Saviano helps turn a research tool or processing workflow into an application an entire team can use. We develop custom scientific software, data platforms and interfaces that support collaboration and make results easier to trace.
A script that works for one researcher can become difficult to maintain when several teams depend on it. We organise inputs, parameters, processing and outputs into an application with suitable access permissions and user journeys.
We start with your data formats, processing volumes and execution constraints. The interface can then support job submission, progress tracking and result comparison while keeping the relevant parameters visible.
A research platform should make it possible to understand how a result was produced. Depending on scope, it can preserve the versions of the dataset, code, parameters and dependencies used for each run.
Software tests check data transformations and application behaviour. Your researchers or scientific partners define and approve scientific validity criteria, methods and the interpretation of results.
We design data views, charts and exports around your users. Sharing permissions, retention requirements and connections to existing tools are agreed during scoping.
Deployment can include a processing queue, monitoring and operating documentation according to the expected workload. An initial version using a representative dataset lets the team validate behaviour before broader use.
These scenarios illustrate possible applications. They are not client case studies or reported project results.
A team imports versioned datasets, runs a documented processing workflow and compares outputs across teams. Parameters and generated files stay attached to each run. This scenario is illustrative.
Scoping reviews the existing code, dependencies, formats and expected workload. It determines what can be reused and which components are needed for multiple users.
Your scientific team defines the methods and validates the results. Saviano handles software engineering, interfaces, software tests and the operation specified in the contract.
We agree on access permissions, hosting requirements, backups and sharing rules. These choices depend on data sensitivity and the obligations of the project.
A business tool reachable from a browser, with nothing to install, that holds up under load and updates without interrupting anyone.
Architecture, permissions, integrations and incremental delivery of your SaaS platform.
Finding out, before building, whether a model can do the task on your data and at what cost. An evaluation set, a measured comparison, a verdict.
Industry, research and biology: users, data and acceptance criteria shape the application.
Production tracking, traceability, field applications and business system integrations.
02Data collection, processing, visualisation and collaboration for research teams.
03Sample tracking, result exchange and automation of laboratory workflows.