It converts that environment into a connected model containing programs, user journeys, dependencies, data models and business rules. Human subject-matter experts validate the resulting model before specifications are passed to agentic coding tools.
The platform also creates an audit trail. Rules are versioned and traceable to their source, while approved specifications can be consumed by AI development tools that generate replacement services.
rhino’s product is available through AWS Marketplace and directly from the company. It works with AWS Transform through Model Context Protocol, uses Amazon Bedrock for agents and can deploy modernised services to AWS Lambda, Amazon ECS or Amazon EKS.
Customers can begin with a fixed-scope estate assessment. rhino says this produces a connected model and modernisation blueprint for a defined part of an environment within two to three weeks.
Two to three weeks changes how modernisation can be sold
The fixed-scope starting point is commercially important.
Legacy-modernisation projects traditionally carry substantial discovery risk. Before replacing a system, teams need to determine which business processes depend on it and which undocumented behaviours must survive the transition.
AI can accelerate code generation, but faster coding does not remove that discovery problem.
For smaller consultancies, this changes where expertise can remain valuable.
A specialist firm does not need to create its own mainframe transformation model. It can concentrate on a particular industry or legacy application environment and provide the human validation, migration planning, testing and operational change surrounding automated modernisation.
Insurance administration, regional banking, manufacturing and logistics contain organisations with older systems whose business rules are understood by relatively few employees.
A consultancy with knowledge of one such environment could package a narrow discovery engagement rather than bidding for an entire multi-year transformation.
The practical entry point is a single business process. Map the legacy programs, integrations and SaaS applications supporting that process and identify which rules must remain unchanged after modernisation.
The risk is dependence on larger platforms. If infrastructure providers and global consultancies package discovery, transformation and validation together, smaller firms can be squeezed out.
Industry knowledge provides the defence. AI can reconstruct technical dependencies, but understanding why a particular underwriting rule, manufacturing exception or settlement process exists still requires domain context.
As automated coding becomes stronger, that contextual knowledge may become more valuable rather than less. The opportunity for smaller modernisation specialists is therefore moving away from selling coding capacity and toward selling verified understanding of the systems enterprises cannot afford to misunderstand.
More information
Source and more information: rhino.ai Launches rhino Agentic Mainframe Modernization on AWS