Artificial Intelligence & Data
From strategy to production: we design your data platforms, industrialize your models with MLOps and activate generative AI to create sustainable and measurable value.
Why choose Sama Solutions?
Our approach combines strategy, governance and delivery. We prioritize high ROI use cases, build modern data foundations (lakehouse, streaming) and industrialize the ML lifecycle with MLOps for reliable and secure production deployment.
Our AI & Data services
Data & AI Strategy
Define a Data/AI trajectory aligned with your business objectives.
- Maturity assessment and business cases
- Use case prioritization (marketing, operations, finance, HR)
- Data/AI roadmap and governance model
Data Platform (Lakehouse & Streaming)
Build a modern, scalable and governed data foundation.
- Lakehouse (Data Lake + Warehouse), ETL/ELT
- Real-time streaming (Kafka, pub/sub), batch/stream ingestion
- Catalogs, lineage, data contracts, security and access
Data Governance & Quality
Make your data reliable and traceable for analytics and AI.
- Data ownership, stewardship, policies and standards
- Quality: profiling, tests, pipeline observability
- MDM/RDM, cataloging, security and privacy (GDPR)
Analytics & Product BI
Give business teams actionable and reliable insights.
- Semantic modeling, dashboards and self-service BI
- Product metrics: funnels, cohorts, attribution, experimentation
- Data storytelling and adoption
Generative AI & LLMOps
Deploy secure and governed assistants and generation engines.
- Use cases: RAG, business assistants, summarization, classification
- LLMOps: evaluation, monitoring, guardrails, prompt engineering
- Privacy, security, compliance and cost control
Data Science & Machine Learning
Create predictive and prescriptive models with business impact.
- Demand forecasting, churn, recommendation, risk scoring
- Computer vision, NLP, operational optimization
- Feature store, experimentation and evaluation
MLOps & Production
Industrialize the ML lifecycle: robustness, repeatability, traceability.
- Training/serving pipelines, ML CI/CD, canary deployment
- Monitoring: data/model drift, performance, costs
- Registry, versioning, governance, explainability
Acculturation & Change
Ensure adoption through training and responsible usage frameworks.
- Data/AI training, business workshops, use case design
- Responsible AI framework (ethics, bias, transparency)
- Data communities, playbooks and adoption kits
Approach and deliverables
We advance in increments: framing, POC, pilot, industrialization. Deliverables are designed to go to production and measure value.
- Data platform blueprint, security and governance
- Use case backlogs, datasets, models and metrics
- ML pipelines, model registries, monitoring and alerting
- Analytics and cost dashboards, responsible AI usage guide
Discovery Pack: Data & AI Audit (10 days)
A rapid diagnostic to prioritize use cases and secure production deployment.
- Review of data platform, governance and security
- Use case evaluation and quick wins identification
- 90-day action plan (MLOps, quality, generative AI)
- Executive presentation and roadmap
FAQ — AI & Data
Which AI use cases generate value quickly?
Business assistants, RAG on your document base, recommendation, forecasting, scoring and repetitive task automation. We prioritize by impact and feasibility.
How long to put a model into production?
Between 4 and 12 weeks depending on complexity and data availability. MLOps practices and a pilot accelerate industrialization and reliability.
How do you manage data quality and governance?
Data ownership, standards, observability, quality tests, cataloging and MDM. Indicators track reliability and compliance (including GDPR).
Is generative AI safe and compliant?
Yes, with a responsible usage framework: privacy, security, prompt control, evaluation/monitoring, guardrails and cost control. Sensitive data is protected.
Which clouds and tools do you work with?
Major hyperscalers (AWS/Azure/GCP), data platforms (Databricks, Snowflake, BigQuery), orchestration, MLOps and pipeline observability tools.
Do you help with business adoption?
Yes: training, workshops, data storytelling, usage frameworks and communities. The goal is to anchor AI and data in business processes.
Tell us about your Data & AI use cases
Indicate your objectives, data scope and constraints. We'll get back to you within 24–48h with a workshop proposal or targeted audit plan.
Schedule a Data & AI audit