Frontier intelligence,
specialized for your use case.
Training Jobs
Train models on your data.
Built for teams that need specialized models,
Veri handle all the infrastructure complexity.
Start training with only a few lines of code.
Ship a live model endpoint without managing a cluster.
Train effortlessly.
Bring your own dataset and kick off a run in a few lines. Veri provisions the exact GPU config, handles checkpointing, and streams logs end to end.
Training guideDeploy peacefully.
Save massive.
Specializing a small open model on your task and it can match frontier quality at a fraction of the inference cost.
We provide an OpenAI compatible endpoint for deployed models, so you could seamlessly switch.
Scale up without
the complexity
Some curated demos from us to help you get started using our platform.
SFT w/ Unsloth
A practical first specialization run with LoRA adapters and a lightweight single-GPU path.
Go to docs →Harness-in-the-loop RL
An example of training an agent w/ GRPO inside the same harness it deploys in.
Go to docs →Verl GSM8K PPO
A walkthrough through GSM8K PPO quickstart for reasoning eval loops using Verl.
Go to docs →Meant to be
easy.
Run an experiment in a few lines of code with the Veri SDK, then compare results before they reach production.
SDKfrom veri_sdk import training_job@training_job( base_model="Qwen/Qwen2.5-0.5B-Instruct", dataset="hf:openai/gsm8k", gpu_type="L4-24GB", gpu_count=1,)def reward(completions, answer, **kwargs): return [1.0 if a in str(c) else 0.0 for c, a in zip(completions, answer)]Maximize Capability.
Iterate faster.

