ENTERPRISE AI / CUSTOM MODEL TRAININGEnd-to-end training

Custom Model Training

Turn a general model into a specialized model that understands an industry, enterprise knowledge, and private task boundaries

Our complete model-training capability supports joint development of industry-specific and private enterprise models. We connect data governance, continued pretraining, supervised fine-tuning, preference alignment, evaluation, compression, and deployment as a repeatable training loop.

DOMAINIndustry capability

Build data and objectives around domain corpora, professional knowledge, task formats, and industry evaluation criteria.

TRAINComplete training path

Combine continued pretraining, SFT, preference optimization, distillation, and safety alignment for the target outcome.

PRIVATEPrivate enterprise model

Create a controlled, evaluable, and continuously improvable model asset within license, data, and deployment boundaries.

CAPABILITY / TRAINING LOOP

Keep training objectives and business acceptance on the same path from data to deployment

Objective definition and base-model selection

Define domain capabilities, tasks, model size, licenses, deployment hardware, and evaluation criteria before selecting the base model.

Data governance and dataset construction

Collect, clean, deduplicate, de-identify, label, synthesize, quality-tier, and version the data as a traceable asset.

Training, alignment, and compression

Combine continued pretraining, supervised fine-tuning, preference optimization, distillation, and quantization while retaining configs, checkpoints, and results.

Evaluation, deployment, and feedback loop

Evaluate domain tasks, risk cases, and business metrics, then use production feedback to guide the next data and training iteration.

DELIVERABLES

Make the training process, model assets, and evaluation results traceable, reproducible, and ready to evolve

Training objectives and technical planData specification and versioned datasetTraining code, configs, and checkpointsDomain evaluation set and reportCompression, inference, and deployment planData and model iteration guide

OUTCOME / MODEL ASSET

Build an industry-specific model or a private enterprise model together

Industry models emphasize domain knowledge, task formats, and sector evaluation criteria. Private enterprise models also incorporate internal data, processes, and deployment boundaries. Both require data quality, training method, evaluation, and inference cost to be judged together.

BOUNDARY / TRAINING

Training capability does not replace data rights, model licenses, or a clear business objective

Before work begins, we confirm data provenance, authorization, privacy, base-model licenses, target hardware, and acceptance criteria. Results depend on data coverage, annotation quality, base-model capability, and training budget; methods and deliverables are finalized during validation.