manueljpconde makes Mike run on your own machine, with your own model

A one-command local install plus bring-your-own AI provider - Mike no longer assumes you're comfortable handing everything to someone else's cloud.

infrastructureintegration

manueljpconde has added a single-command local setup that stands up the whole application - interface, backend, database, login, and file storage - on one machine, with no cloud API keys required to get it running. For a firm that wants to kick the tyres without signing up for hosted services or exposing client data, that's the difference between a demo and a non-starter.

The bigger piece is what the team calls managed models: each user can point Mike at their own AI engine - a local model running on their own hardware, or an account with Microsoft's Azure OpenAI service - and supply their own key, which is encrypted before it's stored and never handed back. It turns "which AI is reading my documents, and where does it live" into a setting the customer controls rather than a decision baked in upstream.

So what Worth a look for in-house legal and IT teams who need to keep model choice and data on their own turf before they'll trust a legal-AI tool.

View this fork on GitHub →

Spotted something wrong? Or know the PR text has fresher detail than the writeup above?

Commits in this thread

1 commit from manueljpconde/mikeEU, oldest first. Source extracted verbatim from the harvested git log.

SHA Subject Author Date
d39706fc Add Docker stack and managed model support Manuel Conde 2026-05-10 ↗ GitHub

Capture this thread into my fork

Download a single Markdown prompt that tells Claude how to port every commit above into your working tree — adapting paths and structure to match your repo. Run it via claude -p < capture-thread-252.md from inside the repo you want the changes in.

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