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Refrakt

Refrakt

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Deep learning workflows today are fragmented across scripts, dashboards, and tools.

Refrakt is a unified platform that brings model training, evaluation, and explainability
into a single system.

This launch includes a short 3-minute UI walkthrough (no live execution yet): http://youtube.com/watch?v=IZQ8kW2_ieI

Platform access is coming soon!

Any feedback is welcome!

2 Comments

•

Interesting idea bringing training and explainability into one place, curious how Refrakt will handle collaboration when multiple people are iterating on the same model.

1 vote
•

@[Andrew Mewborn] great question!

Refrakt doesn’t treat “the model” as a shared mutable object. The primary units are
versioned workflows, configs, and the artifacts produced by each run.

Collaboration is centered around reproducible runs and explicit artifacts (e.g.
being able to inspect, compare, or reuse outputs from prior executions) rather than
multiple people concurrently editing the same state.

For now, the focus is on making iteration legible and traceable (who ran what, with
which config, producing which artifacts).

More explicit team-level collaboration primitives are something we’re thinking about, but this walkthrough is mainly meant to show the core workflow abstraction.

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Akshath Mangudi
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ML systems engineering.

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