Industries
Deep engineering for complex markets
We apply financial-grade engineering rigor to every sector we serve, solving the problems others call impossible.
Engineering rigor with domain depth.
Financial-grade engineering across every sector
Our roots are in financial services, Latin America's most demanding engineering environment. The same standards we built for tier-1 banks transfer to every complex sector we enter, engineering depth, not just technology adoption, is the differentiator in markets where 90% of finance functions will adopt AI by 2026. (Gartner (2024))
Domain expertise that accelerates delivery
We don't just code for healthcare, energy, and retail, we know the regulations, data models, integration points, and failure modes. That knowledge compresses timelines and reduces risk.
Financial Services
From core banking modernization to real-time payments and AI-driven risk intelligence, we build the critical systems financial institutions rely on to operate, innovate, and scale.
- Core & channels modernization
- Payments & settlement platforms
- Fraud, risk & operational intelligence
- Open finance & connected ecosystems
- Tokenization & digital assets
Multi-sector expertise
The same engineering rigor born in financial services, applied to every complex sector we serve.
Engineering precision in every policy and claim
Core system modernization, AI-driven underwriting, claims automation and anti-fraud intelligence for enterprise insurers and brokers at scale.
- Policy admin modernization
- AI-powered underwriting
- Claims automation & STP
- Fraud detection
- Digital distribution
Platforms that match the pace of commerce
Marketplace orchestration, pricing intelligence, loyalty personalization and payment flows, built for the speed and complexity of modern retail.
- Marketplace architecture
- Loyalty & personalization
- Pricing intelligence
- Payments orchestration
- Digital supply chain
Digital systems for regulated health ecosystems
Interoperable health platforms, patient-centric digital journeys and responsible AI, meeting the operational and regulatory demands of healthcare.
- Digital health platforms
- Interoperability & data exchange
- Operational automation
- Patient digital journeys
- Responsible AI in healthcare
Smart infrastructure for critical operations
Real-time data platforms, predictive maintenance, trading systems and process automation, for sectors where downtime is not an option.
- Critical operations systems
- Real-time data platforms
- Predictive maintenance
- Energy trading platforms
- Process automation at scale
Modern platforms for connectivity at scale
BSS/OSS modernization, digital self-service channels, billing architecture and AI-driven operations for operators reimagining the customer experience.
- BSS/OSS platform modernization
- Self-service channels
- Data & automation
- Billing & revenue assurance
- Network intelligence
Orchestrating movement with software precision
Operational platforms, tracking & orchestration systems, mobility marketplaces and AI-driven efficiency for companies that move the world.
- Operational platforms
- Tracking & orchestration
- Mobility marketplaces
- Multi-system integration
- AI efficiency
// FAQ
Frequently asked questions.
Sciensa serves seven sectors: Financial Services, Insurance, Retail & E-Commerce, Healthcare, Energy & Utilities, Telecommunications, and Mobility & Logistics. The deepest expertise lies in Financial Services and Insurance, banking, payments and insurers, where Sciensa has operated since 2014. This includes experience with BACEN and SUSEP regulations, Open Finance infrastructure, claims automation and core system modernization across 40+ financial and insurance clients.
Regulated sectors have constraints that change the nature of technology delivery: compliance requirements that must be designed into the architecture from the start (not added later), audit and explainability requirements that affect how systems are built, data residency and privacy requirements that restrict infrastructure choices, and operational SLOs driven by regulatory expectations. A generalist firm learns these constraints during the project; a specialist brings them as starting premises.
In unregulated contexts, the main constraints are user experience, performance, and cost. In regulated sectors, compliance is an equal constraint from day one, a digital banking onboarding that works perfectly but fails KYC requirements cannot be launched. Data architecture must account for audit trails, data lineage, and the right to erasure from the start. Security must meet sector standards. Tests must cover compliance scenarios, not just functional ones. These constraints slow teams that don't know them and are invisible to teams that do.
Domain knowledge changes which technical options are even on the table. An engineer who understands PIX knows the latency budget for fraud scoring before writing a line of code. One who understands FHIR knows which data model to use before designing the API. One who knows BSS architecture knows which components can be strangler-figged and which require a more careful migration path. Domain knowledge compresses the discovery phase and prevents costly late rework when technical decisions collide with domain constraints.
Operating in a complex market?
Let's talk about how engineering precision and AI can accelerate your digital agenda.