Praxent

AI and ML

AI Command — Fintech Agents In Production

Praxent helps financial services firms achieve AI Command through a three-phase framework: Decode (AI-accelerated legacy modernization), Activate (production-ready agentic features in governed frameworks), and Compound (continuous AI innovation via dedicated product pods). AI is embedded in underwriting, compliance automation, claims acceleration, and personalized experiences — governed, auditable, and ROI-driven.

Product engineering

Digital Products — Transform concepts into reality

Designing and building new financial products with specialization in digital experience, speed to market, and foundational architecture. Covers UX strategy, UX design, full-stack development, mobile and web apps, and cloud-native solutions for financial services.

Advisory and strategy

Enterprise Systems — Navigate from complexity to agility

Transforming legacy systems and maximizing engineering productivity with a focus on human-centered redesigns, systems integration, DevSecOps, and cloud infrastructure. Includes architectural assessments, application portfolio rationalization, and fintech vendor recommendations.

Product engineering

Fintech Talent — Expand to accelerate

Augmenting client teams with US and LATAM-based talent hand-selected for financial services experience, technical expertise, and CAN/DO values. Supports engineering staffing, designer staffing, and PM staffing.

Advisory and strategy

CanDone.os — Technology Operating Model

A technology operating model designed to enhance the performance of engineering teams, increasing on-time delivery and reducing rework. Offers agile transformation and a proven way to improve velocity, productivity, and team satisfaction.

Design and experience

UX Strategy & Design — Human-centered digital experiences

End-to-end UX services from strategy to high-fidelity design, including customer research, journey mapping, wireframes, prototypes, and design systems tailored to financial services digital products.

Data and analytics

Data — Strategy, Architecture & Implementation

Data strategy, architecture, and implementation services for financial institutions, including data lake and business intelligence implementations.

Cloud and platform

Cloud and DevOps — Cloud strategy, FinOps, DevSecOps

Cloud strategy and implementation, FinOps, and DevSecOps services across AWS, Azure, Google Cloud, Heroku, and CloudFlare for financial services firms.

A branded three-phase framework (Decode, Activate, Compound) for helping financial services firms move from AI pilots to full production AI embedded in their platforms — covering underwriting, compliance, claims, and customer experience.

Our assessment: Flagship, productized framework with named phases, case studies, and measurable outcomes; well-described and clearly central to Praxent's current positioning.

AI-accelerated legacy modernization service that extracts and preserves financial logic trapped in legacy platforms, rebuilding on modern architecture with full traceability. Claims modernization measured in months.

Our assessment: Named, branded accelerator with a concrete case study (700+ financial requirements extracted from payments codebase); substantive and well-evidenced.

Designs and deploys production-ready agentic features inside governed frameworks built for regulated financial environments, including intelligent document processing agents.

Our assessment: Named and branded with a specific case study (enterprise payroll onboarding automation); clearly positioned as a production AI deployment methodology.

Continuous AI innovation delivered via dedicated product pods that relentlessly improve client KPIs by continuously deploying leading-edge AI improvements.

Our assessment: Named and branded with a compelling case study (83% reduction in time-to-fund for SMB lender); clearly articulated as an ongoing innovation model.

A technology operating model designed to enhance engineering team performance, increase on-time delivery, and reduce rework, encompassing agile transformation and accountability practices.

Our assessment: Branded operating model with defined principles (CAN/DO values) and tracked metrics, but lighter on external proof than the Decode/Activate/Compound assets.

A deliverable that maps business logic density, undocumented rules, compliance-critical workflows, integration dependencies, and modernization priorities inside a client's current system; described as the first step toward AI Command.

Our assessment: Positioned as a structured discovery offering but described at a high level with no detailed methodology exposed publicly.