Refresh C Verified

RL environment company · Coding

On X
@refresh_dev ↗
Funding
Y Combinator X25 · rounds and investors
Tier
C why
Snapshot

Open environment ↗refresh.dev

What Refresh does

Refresh builds RL environments and evals with verifiable rewards for coding, computer use (cloned software suites like EHRs and enterprise apps) and 3D animation in Blender, for frontier labs and enterprises.

Leads with
Several domains (a generalist)
Based in
San Francisco, USA
Team
1-10

What Refresh sells

Read from Refresh's own website, checked October 12, 2026: the line that puts it in each category.

RL environments

  • RL environments

    “Refresh builds simulated worlds for coding and computer use, with verifiable rewards that move models forward.”
    refresh.dev ↗
  • Evals

    “Refresh builds these environments as both evals, to objectively benchmark how well frontier models perform real computer work”
    refresh.dev ↗

Data

Domains Refresh covers

  • Coding

    “Software engineering work that targets GDPval capabilities, the economically valuable tasks professionals handle across dozens of occupations.”
    refresh.dev ↗
  • Computer use

    “High-fidelity clones of full software suites, wiring together multiple connected applications, from EHRs to enterprise apps and beyond.”
    refresh.dev ↗
  • Enterprise work

    “from EHRs to enterprise apps and beyond”
    refresh.dev ↗
  • Health and bio

    “from EHRs to enterprise apps and beyond”
    refresh.dev ↗
  • Media

    “Agents working inside Blender, from building scenes and materials to rigging characters, keyframing animation, and running cloth and physics simulations.”
    refresh.dev ↗

Refresh competitors and alternatives

The companies that sell the most of the same things in the same domains, and what they share with Refresh.

Every RL environment company on the landscape map →

Tier C

C

Early: a small team.

How much stands behind a tier: usage, who backs it, a confirmed line from its own site or paper, and a clear read on X. High with three of the four, medium with two, low otherwise.

  • team 1-10
  • investors: Y Combinator
  • went through Y Combinator Spring 2025
  • in curated RL directories (5 pts)

On X · unclear, low buzz, from 12 posts about Refresh in the last month

A small circle of replies praises Refresh's newly released Blender/animation benchmark results, and one VC flags it as an RL gym company; little broader attention.

@frontrunvc ↗ · @refresh_dev ↗ · @AdamWax3 ↗

How we got to tier C
  1. Adoption: team 1-10; investors: Y Combinator; went through Y Combinator Spring 2025. Tier C.
  2. On X: unclear, low buzz. “A small circle of replies praises Refresh's newly released Blender/animation benchmark results, and one VC flags it as an RL gym company; little broader attention.” No move.
  3. In curated RL directories: 5 points, a floor of C.
  4. Confirmed: a line from its own site or paper places it.

A clear view on X moves a tier one step up or down; most entries don't move. How tiers work.

Refresh funding

Accelerator
Y Combinator X25

Backed byY Combinator Spring 2025

Accelerator

  • Y Combinator Spring 2025
    1. Y Combinator's company directory lists Refresh with the website refresh.dev, in its Spring 2025 batch
    2. Checkable on YC's page: ycombinator.com/companies/refresh
    3. No other page read names Y Combinator yet
    ycombinator.com/companies/refresh

Every figure is quoted from its own site, its accelerator or a funding announcement; a round's amount and lead appear only when its quote states them. Startup databases are never used as evidence. Checked 2026-10-11. How funding is checked.

Training methods

Methods Refresh uses, offers or builds for, with public evidence: its own website says so, or two independent sites do.

  • “An RLVR dataset curated from Gauntlet, delivered in Harbor format for reinforcement learning.”

    refresh.dev

    “\\ \\ Datasets\\ \\ Feb 17, 2026 Gauntlet 4K RLVR \\ \\ An RLVR dataset curated from Gauntlet, delivered in Harbor format for reinforcement learning.\\ \\ Read more”

    refresh.dev
  • “We trained rnj-1-instruct 8B using the terminus-2 harness with our Gauntlet 4K RLVR dataset. After GRPO showed instability during training, we switched to the DAPO algorithm which provided consistent convergence.”

    refresh.dev
  • SFT Supervised Fine-Tuning On its own website

    “…k, and as training gyms with verifiable rewards that models learn from. A verifiable reward is an objective signal of whether the agent completed a task correctly, and it powers the two main ways to post-train an agent: supervised fine-tuning (SFT) on high-quality example trajectories, and reinforcement learning, where the agent improves by acting in the environment and being scored on the outcome. That signal can come from a deterministic verifier, such as…”

    refresh.dev

Where Refresh sits

Its domain on the map, live. Hover a logo for its name; click to open it. Open it on the full map

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Latest from Refresh on X

@refresh_dev ↗

Next: browse all environments. Entry from the RL Research daily scrape of public sources, 2026-11-05 snapshot.