At Logiciel, we combine the best of software and data engineering technologies to build scalable, AI-ready systems that power product innovation and operational intelligence.

Book an Intro Call Common Questions

5 areas

Data engineering technology areas we use

3 areas

Software engineering technology areas we use

Why Logiciel

Why Software and Data Engineering Belong Together.

Software Engineering Technologies → build, scale, and automate core systems.

Data Engineering Technologies → structure, transform, and deliver insights.

Backend Engineering

Outcome: Microservice-driven, resilient systems that scale effortlessly.

Frontend & User Experience Engineering

Outcome: Fast, interactive, and secure user experiences optimized for performance.

DevOps & Automation Technologies

Outcome: Continuous delivery with full observability and reliability.

Software Engineering

Technology

Software Engineering Technologies We Use.

Technology · 01

Languages

Python, Node.js, .NET, Go, Java.

Technology · 02

Frameworks

Express.js, Django, Spring Boot, FastAPI.

Technology · 03

Cloud & Serverless

AWS Lambda, ECS, Azure Functions, GCP Cloud Run.

Technology · 04

Databases

PostgreSQL, MongoDB, DynamoDB, Aurora.

Technology · 05

Frameworks

React, Next.js, Angular, Vue.js.

Technology · 06

Mobile

Flutter, React Native, Kotlin, Swift.

Technology · 07

APIs

REST, GraphQL, gRPC.

Technology · 08

Testing

Jest, Cypress, Playwright.

Technology · 09

CI/CD

GitHub Actions, Jenkins, CircleCI.

Technology · 10

Infrastructure as Code

Terraform, AWS CDK, Pulumi.

Technology · 11

Containerization

Docker, Kubernetes, Helm.

Technology · 12

Monitoring & Logging

Datadog, Prometheus, Grafana, ELK Stack.

Technology

Data Engineering Technologies We Use.

Streaming: Apache Kafka, AWS Kinesis, Google Pub/Sub.

Technology

Batch Ingestion: Fivetran, Airbyte, Stitch.

Technology

ETL/ELT Tools: dbt, AWS Glue, Apache NiFi, Airflow.

Technology

API Integrations: Custom ingestion via REST or webhooks.

Technology

Cloud Data Warehouses: Snowflake, BigQuery, Redshift.

Technology

Data Lakes: AWS S3, Azure Data Lake, Delta Lake.

Technology

Lakehouse Engines: Databricks, Synapse, Presto.

Technology

Metadata & Catalogs: Amundsen, DataHub, Glue Data Catalog.

Technology

Outcome: A single source of truth

structured, secure, and query-ready.

Technology

ETL Pipelines: Airflow DAGs and Glue Jobs.

Technology

Data Modeling: dbt, SQL Mesh, Great Expectations for quality control.

Technology

Workflow Orchestration: Step Functions, Prefect.

Technology

Visualization Tools: Power BI, Tableau, AWS QuickSight, Looker.

Technology

Query Engines: Athena, Trino, Presto.

Technology

Custom Dashboards: React + Chart.js, Grafana, Metabase.

Technology

ML Platforms: AWS SageMaker, Vertex AI, Azure ML, Databricks MLflow.

Technology

Feature Stores: Feast, SageMaker Feature Store.

Technology

Data Science Stack: TensorFlow, PyTorch, scikit-learn.

Technology

Automation: MLOps orchestration using Airflow + GitOps pipelines.

Technology

Why Logiciel

Why Choose Logiciel.

Engineering Excellence

Certified engineers across software, cloud, and data domains.

↳ Why Logiciel

AI-Ready Systems

Every build designed to integrate with ML and analytics.

↳ Why Logiciel

Faster Delivery

Sprint-aligned execution with measurable milestones.

↳ Why Logiciel

Proven Tools, Proven Outcomes

Enterprise-grade reliability at startup speed.

↳ Why Logiciel

Security by Default

IAM, encryption, and governance included from day one.

↳ Why Logiciel

Engagement

Engagement Models.

Model	Ideal For	Core Benefit
Integrated Software + Data Team	Full-scale platform builds	Unified sprint delivery across both domains
Project-Based Engineering	Targeted integrations or upgrades	Predictable timelines and measurable ROI
Technology Consulting & Audit	Architecture optimization	Strategic modernization roadmap

Selected work

Tailored engineering for your industry.

Zeme · Real Estate Cut development costs 50% and launched 3× faster with dedicated dev teams.

Real Estate

Cut development costs 50% and launched 3× faster with dedicated dev teams.

Leap · Construction Scaled to 7-figure ARR with AI-augmented software teams.

Construction

Scaled to 7-figure ARR with AI-augmented software teams.

KW · Real Estate 56M+ workflows automated, saving agents 30% time with AI-powered tasks.

Real Estate

56M+ workflows automated, saving agents 30% time with AI-powered tasks.

