Dependabot for fine-tuned models

Your model, requalified on every new base.

A new base ships. Roadbed retrains your model on your GPUs, scores it on evals from your own reviewers, and hands your risk team the evidence.

roadbedbot opened a rebase just now

Qwen3.8-27B shipped. Candidate ready for claims-triage.

v12 on Qwen3.6-27B → v13 on Qwen3.8-27B · 38,410 verdicts · 1,284 frozen holdout cases · material change

Your evals
+2.1
94.0 → 96.1 · 95% CI +0.9 to +3.3
Cost
−31%
per 1k calls, your GPUs
Below margin
0 of 14
slices, margin −2.0 · 2 flagged low-n
License
Allowed
Apache-2.0 · policy allow-list · BOM attached
Illustrative numbers. Method note to follow.

How it works

Capture. Rebase. Promote.

The system of record for what your models have learned, and the control plane for changing them.

No platform we know of requalifies a fine-tuned model per slice when a new base ships, or writes the change record a risk team reviews. That loop is Roadbed.

Capture anywhere, even on a closed API. Rebase onto open weights when you are ready.

  1. 01

    Capture verdicts

    Every accept, edit and rejection, logged with who and why.

  2. 02

    Derive evals

    Golden sets, correction tests and slices. A sealed holdout.

  3. 03 The gap

    Rebase on every new base

    Retrained and scored on your evals, on your hardware.

  4. 04

    Promote behind a gate

    Shadow, canary, rollback. An evidence pack for your validation file.

Composite scenarios from real demand. Numbers illustrative.

What you own

Plain files in your bucket.

The asset is a folder, not a platform. Open format and CLI on GitHub when the first design partner is live.

roadbed.yaml illustrativemodel: claims-triage
base: Qwen/Qwen3.8-27B@7f3a…
data:
  verdicts: s3://acme/claims/verdicts@2026-10-28
  holdout: sealed@2026-01-14
evals:
  golden: 412
  correction_tests: 96
  slices: [line, state, channel]
  margin: -2.0
recipe: lora-r16-sft@v4
gate: [shadow, canary, bias-tests, sign-off]
lineage: v12 ← Qwen3.6-27B · verdicts@2026-07-02
terminal illustrative$ roadbed watch --base Qwen/Qwen3.*
new base: Qwen/Qwen3.8-27B

$ roadbed rebase claims-triage --on Qwen/Qwen3.8-27B
trained on 38,410 verdicts
scored on 1,284 holdout cases
+2.1 (CI +0.9 to +3.3)
0 of 14 slices below margin

opened rebase #13 → awaiting MRM sign-off

The rebase moment

A pull request against your model.

Retrained on your data, scored on your evals, costed on your hardware. When a slice fails, the gate says no.

  1. New base detected: Qwen/Qwen3.8-27B
  2. Candidate v13 trained on 61,200 verdicts
  3. Scored on 1,420 sealed holdout cases. Overall +1.8
  4. PT identity cards −9.0, below the −2.0 margin
  5. Promotion blocked. Finding logged against the model
  6. v12 stays live. Evidence pack attached for review

Every model runs on your roadbed.

Read the manifesto

Fine-tuned a model?

Three design-partner slots for teams whose fine-tuned model sits on an API that is being retired, or on a base that has fallen behind. Or leave an email for one update.

Design partners and investors: founders@roadbed.ai