DATA & AI ENGINEERING
From dashboards to autonomous AI In production.
One partner for the whole data and AI spectrum reporting, machine learning, LLM applications and agentic AI designed, deployed and operated by the same team since 14 years
WHY THIS PILLAR ?
Data and AI is not one decision… it’s a path
Some companies need their numbers in one trusted place; others are ready to put autonomous agents inside their operations. We have shipped every step of that path: the dashboards, the models, the LLM applications and the agents. Wherever you are today, we meet you there and take you to the next step.
Our services
Four services, one team
the catalog behind the path, if you already know your need.
Data maturity path
Where are you today?
Four steps. Enter at yours we handle the climb.
01 - you are here ?
Analysis
Dashboard & Reporting
One source of truth: your numbers, trusted, auto-refreshed, actually used by leadership.
02 - you are here ?
PREDICTION
Machine learning
Models that predict, score and detect each one built against a single measurable business target.
03- you are here ?
Assistance
LLM
Your knowledge, on tap: assistants and document intelligence grounded on your own data.
04 - you are here ?
Agentic AI
ARTIFICIAL INTELLIGENCE
AI that doesn’t just answer it acts, agents that execute multi-step work inside your tools, under supervision and with guardrails.
Why steps
What you get with us
ONE TARGET PER MODEL.
Every initiative starts with a single measurable business target the contract that kills eternal POCs.
AI SHIPS LIKE SOFTWARE.
Code review, automated tests, security review our three release gates apply to models and agents too.
YOUR DATA STAYS YOURS.
Private deployments by default, zero data sent to public models, FR/EN/AR environments.
Built to be IN PRODUCTION.
We were shipping machine learning before the hype 30+ models run in real operations today.
FAQ
FREQUENTLY ASKED QUESTIONS
1. What does Data & AI Engineering cover?
Our Data & AI Engineering services cover the systems required to turn data into usable business capabilities, including data engineering, analytics, machine learning, generative AI, LLM applications and AI-powered automation.
2. Can STEPS help us build a data foundation before implementing AI?
Yes. Reliable AI depends on accessible, well-structured and relevant data. We can help assess your existing data environment, build pipelines and improve the foundations required for analytics and AI use cases.
3. Can you integrate AI into our existing business applications?
Yes. AI capabilities can be integrated into existing applications, APIs, workflows and business systems. This can include intelligent assistants, document processing, prediction, recommendations, automation and other AI use cases.
4. How do you move an AI prototype into production?
We approach productionization as more than simply deploying a model. Depending on the use case, this can involve data pipelines, model or LLM integration, evaluation, APIs, security, monitoring, scalability and integration with existing business workflows.
5. How do you make sure AI solutions are reliable?
We define measurable evaluation criteria and combine appropriate testing, data validation, model or LLM evaluation, monitoring and business controls. For sensitive workflows, human review and explicit authorization rules can also be incorporated.