Resources

Insights for tech leaders.

Whitepaper · PDF

The State of AI-Assisted Engineering 2026

Whitepaper · PDF

Building AI-Ready Healthcare Data Infrastructure: The 90-Day Roadmap from Staging Bottleneck to Production

Whitepaper · PDF

Building AI-Ready Data Foundations in Healthcare

In their words

What our clients say.

Teams that needed to ship fast, and did. Here's what partnering with Logiciel felt like from the inside.

I would highly recommend them to anyone looking to scale quickly or needing support in engineering, product, or QA.

Patrick Fingles

CEO, Leap

We don't just call them Logiciel; they're part of the Zeme team. Within the first week they were contributing meaningfully to our codebase.

Elior Alayev

Founder & CEO, Zeme

The Logiciel team worked tirelessly and built everything we needed, with security and best practices across our entire platform. It allowed us to become #1 in our industry, and we couldn't have done it without them.

David Buzzelli

Co-Founder, JobProgress

Questions

Frequently asked questions.

What is software and data engineering technology?

It’s the combination of modern software frameworks and data systems used to build scalable, intelligent applications.

What technologies do you use?

React, Node, Python, AWS, Airflow, dbt, Snowflake, SageMaker, Power BI, Kubernetes, Terraform.

What industries benefit most?

SaaS, PropTech, FinTech, and enterprise platforms handling high data velocity.

Do you support hybrid or multi-cloud?

Absolutely AWS, GCP, Azure, or on-prem hybrid deployments are fully supported.

What ROI can we expect?

Faster analytics, lower cloud spend, and greater product velocity measurable every sprint.

Why combine software and data engineering?

Because real-time, intelligent applications require continuous data ingestion, processing, and analytics supported by scalable software foundations.

Can Logiciel modernize legacy systems?

Yes we upgrade both software architecture and data pipelines for cloud and AI readiness.

How do you ensure system security?

IAM, encryption, VPC isolation, and compliance frameworks (SOC-2, GDPR, HIPAA).

How long does a project take?

Typical enterprise builds take 8–14 weeks for MVP, full deployment in 3–4 months.

What’s the first step?

Schedule a call we’ll assess your current tech stack and design a roadmap for unified software and data engineering.

Let's build

Ready to Get Started?.

Book a call with our team today and see how Logiciel can transform your operations.

Software and Data Engineering Technology.

See Logiciel in action.

Why Software and Data Engineering Belong Together.

Backend Engineering

Frontend & User Experience Engineering

DevOps & Automation Technologies

Software Engineering Technologies We Use.

Languages

Frameworks

Cloud & Serverless

Databases

Frameworks

Mobile

APIs

Testing

CI/CD

Infrastructure as Code

Containerization

Monitoring & Logging

Data Engineering Technologies We Use.

Streaming: Apache Kafka, AWS Kinesis, Google Pub/Sub.

Batch Ingestion: Fivetran, Airbyte, Stitch.

ETL/ELT Tools: dbt, AWS Glue, Apache NiFi, Airflow.

API Integrations: Custom ingestion via REST or webhooks.

Cloud Data Warehouses: Snowflake, BigQuery, Redshift.

Data Lakes: AWS S3, Azure Data Lake, Delta Lake.

Lakehouse Engines: Databricks, Synapse, Presto.

Metadata & Catalogs: Amundsen, DataHub, Glue Data Catalog.

Outcome: A single source of truth

ETL Pipelines: Airflow DAGs and Glue Jobs.

Data Modeling: dbt, SQL Mesh, Great Expectations for quality control.

Workflow Orchestration: Step Functions, Prefect.

Visualization Tools: Power BI, Tableau, AWS QuickSight, Looker.

Query Engines: Athena, Trino, Presto.

Custom Dashboards: React + Chart.js, Grafana, Metabase.

ML Platforms: AWS SageMaker, Vertex AI, Azure ML, Databricks MLflow.

Feature Stores: Feast, SageMaker Feature Store.

Data Science Stack: TensorFlow, PyTorch, scikit-learn.

Automation: MLOps orchestration using Airflow + GitOps pipelines.

Why Choose Logiciel.

Engineering Excellence

AI-Ready Systems

Faster Delivery

Proven Tools, Proven Outcomes

Security by Default

Engagement Models.

Tailored engineering for your industry.

Cut development costs 50% and launched 3× faster with dedicated dev teams.

Scaled to 7-figure ARR with AI-augmented software teams.

56M+ workflows automated, saving agents 30% time with AI-powered tasks.

Insights for tech leaders.

The State of AI-Assisted Engineering 2026

Building AI-Ready Healthcare Data Infrastructure: The 90-Day Roadmap from Staging Bottleneck to Production

Building AI-Ready Data Foundations in Healthcare

What our clients say.

Frequently asked questions.

Ready to Get Started?.