Pricing
Anrixa pricing is structured around the amount of architecture, implementation, content, deployment, and review a project needs. The goal is to price the real work, not sell vague packages.
Static site architecture, page copy, metadata, schema, sitemap, deployment scripts, and verification. Starting range: from USD 800 / RMB 5,800 for a focused static rebuild or SEO repair.
Best for: company sites, product pages, regional SEO, public trust rebuilding.
Document flow, AI output schemas, review screens, automation logic, logs, and controlled deployment. Starting range: from USD 2,500 / RMB 18,000 for a controlled first-phase AI workflow.
Best for: education content, internal reports, document-heavy operations.
Dashboard, records, user roles, workflow states, API/backend, exports, and deployment. Starting range: from USD 3,500 / RMB 25,000 for a maintainable internal tool or workflow dashboard.
Best for: operations, staff workflows, data handling, business automation.
Product architecture, app/site/backend direction, public positioning, privacy/support pages, and launch infrastructure. Starting range: from USD 2,000 / RMB 14,000 for product direction, launch structure, and compliance-ready public pages.
Best for: tools like CommandPad, app-store preparation, founder-built products.
A proper estimate needs the current state, target outcome, pages or features required, deployment environment, content volume, content scope, backend needs, and risk level. A simple static page update is very different from a multi-page product site with a backend contact system and AI workflow.
The pricing page is evaluated by how well it separates small repairs, full rebuilds, AI workflow systems, internal tools, and product engineering work before a buyer sends an inquiry.
The important pricing checkpoints are current state, number of pages or screens, backend/API needs, AI or data complexity, deployment environment, security exposure, content readiness, support expectations, and launch pressure.
Process explains how those details move through delivery, case studies show the proof model, support explains post-launch routes, and contact turns a starting range into a real estimate.
Technology pricing is most useful when it explains what changes scope. A small static website patch, a full SEO rebuild, an AI document workflow, a mobile product, and a secure internal operations system are not the same type of work. Each has different requirements for discovery, design, data structure, backend logic, testing, deployment, documentation, and support.
The public pricing page should therefore guide expectation without pretending that every project has a fixed package price. It should help the buyer prepare better information: target users, current system, data sources, required integrations, security concerns, launch deadline, content readiness, and whether the work must become a maintainable product.
