application outside the cluster
- Configure additional Helm values/secrets for AI services, worker replicas, etc.
- Deploy: helm install rhino -n [namespace] ...
Support
Vendor support
Email: support@rhino.ai Web:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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