Fintech AI Development Services

It depends on the use case, data readiness, deployment model (cloud, private or on-premise) and integration scope.

As a general reference, discovery, validation and prototyping engagements start from around $30,000. Enterprise projects involving legacy integrations, regulated workflows, AI functionality or full-scale product development often range from $150,000 to $1,000,000+. Itexus provides a detailed estimate after an initial discovery session and technical scoping.

Yes. Itexus deployed an open-weight LLM on-premise inside a security-constrained bank, within the bank’s own infrastructure, and reached a production MVP in three weeks. Private cloud deployment is also an option.

One with clear value, contained risk and available data. Document intelligence — classifying documents, splitting PDF bundles, extracting fields — is a common starting point because it removes manual work without making credit or client-facing decisions. The architecture should be chosen so later use cases can reuse it.

Both, depending on the problem. LLMs and RAG suit language-heavy work such as documents, research and conversation. Credit scoring, fraud detection and forecasting usually call for statistical and machine learning models where accuracy and explainability matter.

Through retrieval grounded in approved sources, validation and evaluation of outputs, human review steps for consequential decisions, access controls on what the model can see, and logging of AI actions for audit.

A focused first use case can reach production quickly: three weeks for on-premise document intelligence in a bank. In a larger engagement, Itexus built a supply chain finance platform with AI underwriting in seven months and cut credit memo preparation from two weeks to four hours.

AI-first development is most effective for greenfield products, where the architecture, requirements, documentation and technical guardrails can be designed for agent-based development from the start.

AI-accelerated development is better suited to legacy systems, where tightly coupled architecture and incomplete documentation require more manual analysis, refactoring, test generation and controlled modernization. In both cases Itexus keeps architecture oversight, QA, security and compliance control.

Yes. Itexus provides post-launch support and maintenance for production financial systems, including L2/L3 support, monitoring, incident response, patch and release management, performance tuning, backup and rollback support, and ongoing improvements.