Predibase

core-platform

closed(proprietary post-training stack + turbo serving)

source

partial(LoRAX and Ludwig are adjacent OSS

OSS-components

LoRAX(open source multi-LoRA serving)+Ludwig(open source)

runs-on

Predibase-SaaS-or-customer-VPC

license

Proprietary(managed) with Apache-licensed LoRAX/Ludwig adjuncts

Predibase's founders still maintain LoRAX, the open-source multi-LoRA serving stack, and Ludwig, but the fine-tuning and reinforcement-fine-tuning platform itself is proprietary managed SaaS running on Predibase's cloud or inside a customer VPC. That makes it source-available rather than open source: public repositories exist at the serving edge, but the training runtime does not ship.

• https://files.pythonhosted.org/packages/f2/f0/6fb3406af8891fe08b8e5d3b325c39050f7616054bf0a73496277701356a/predibase-2025.10.3.tar.gz recorded 2026-09-23

  Extracted with Python's tarfile (106 members). README.md opens "## Predibase Python SDK"; PKG-INFO records "License: UNKNOWN"; no LICENSE file exists anywhere in the archive; setup.py registers only a console-script entry point (pbase=predibase.cli:main) and no license classifier. A case-insensitive grep of every decoded file for "vpc" found exactly one hit, in predibase/resources/datasets.py: ":param region: (str) Optional region to upload to. Only relevant for VPC customers with multiple dataplanes." This corrects a prior run's claim that the sdist contains no VPC reference.

• https://github.com/predibase/lorax recorded 2026-08-09

  The repository title reads "Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs"; the repo metadata records "license":{"spdxId":"Apache-2.0","name":"Apache License 2.0"} and "archived":false. The serving engine that plugs into Predibase is public, OSI-licensed, and actively maintained, in contrast to the managed fine-tuning/training platform itself, which ships no equivalent repository.

• https://pypi.org/pypi/predibase/json recorded 2026-09-23

  The JSON API's info object records license: null, classifiers: [], summary: null, and home_page: null for the predibase package (version 2025.10.3) on PyPI — no license or project metadata is declared for the published client library.

• https://web.archive.org/web/20260107043258/https://docs.predibase.com/ recorded 2026-09-23

  The "Additional Capabilities" list states "SaaS or VPC deployment options: Deploy in our cloud or yours" and "UI and SDK: Deploy, fine-tune, and prompt via our UI or Python SDK" — access is through a hosted UI/SDK and a deployment-location choice, not a self-hostable code drop of the platform itself.

Predibase does not disclose jobs run or customer counts for the platform. Its only public traction is its acquisition by Rubrik, which the press valued in the hundreds of millions of dollars, and that reflects commercial interest in the company rather than measured use of the platform.

• https://techcrunch.com/2025/06/25/rubrik-acquires-predibase-to-accelerate-adoption-of-ai-agents/ recorded 2026-09-28

  Reports the Rubrik acquisition of Predibase: "Terms of the deal were not disclosed, though CNBC reported that the deal was between" $100 million and $500 million, and that the company "has raised more than $28 million in VC money". Searched the body for customer counts, jobs run and usage figures: none given for the platform.

Predibase matches the reinforcement-fine-tuning services from OpenAI, Azure and Fireworks, and adds multi-adapter serving that hosts hundreds of fine-tunes per GPU, which those platforms lack. It remains a managed platform with no exposed large-scale training internals, well behind Megatron-LM and the other libraries that publish their own training-scale numbers.

• https://web.archive.org/web/20260107043258/https://docs.predibase.com/ recorded 2026-08-09

  The Key Features section describes Serving as deploying models via production-ready private serverless endpoints through LoRAX, which serves hundreds of fine-tuned models on a single GPU, and Post-training as supervised fine-tuning, reinforcement fine-tuning, or continued pretraining. A features card elsewhere names Reinforcement Fine-Tuning specifically as Group Relative Policy Optimization (GRPO), and the docs' internal redirect map still routes a turbo_lora path to a TurboLoRA page, confirming it as a current feature name rather than a retired one.

• https://web.archive.org/web/20260118040413id_/https://predibase.com/ recorded 2026-08-09

  Searched the raw HTML including script payloads (not just visible text), case-insensitive substring counts: "fine-tun" appears 11 times and "TurboLoRA"/"reinforcement fine-tun" once each. The Organization JSON-LD lists knowsAbout entries for "Fine-tuning", "LoRA", "TurboLoRA", and "Reinforcement fine-tuning", and keywords "LLM, LoRA, inference, AI, fine-tuning, open-source models, AI serving". This directly contradicts a prior claim that this archived homepage has no fine-tuning mentions. The rendered page itself (title "Predibase: Govern Every Agent. Trust Every Action.") had already pivoted to agent-governance messaging by this date even though the schema block still lists the fine-tuning capabilities.