Skip to content

    Intent-driven training,end to end

    Bring your datasets and code; FlexAI handles orchestration, checkpoints, and workload placement so your team stays in motion.

    Train and post-train the models that power your agents, then deploy winners back into Token Factory, dedicated endpoints, or Agent SDK workflows.

    Get startedBrowse blueprints

    Two phases. One rhythm

    01
    Pre training prep that ships
    Dataset ingest from buckets, volumes, or your existing storage.
    02
    Multi node without complexity
    Scale from a single GPU to large clusters.
    03
    Checkpoints that just happen
    Automatic snapshots and fast resume.
    FlexAI Training Console

    Large Scale Support

    • 1 to 1000s of GPUs
    • Multi-node distributed
    • Multi-region compute

    Performance & Resilience

    • Parallelized execution
    • Auto checkpointing
    • Managed data pipelines

    Built-in Observability

    • TensorBoard · Visualize metrics and graphs
    • Weights & Biases · Track experiments at scale
    • Grafana · Infrastructure monitoring

    A calm interface for serious work

    A simple control point for end users and admins, with governance and visibility when you need it.

    One platform
    Web UI, CLI, and API all map to the same mental model. Your workflow stays yours.
    Self healing runs
    Automatic recovery with managed checkpoints so long runs keep their shape.
    Enterprise grade guardrails
    RBAC, quota policies, and visibility across teams and workloads.

    Start with our Blueprints

    View all→
    Domain fine tuning playbookpre training
    →
    Multi node training with managed checkpointstraining
    →
    Post training alignment pipelinepost training
    →
    Evaluation and release gateseval
    →
    Proof

    Teams keep velocity

    A few words from builders using FlexAI for training and deploying models.

    "

    Compared to other platforms I have used, FlexAI provides a more cost effective and hassle free experience for training and deploying my models.

    LegML
    "

    FlexAI enabled us to prove the value of our model in record time and make it to Y Combinator.

    Dollyglot.com
    "

    The ability to manage compute resources across multiple cloud providers through a unified interface is a game changer.

    Pixelcut
    Read the full stories: how LegML fine-tuned a 32B legal LLM, DragonLLM training on sovereign infrastructure, and Pixelcut's pay-per-use fine-tuning.
    Plan your spend

    Sizing a training run? Use the GPU savings calculator to compare H100/H200 costs against hyperscalers, or work out when serverless stops paying off. Need dedicated capacity for the largest jobs? See dedicated endpoints.

    Get started

    Put pre and post training on rails

    Get startedTalk to an engineer
    90 second path
    1. 1Pick a blueprint for your model family and stage
    2. 2Set constraints: budget, speed, region, reliability
    3. 3Launch. Observe. Promote the winner

    Frequently Asked Questions

    More managed AI services: inference, fine-tuning, and the platform overview.