Train, fine-tune, evaluate, and optimize models for your ticket workflows
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Editions
Editions
- Focused single-task model or one fine-tuning run
- Clear acceptance metrics
- Baseline training + evaluation
- Deployment-ready artifact + short docs
- Fuller training & evaluation cycle
- Synthetic-first or hybrid data path
- One optimization / tuning round
- Evaluation report + integration guidance
- Complex or multi-model programs
- Real-data alignment, custom metrics, constraints
- Scoped proposal after discovery
Who it’s for
- You need a dedicated AI model for your specific workflow or business process
- You already have a dataset and want a deployable fine-tuned model
- You want training, evaluation, and optimization in one engagement — not split services
Deliverables
- Custom AI model specification aligned to your workflow
- Training or fine-tuning pipeline (synthetic-first and/or real-data as scoped)
- Evaluation report with metrics, failure modes, and recommendations
- Deployment-ready model artifact
Prerequisites
- Clear task definition, expected inputs, and target outputs
- Acceptance metrics (precision/recall targets or business KPIs)
- For larger editions: sample data access or synthetic-data pack as agreed
Included
- Model iteration within the chosen edition
- Optimization round where the edition includes it
- Deployment guidance
Excluded
- Long-term MLOps / monthly maintenance (see Support)
- Large-scale data annotation operations unless scoped separately
Process
- Define model task and acceptance metrics
- Define evaluation set strategy
- Prepare or generate training data
- Train or fine-tune and validate the model
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Evaluation + Optimization
- Report metrics and failure modes
- Tune thresholds, config, or parameters within scope
- Deliver model + docs
- Integration guidance
Frequently Asked Questions
Everything you need to know about scope, prerequisites, and delivery.
AI Model Development
Train, fine-tune, evaluate, and optimize models for your ticket workflows