AI infrastructure and software engineering tools designed around the security boundary your organization chooses.
CodeLoop is MCMLV1’s private AI software-engineering system, currently in active development. It is designed to inspect a project, reason about the work, modify files in a private workspace, build and test the result, recover from errors, and present a reviewable diff before changes are applied.
CodeLoop is designed to work with local and private inference rather than requiring source code to be sent to a public cloud service.
The model proposes work, while compilers, tests, structured tooling, and human review provide the verification loop.
Changes are prepared for review rather than silently becoming production code. The professional engineer remains responsible for acceptance and deployment.
MCMLV1 can design an inference setup around the customer’s hardware, network, security policy, and performance requirements.
CodeLoop and inference on one Mac or PC for the simplest local deployment.
Developer workstations use a stronger inference workstation or server available only on the organization’s private network.
Dedicated customer-owned inference hardware deployed inside the organization’s facility or data environment.
Offline or physically isolated architectures can be designed when the organization requires stronger separation from external networks.
Keep routine or sensitive work local while routing approved workloads to stronger private or cloud models when policy permits.
Cloud inference can also be deployed when scale, convenience, or an organization’s existing cloud architecture makes it the right fit.
A deployment can include hardware and model evaluation, inference serving, network architecture, CodeLoop configuration, benchmark validation, offline testing, and documentation for the environment.
Workload, users, hardware, privacy constraints, model requirements, and expected performance.
Configure the selected local, private-network, on-premises, isolated, hybrid, or cloud architecture.
Benchmark the system, test failure/recovery paths, and document exactly what was deployed.
