Financial technology engineering

We design and build the data infrastructure that powers modern enterprise intelligence — from real-time streaming pipelines and enterprise data platforms to ML pipeline support and agentic AI automation. Our data teams have processed billions of records per month in production with Banking & Capital Markets clients.  We have deep expertise in event-driven architectures, Apache Kafka, Spark, Databricks, and regulatory data governance. Delivered nearshore with the same quality and time-zone alignment as an onshore team.

We architect, build, and operate cloud-native infrastructure across AWS and GCP — hyperscaler-agnostic by design, without allegiance to any single vendor. Our platform engineers select the right tools for each client’s regulatory Banking environment and existing infrastructure. Capabilities include Kubernetes, Docker, Terraform, CI/CD pipelines, Site Reliability Engineering, DevSecOps, and FinOps across PCI-DSS, HIPAA, DORA, and CPNI-compliant environments.

We build native and cross-platform mobile banking applications for iOS (Swift) and Android (Kotlin) — from retail and private banking apps and cardholder experiences to high-net-worth concierge platforms and corporate banking tools. Our mobile engineers specialize in PCI-DSS compliant payment flows, biometric authentication, card digitization, and secure mobile wallet integrations (including React Native and Flutter). Nearshore delivery enables faster team scaling without sacrificing engineering quality.

End-to-end architectural blueprints for complex, mission-critical systems — cloud migration roadmaps, core platform modernization strategies, enterprise integration patterns, and reference architectures tailored to each client’s regulatory environment. Specific depth in the financial services core banking sector compliance (ISO 20022, PCI-DSS). Our architects are embedded in delivery — not parachuted in at the start and gone before go-live.

Quality embedded into every Financial Technology Engineering (FinTech Eng.)  engagement — not bolted on at the end. Our QA engineers design and execute automated and manual testing frameworks that validate functional correctness, performance under load, regulatory compliance, and security posture across financial services, healthcare, and telecom environments. Technical product managers bridge business intent and engineering execution, owning backlogs, sprint ceremonies, and stakeholder communication in technically complex, regulated programs. Nearshore delivery means QA and TPM resources operate in your time zone, in real time, without coordination lag.

Experienced engineering managers and tech leads who oversee delivery quality and align technical execution with business outcomes. Our Client Service model provides senior PwC oversight from kickoff through delivery — giving clients the speed of staff augmentation with the accountability of a managed engagement. This is what differentiates Financial Technology Engineering (FinTech Eng.) from traditional staff augmentation or the broader Custom Application Development and Testing capability: domain-specific senior talent, nearshore delivery between the US and Mexico, and PwC-level delivery governance — purpose-built for Banking & Capital Markets.

Experience in developing business process automation platforms purpose-built for financial institutions, eliminating the manual, error-prone back-office workflows that slow operations and create compliance risk. Using agentic AI, we automate high-volume, rules-based processes across dispute resolution, accounts payable, invoice generation, wire instruction handling, and lending operations without requiring a full systems overhaul. Our platform connects to existing legacy systems, SaaS tools, and document workflows, applying process mining to identify the highest-value automation targets before building. In production, our automation has processed over 100 million invoices, reduced tax liabilities by $20M, and cut invoice generation time from one week to ten minutes at 99.5% accuracy. Every workflow includes built-in auditability and safety controls, critical for regulated environments where AI-driven decisions must be explainable and traceable.