Custom Model Training
About this service
Custom model training tied to measurable performance, cleaner data assumptions, and a real production use case.
This service is best for businesses that need model behavior tuned to their own data, quality standards, and operational context instead of relying entirely on generic off-the-shelf behavior.
Outcomes you can expect
- Train around your actual domain, classification, or prediction needs
- Improve model accuracy for business-specific tasks
- Build a path from training into evaluation, deployment, and iteration
What's included
- Training approach and evaluation plan
- Data preparation or quality guidance
- Model build, testing direction, and deployment recommendations
Compare packages
Three scope levels. Feature-by-feature comparison — no surprises after the quote.
| Feature | Starter $8,000 | GrowthPopular $8,000-$60,000+ | Custom Custom quote |
|---|---|---|---|
| Turnaround | 7-10 day delivery | 2-5 week delivery | Custom phased plan |
| Revisions | 1 structured revision | 2 structured revisions | Milestone-based reviews |
| Training approach and evaluation plan | |||
| Representative data or a realistic route to acquiring it | |||
| Clear scope and recommended next step | |||
| Data preparation or quality guidance | |||
| Stronger implementation depth and refinement | |||
| Model build, testing direction, and deployment recommendations | |||
| Custom scope aligned to complexity, integrations, and rollout needs | |||
| Choose Starter | Choose Growth | Choose Custom |
How the work runs
Every phase has a deliverable. You always know what's next.
- 01
Clarify the real task
The first step is defining the business task and useful success criteria, not jumping straight into training.
- 02
Assess data and evaluation fit
Data quality, labeling quality, and realistic evaluation approach are reviewed before the build goes deeper.
- 03
Train with production in mind
The training plan is shaped around where and how the model will actually be used later.
- 04
Plan deployment and iteration
A useful training engagement should lead into clear next steps for testing, deployment, and refinement.
Delivery commitments
The guardrails that apply to every engagement, not just the big ones.
48-hour quote turnaround
Submit a scope request; we return a real number, a scoping proposal, or a written recommendation within two business days.
Written scope before kickoff
Every engagement starts with a shared document — deliverables, assumptions, exclusions, and what counts as done.
Fixed price when scope is clear
Hourly billing creates perverse incentives. Once requirements are defined, we commit to a fixed number and absorb estimation risk.
Production-first, not demo-first
Evaluation, monitoring, and ownership paths are part of the scope — not retrofitted after the pilot impresses the exec room.
Where this service lands hardest
Domain-specific prediction
When the business needs model behavior shaped around its own patterns, thresholds, and context rather than general assumptions.
Classification and quality tasks
When the system needs to consistently sort, detect, label, or rank business-specific inputs.
Operational model improvement
When an existing model approach exists but needs clearer evaluation, stronger data assumptions, or more useful performance.
What we need from you
Better input creates a stronger engagement. Bring as much of this as you can.
- Representative data or a realistic route to acquiring it
- A clear task such as classification, ranking, prediction, or detection
- Success criteria such as accuracy, precision, speed, or reliability
Frequently asked questions
Is this only for large enterprises?+
No. The engagement size changes with scope, but the structure is meant for teams that want clear implementation rather than vague AI exploration.
Can this include integrations and deployment?+
Yes. The exact scope depends on the service, but production deployment and integration planning are common parts of this kind of work.
What most affects pricing?+
Data readiness, integration depth, evaluation requirements, compliance, and how production-ready the final system needs to be.
About ConnectivAI
Applied-intelligence practice delivering AI systems, custom software, web platforms, and growth infrastructure built for production. One partner across four lanes — fewer vendor seams, tighter handoffs, work that compounds across acquisition, product, and operations.
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Helpful resources
Get a written estimate for Custom Model Training
Share enough context and we'll email back a budget range, recommended next step, and any clarifying questions — usually within one business day.