# Ashr: custom models and evals for production AI

Canonical: https://thelazyweb.com/companies/ashr/
Breadcrumb: [Home](https://thelazyweb.com/) / [Companies](https://thelazyweb.com/companies/) / [Ashr: custom models and evals for production AI](https://thelazyweb.com/companies/ashr/)
Author: Ali Abouelatta (https://thelazyweb.com/authors/ali-abouelatta/)
Published: 2026-09-19
Updated: 2026-09-19
Research type: Company profile
Method: Company and accelerator sources checked 2026-09-19. Product claims are attributed to their sources; this is research, not a hands-on product trial.

## What it does

Ashr builds Manifold, a platform for training, hosting, evaluating and continuously improving purpose-built open-weight models. Its [current homepage](https://ashr.io/) describes a loop that captures an organization’s documents, transcripts, logs and corrections, trains against a written rubric, benchmarks against a current frontier API and keeps retraining in the customer’s cloud. The [YC profile](https://www.ycombinator.com/companies/ashr) also describes the earlier Ashr evals product for mimicking real user behavior and testing agents.

The fit is a company with enough production data and a repeatable AI workload to justify a specialist model, but not enough research infrastructure to build the training/evaluation loop alone. Ashr’s key promise is ownership: encode the organization’s judgment in weights and run them in an environment the customer controls.

## Why I’d look closer

The public workflow is unusually disciplined. Ashr says teams define correctness, freeze a dataset, run a head-to-head

[Ashr: custom models and evals for production AI](<https://www.thelazyweb.com/companies/ashr/>)

Source observed: 2026-09-20T02:21:45.548Z. Last checked: 2026-10-08T01:59:39.085+00:00.

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