We work end to end across the data journey, from streaming and data engineering to analytics and AI. Every project is tied to a business objective, owned by our team from start to finish and run with full transparency on progress, risks and decisions.
Our professionals are highly qualified and certified, ready to support companies from structuring the data foundation to generating value with advanced analytics and business-oriented solutions.
Batch and real-time pipelines, layered lakehouse architectures and event-driven ingestion, from the data source to analytical consumption.
Predictive modeling, forecasting and mathematical optimization to support decisions such as raw material purchasing and supplier selection.
We interpret data and turn it into clear dashboards and metrics, so teams can monitor KPIs and decide quickly.
Infrastructure as code with Terraform, CI/CD pipelines and Kubernetes on Azure, AWS and Confluent Cloud, with observability through traces, logs and metrics.
Data modeling, real-time replication, migration and performance tuning for databases in critical environments.
Generative AI, computer vision and MLOps: models and prompts in production with governance, traceability and continuous monitoring.
We work on mission-critical projects, high data volumes and real-time scenarios, helping organizations build modern, resilient ecosystems.
Real-time platforms with Confluent, Kafka and Flink, built for high volume, low latency and high availability.
Evolution to modern, scalable architectures without compromising performance or operations.
People, processes and tools governed end to end, from the data source to dashboards and reports.
Production deliveries in critical environments, with operational continuity and data integrity.
Agile cycles with a steady cadence of rituals, continuous replanning and a clear focus on reaching production.
Step 1
Scope, business objectives, architecture, roadmap and initial backlog.
Step 2
One- or two-week cycles with epics and tasks, each with an owner and a deadline.
Step 3
Tests, reprocessing and quality checks by sampling.
Step 4
Release to the development, staging and production environments.
Step 5
Monitoring, continuous improvement and new demands.
Everything that happens in your project stays visible: in the rituals, in the tools you already use and in the reports you receive.
We take part in, and help build, the rituals of each client's management model.
Full transparency: risks, dependencies and actions reported at every ritual, with continuous replanning and a focus on production.
Every delivery is tied to a business objective and an agreed indicator.
Our team answers for the end-to-end result, not just for executing the tasks.
Architecture decisions are reviewed by our technical leads before they reach the client.
Jira, Azure DevOps or the tool you already use, with epics, sprints and tasks, each with an owner and a deadline.
A traffic-light roadmap per system or workstream.
Risk register, mitigations, checkpoints and key dates.
Our internal contract management system tracks hours by client, project and task, and time logged by professional and activity.
Flexible models that can be combined in the same contract, all with governance and monthly billing.
Main model
Defined scope, timeline and profiles, with Datatchê management and formal acceptance of each delivery.
A dedicated team for a defined period, with planned profile rotation.
Full-time specialists, integrated into the client's team.
Hours consumed as needed, for predefined profiles.
Continuous operation of products in production, with SLAs by criticality and NPS.
Technical transparency before any decision: a structured opportunity for us to demonstrate our approach in practice, with real deliverables and jointly defined goals.
Recommended when the goal is diagnosis and direction.
up to 15 days
No initial commercial commitment.
Recommended when the goal is practical validation.
up to 30 days
No initial commercial commitment.
Start with an Assessment or a POC, with no initial commercial commitment.
