MLOps and Model Deployment
About this service
Applied AI delivery that is shaped around real production constraints, not abstract demos.
This service is designed for teams that need a practical AI outcome with clear architecture, defined scope, and a route into production.
Outcomes you can expect
- Reduce uncertainty around where AI will create real business value
- Move from experimentation into a more reliable delivery path
- Create a usable system rather than a disconnected proof of concept
What's included
- Solution design aligned to business constraints
- Build scope, success criteria, and implementation direction
- A production-minded handoff or deployment-ready output
Compare packages
Three scope levels. Feature-by-feature comparison — no surprises after the quote.
| Feature | Starter $5,000 | GrowthPopular $5,000-$25,000+ | 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 |
| Solution design aligned to business constraints | |||
| A clear business problem or workflow target | |||
| Clear scope and recommended next step | |||
| Build scope, success criteria, and implementation direction | |||
| Stronger implementation depth and refinement | |||
| A production-minded handoff or deployment-ready output | |||
| Custom scope aligned to complexity, integrations, and rollout needs | |||
| Choose Starter | Choose Growth | Choose Custom |
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.
What we need from you
Better input creates a stronger engagement. Bring as much of this as you can.
- A clear business problem or workflow target
- Any available data, documentation, or source systems
- Constraints around compliance, timelines, or integrations
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 MLOps and Model Deployment
Share enough context and we'll email back a budget range, recommended next step, and any clarifying questions — usually within one business day.