From pixel-perfect interfaces to robust backend systems XFactr.AI engineers web and mobile applications that perform, scale, and hold up under real-world load.
AI Agent Live in Production
PO processing Time Reduction
Added Head Count as Scale
Customer Satisfaction
Agents Scaled from First Diployment
↑ 12.4%
↑ 8.1%
↑ 21%
Node.js + JWT
REST · GraphQL
FastAPI
Kafka Events
Go
gRPC Internal
Our engineering process,made plain.
Technology we use in production.
Edge Foundry capabilities
Vertical deployments
Streaming SSR · React Server Components · Edge CDN
React 19 concurrent features · optimistic updates
Strict mode · Zod runtime validation throughout
Where these capabilities apply
XFactr builds frontend with React 19 and Next.js 15 using the App Router, streaming server-side rendering, and React Server Components, paired with TypeScript, Tailwind CSS, and Radix UI. On the backend, it uses Node.js for high-concurrency workloads, FastAPI for compute-intensive Python services, and Go where raw throughput is the priority, with REST and GraphQL APIs designed contract-first.
Every API ships with OpenAPI documentation, rate limiting, and authentication built in, rather than added after launch.
Performance is built into the architecture from day one through streaming SSR, edge rendering, image optimization, and route-level code splitting, rather than optimized after launch. Delivery is automated with GitHub Actions CI/CD, Docker, Kubernetes, and Terraform infrastructure-as-code, with every pull request running the full test suite and deploying to a preview environment before anything reaches production.
Typical production targets include a Largest Contentful Paint under 2.5 seconds and Interaction to Next Paint under 200ms.
Yes — XFactr builds cross-platform mobile applications using React Native with Expo, sharing business logic, navigation, and API clients between the mobile app and the web product from a single codebase. Where frame-perfect native UI is required instead, Flutter is used, and both approaches ship to both app stores with push notifications, deep linking, and the same automated test suite used on web.
The process runs in four stages: discovery and architecture (requirements workshop, system architecture document, API contracts, written technical approach), iterative delivery in two-week sprints with working software staged at every milestone, quality and testing (unit, integration, end-to-end, accessibility, and performance checks on every pull request), and handover with documentation, onboarding, and 30-day hypercare support. Nothing is considered complete until it's running on staging, and nothing reaches production without passing the full test suite.
Every pull request runs unit and integration tests (Vitest), end-to-end tests (Playwright), a Lighthouse CI performance gate, and axe accessibility validation, alongside strict TypeScript checks with zero implicit any types. This runs continuously during development rather than as a separate QA phase at the end, so regressions are caught before they reach staging.
Handover includes complete runbook documentation, a developer onboarding session, monitoring and alert configuration, and 30 days of hypercare support, with optional ongoing maintenance available afterward. This is designed so the receiving team isn't left without documentation or support the moment the initial engagement ends.
Connect With us
Tell us what you’re building, what’s broken, or what you’ve been putting off. We’ll tell you what it takes and what it costs honestly.