Senior engineering for banking, insurance, trading and risk systems, combining more than a decade of our founders’ delivery experience with controlled AI-enabled execution.
We build and modernise software, models, data pipelines and connected systems, from data and architecture through delivery.
AI for production with controls you can explain and audit
We pair AI-enabled delivery and embedded AI features with explicit data access, clear interfaces, domain rules and defined review roles.
Evaluation, human review and traceability remain part of the solution, so it holds up in production and audit, not just in a demo.
Reliable data, reproducible calculations
We connect market, risk and operational data with calculations, quantitative models and validation. Lineage and quality controls extend from the source to the dashboards, reports and APIs that use the results.
Results remain explainable and reproducible end to end, so risk and reporting owners can rely on them.
Clarity before major investment
We map the existing estate, options and constraints, then test uncertain integration or migration assumptions with prototypes before committing to a direction.
An architecture or migration question becomes a staged, testable delivery path, with the capabilities worth preserving clear from the outset.
Software you can keep changing safely
We build, modernise and integrate applications, services, interfaces and quantitative models. Testing, CI/CD and observability keep change controlled in regulated environments.
User interfaces, domain logic, data, integrations and operations ship as one maintainable system, not as a prototype that stalls at go-live.
Our deepest experience is in financial services. The founders bring more than a decade of work across digital banking, trading and markets systems, risk, capital and regulation, and quantitative platforms.
Channels and platforms modernised in stages
We connect web and mobile through shared components and modularise existing platforms with microapps and central integration services.
The existing estate can keep operating while it is renewed in stages, without waiting for a complete rewrite.
Integrating data flows and platforms into live operations
We connect desk requirements with architecture and implementation, then integrate the result into the existing estate.
The change becomes usable in the trading desk's daily workflow, rather than remaining an isolated technical component.
Quantitative methodology implemented as reproducible software
Methodology, numerical implementation and documentation describe the same calculation, so a run can be repeated and reviewed from the same inputs.
The model methodology remains traceable through the calculation run to the capital or solvency result.
Research, execution and operations as one connected platform
We develop and modernise the systems quantitative teams use to research, validate, execute and monitor strategies in operation.
The starting point can be a single component, the integration of existing systems or a clearly bounded platform stage.
Current Nuitio systems and work drawn from over a decade of our founders’ experience – built, adopted, approved or in production.
The team defines the architecture, domain and quality rules against which planning, implementation and repository audit are checked.
Nuitio developed the platform from the ground up using its software delivery pipeline.
Nuitio and the team turned the current state and priorities into a defined intake route, clear prioritisation and scoping, delivery KPIs and cross-training.
For every balance-sheet scenario produced by the group risk model, the contagion model calculates how defaults and rating migrations affect other legal entities through ownership, internal reinsurance and guarantees.
All relevant sensitivities and position data were consolidated across the bank, assigned to the prescribed risk factors, risk classes and buckets, and calculated using the regulatory parameters.
A monitored, gap-free Bloomberg stream feeds optimised live calculations and delivers current figures directly to traders’ screens.
Reusable components provided identification, authorisation, customer communications and analytics across all three channels.
The study compared ways to bring the digital bank closer to the Avaloq Front Platform, weighing effort, risks, synergies and total cost against the capabilities to preserve.
A central hub provided reusable front-end functions and a common integration point for new microapplications.
The portal integrated the microapplications with the Avaloq Front Platform and connected microservices from several third-party systems.
The modernisation also covered the migration of the existing data model and implementation of the CRM processes.
Every engagement follows one clear path, from clarifying the outcome to handing it over, led by a senior team. We agree scope and approach around the result, not as a fixed package.
We start with the result that needs to work, the current system or way of working, the constraints, the people involved and a clear definition of done.
We turn the outcome into a concrete path: sequence, responsibilities, delivery mode, and time and cost expectations. Where uncertainty matters, we test it before committing to implementation.
We deliver the agreed outcome and make it operable beyond the engagement. We finish when your team has the knowledge and ownership to run it without us.
The people clarifying requirements and architecture remain involved through implementation. Options are tested against what can actually be built, integrated and operated.
A senior team leads the engagement from clarification through implementation. The people making the key decisions remain accountable for the delivered result.
We define the architecture, domain constraints, review roles and quality checks before AI-assisted work proceeds, then verify the result against them.
Nuitio is founder-led. Tobias and Fabian are your direct points of contact, combining quantitative finance and risk modelling with software architecture and platform engineering: two complementary backgrounds, one senior team.
PhD, ETH Zürich · Financial Risk Manager · IMD Future Leaders
MSc Computer Science, ETH Zürich · MAS MTEC, ETH Zürich
Send us a short note about what you have in mind. In an initial conversation, we discuss the project and possible next steps.
