AI & Data Engineering Services

AI fails without reliable data. Data is wasted without AI. Modern AI requires:

• Clean, governed, and structured data

• Scalable pipelines and real-time processing

• Feature stores, embeddings, and vector search

• Efficient inference and GPU utilization

• Automated ML training, deployment, and monitoring

Logiciel unifies AI + Data Engineering to deliver production-ready systems and actionable insights.

Data Ingestion & Pipelines

• Structured/unstructured data, APIs, events, logs, batch imports

• Tech: Kafka, Kinesis, AWS Glue, Airflow, Lambda

• Outcomes: scalable, reliable ingestion

Data Lakes & Warehouses

• Cloud-native storage, S3 lakehouse, Redshift, Snowflake, Athena

• Outcomes: unified, AI-ready datasets

ETL/ELT & Transformation

• Cleaning, validation, feature extraction, enrichment

• Tools: Spark, Glue, Lambda, dbt

• Outcomes: reliable, business-aligned data

Data Quality & Governance

• Schema enforcement, PII masking, lineage, compliance

• Outcomes: trusted, auditable datasets

ML Engineering

• Model training, hyperparameter tuning, NLP, vision, forecasting

• Frameworks: PyTorch, TensorFlow, Scikit-learn

• Outcomes: deployable, accurate ML models

LLM & AI Systems

• ChatGPT-style agents, document intelligence, workflow automation

• Tools: GPT-4o/5, Claude 3, LangChain, LlamaIndex

• Outcomes: enterprise-grade AI, automated workflows

RAG & Vector Search Pipelines

• Embeddings, hybrid search, source verification, hallucination reduction

• Outcomes: accurate, reliable AI responses

Multi-Agent AI Systems

• Complex workflow automation, dynamic decision-making, self-reflection loops

• Outcomes: 5–10x efficiency, reduced manual effort

Real-Time AI Inference

• Chat, classification, embeddings, streams, multi-doc analysis

• Outcomes: faster responses, lower GPU cost, high concurrency

MLOps & Monitoring

• Continuous training, drift detection, rollback, versioning, feature stores

• Tools: MLflow, Kubeflow, Airflow, SageMaker Pipelines

• Outcomes: reliable, long-term model health

Advanced Analytics & BI

• Dashboards, KPIs, product insights, forecasting

• Platforms: Tableau, Power BI, QuickSight, Looker

• Outcomes: faster, data-backed decisions

• Data & AI Assessment – Evaluate pipelines, AI readiness, and gaps

• Architecture & Strategy – Design full-stack AI + data ecosystem

• Build & Implement – Pipelines, ML systems, LLMs, RAG layers, agents

• Deploy & Optimize – Monitoring, performance tuning, scaling

• Scale & Evolve – Continuous improvement, retraining, roadmap expansion

We don’t just build AI. We build scalable AI ecosystems powered by world-class data engineering.

• Full-stack AI + Data engineering capability in one team

• Experience with real-world enterprise workloads

• AI-first engineering culture

• Rapid development cycles

• Infrastructure, DevOps, pipelines, ML, and LLM engineering under one roof

• Proven experience delivering automation and AI for 50M+ workflows

• Strong cloud + data + ML + LLM integration expertise

• Predictable delivery with measurable outcomes