+966 55 208 1012
[email protected]العربية
Tamken Digital
Vision 2030 — Kingdom of Saudi ArabiaSchedule a meeting
Services/AI Solutions/Machine Learning Integration

Machine Learning Integration

Machine learning that ships — models embedded in your product with the pipelines and monitoring to keep them accurate.

Start your project All services
8+
Years of experience
250+
Projects delivered
120+
Happy clients
30+
Specialists
Trusted by our clients
Overview

ML that ships, not just trains.

We integrate machine learning where it creates measurable value — recommendation, scoring, forecasting — handling data pipelines, model serving and the feedback loops that keep it accurate.

What you get
Custom model integration
Data pipelines
Model serving & APIs
Monitoring & retraining
A/B evaluation
MLOps setup
Capabilities

Our Machine Learning Capabilities

We take machine learning from data pipeline to production — building, serving and monitoring models embedded directly in your product.

Custom Model Development

Models built and tuned for your specific problem.

Data Pipelines

Reliable ingestion, cleaning and feature engineering.

Model Serving & APIs

Low-latency inference wired into your product.

Recommendation Systems

Personalization that lifts engagement and revenue.

Forecasting

Demand, revenue and capacity predictions you can plan on.

MLOps & Monitoring

Retraining, drift detection and A/B evaluation.

Why Tamken

One accountable team, the full journey.

01

Senior, in-house team

No hand-offs to subcontractors — the people who design it build it.

02

Built for ROI

Every decision ties back to a metric that matters to your business.

03

AI-native & local

Intelligence built in, with Arabic-first thinking and Vision 2030 alignment.

04

Bilingual by default

Arabic and English, RTL and LTR, handled correctly from day one.

05

Weekly delivery cadence

You see working progress every week, not a status report.

06

No lock-in

Clear ownership of what we build, and the freedom to pause or stop anytime.

How we work

A clear path from idea to impact.

1

Data & Feasibility

We assess your data and prove the use case is worth building before we commit.

2

Model Design

We select and design the right approach — classic ML, deep learning or LLM/RAG.

3

Training & Evaluation

We train, measure against real metrics, and tune until it's genuinely useful.

4

Integration

The model ships inside your product with low-latency, secure inference.

5

Monitoring & Retraining

We watch for drift and retrain so accuracy holds up over time.

Technology

Our technology stack

We build with proven, modern technologies chosen for performance, security and long-term maintainability.

PythonPython
TensorFlowTensorFlow
PyTorchPyTorch
scikit-learnscikit-learn
AWS SageMakerAWS SageMaker
MLflowMLflow
Testimonials

Launching the Rayan perfumes line with Tamken was a great experience — quality work, fast execution, and we hit every goal. Among the best agencies in the region.

ع
عمر تقي الدين
Founder, Rayan Shop
Pricing

Sprint pricing — know your full cost before you start.

A sprint is our unit of work: one focused week with a dedicated team. Your project is scoped into an agreed number of sprints up front — so the total cost is clear from day one, with no surprises.

Free discovery sprint

We scope it before you pay

We start with a free discovery sprint: we analyse your idea, define the scope, and hand you an execution plan with the exact number of sprints and total cost. You decide after seeing the plan.

Book your free discovery sprint
execution sprints
3,750SAR/ sprint
Placeholder figure — to be confirmed.
1 sprint = 5 working days · typical scopes: landing site 2–3 · store 4–6 · app/MVP 6–10 sprints
Agreed scope & sprint count before we start
A dedicated team throughout the sprint
Daily progress updates & weekly demo
You own everything we deliver
Stop at the end of any sprint
FAQ

Questions we hear often.

How much data do we need to get started?

It depends on the problem — some tasks work with a few thousand labeled examples, and we can start from pre-trained models or synthetic data when your dataset is thin, then improve as more arrives.

Should we build a custom model or use a pre-trained API?

We start with pre-trained models or APIs when they solve the problem cheaply, and build custom models only when your data or accuracy needs justify the investment.

What happens when the model's accuracy drops over time?

We monitor for data drift and performance decay in production, and set up retraining pipelines so the model stays accurate as your data and patterns change.

How does the model connect to our product?

We serve it behind a low-latency API or embed it on-device, wired into your app with monitoring, so predictions arrive exactly where your users and workflows need them.

Related services
Let's build

Turn your data into decisions embedded in your product.

Book a free consultation and we will map the fastest credible path to launch.

CustomBuilt for youProductionShips, not demosVision 2030Aligned
Start your project See our work
Free discovery sprint
Full cost agreed up front
Reply within 24 hours
Contact us

Tell us about your project.

This is what happens after you submit:

1
Full confidentiality

We can sign an NDA to fully protect your idea.

2
Reply within 24h

Our experts contact you within one business day.

3
A complete proposal

We discuss the details and send a clear plan and offer.

Or directly viaWhatsApp+966 55 208 1012[email protected]
Machine Learning Integration