Senior judgment in one chain
The product model, interface, data layer, AI workflow, and infrastructure are designed together.
Complex software without handoffs
Vyshyvka designs and builds complex platforms, AI workflows, archives, dashboards, and internal tools without the usual handoffs between strategy, design, engineering, data, and infrastructure.

Files, records, media, source documents, databases, staff input.
Schemas, workflows, AI steps, validation, review state.
Websites, dashboards, internal tools, publishing screens.
Where projects break
AI, data, interfaces, permissions, infrastructure, and operations have to match. Vyshyvka keeps those decisions in one build process.
Files, records, media, source documents, databases, staff input.
Data models, workflows, AI pipelines, validation, review state.
Websites, dashboards, internal tools, publishing screens.
Team-scale work
Custom platforms are expensive because they ask a client to exercise senior product, design, engineering, data, AI, infrastructure, validation, and delivery judgment at once.
The offering
The product model, interface, data layer, AI workflow, and infrastructure are designed together.
Automation is tied to sources, validation, permissions, review state, telemetry, and repair paths.
Fewer vendor relays, fewer handoff gaps, and fewer late discoveries that the parts do not fit.
Systems we build
Websites connected to records, events, media, permissions, files, and staff workflows.
Structured collections with provenance, search, review state, and publication tools.
Pipelines where extraction, validation, human review, telemetry, and writeback are built into the product.
Internal tools for teams working with messy data, status changes, filters, files, and approvals.
Technology
These are the tools used across recent builds. The point is not the logo list; it is that product, data, AI, infrastructure, and deployment are handled together.
Application framework for routed pages, server-rendered screens, and public site delivery.
Interface layer for reusable product screens, interactive workflows, dashboards, and internal tools.
Keeps data contracts, component props, workflow state, and integration boundaries explicit across the stack.
Used for responsive layout, component styling, and fast interface iteration.
Typed database modeling for records, relationships, migrations, and domain-specific operational data.
Authentication layer for protected routes, sessions, staff tools, and authenticated product workflows.
Edge runtime for application pages, API routes, file handling, and deployment workflows.
Cloudflare-native relational storage for Workers-deployed apps and structured product data.
Object storage for media, generated assets, document artifacts, and file-backed workflows.
Payment and billing infrastructure for subscriptions, checkout, and account commerce.
Used for pipeline work, AI tooling, data repair, extraction, enrichment, and operational scripts.
Modeling and prototype ML layer for sequence analysis, evaluation, and applied AI research workflows.
Numerical foundation for compact inference paths, model artifacts, and data-heavy Python operations.
Local and embedded relational storage for development, prototypes, imports, and focused operational datasets.
Python-side validation for AI, extraction, and service workflows where structured inputs and outputs matter.
Runtime validation for form inputs, server actions, API payloads, and typed workflow boundaries.
Bridges Next.js apps into Cloudflare deployment targets while preserving the App Router model.
Test runner for focused unit and integration coverage around parsing, data transforms, and product logic.
Selected systems
Public sites, staff tools, data models, workflow screens, and research prototypes from recent work.
If the work crosses design, data, AI, and infrastructure, bring it early.
Send a project brief