How much does machine Learning Development Services cost?

Machine Learning Development Services starts at $4,400 for a typical engagement. The final price depends on scope, existing code and integrations — send the brief through the form and you get a fixed-scope quote, usually within one business day.

How long does it take?

A typical machine Learning Development Services engagement runs 5–12 weeks from signed scope to delivery, with something running on a staging URL from the first week.

You do. The repository, deployment pipeline and hosting accounts are yours from day one, and intellectual property transfers on final payment. There is no platform to stay locked into.

Every engagement includes: A simple baseline measured first — sometimes it wins; Feature pipeline shared between training and serving; Model served behind an API with latency SLOs.

Send the enquiry form on this page or email bilgisam@gmail.com with a short description of the problem. You get a reply within one business day, a free scoping call, and a written proposal before any invoice.

📐 AI & Machine Learning

Machine Learning Development Services

Forecasting, scoring and recommendation models that reach production and stay monitored afterwards.

Starting at: $4,400
Typical delivery: 5–12 weeks
Engagement: Fixed scope
Code ownership: Yours

Most machine learning value is lost after the model works: no serving path, no monitoring, no retraining, and a slow decay nobody notices for two quarters.

We build the serving and monitoring path in parallel with the model, and we compare every model against the boring baseline. If a rule you can write in SQL matches the model, that is the answer we recommend.

What you get

A simple baseline measured first — sometimes it wins
Feature pipeline shared between training and serving
Model served behind an API with latency SLOs
Drift and performance monitoring with alerting
Scheduled retraining with automatic rollback on regression

Who this is for

Companies with years of operational data and no one to turn it into predictions.

Tools and technologies

Python scikit-learn XGBoost MLflow Airflow FastAPI

How it runs

Scoping call
45 minutes with the engineer who would do the work, within one business day of your enquiry.
Written proposal
Scope, price, timeline and exclusions in writing. No invoice until you approve it.
Weekly delivery
Staging URL from week one, in your repository and your cloud account.
Handover
Documentation, walkthrough and 30 days of post-launch bug fixing included.