VVyshyvka
studio

Complex software without handoffs

Serious systems, built end to end.

Vyshyvka designs and builds complex platforms, AI workflows, archives, dashboards, and internal tools without the usual handoffs between strategy, design, engineering, data, and infrastructure.

Hand-drawn flow from source material and data into product screens.

Domain material

Files, records, media, source documents, databases, staff input.

System logic

Schemas, workflows, AI steps, validation, review state.

Working product

Websites, dashboards, internal tools, publishing screens.

Where projects break

Software projects fail between teams.

AI, data, interfaces, permissions, infrastructure, and operations have to match. Vyshyvka keeps those decisions in one build process.

  1. 01

    Domain material

    Files, records, media, source documents, databases, staff input.

  2. 02

    Product system

    Data models, workflows, AI pipelines, validation, review state.

  3. 03

    Working product

    Websites, dashboards, internal tools, publishing screens.

Team-scale work

This is the team the work usually takes.

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

Senior judgment in one chain

The product model, interface, data layer, AI workflow, and infrastructure are designed together.

AI inside the workflow

Automation is tied to sources, validation, permissions, review state, telemetry, and repair paths.

Delivery without integration drift

Fewer vendor relays, fewer handoff gaps, and fewer late discoveries that the parts do not fit.

Systems we build

01

Institutional platforms

Websites connected to records, events, media, permissions, files, and staff workflows.

  • Public site
  • Staff tools
  • Data model
02

Archive and knowledge systems

Structured collections with provenance, search, review state, and publication tools.

  • Catalog
  • Review
  • Publishing
03

AI workflow systems

Pipelines where extraction, validation, human review, telemetry, and writeback are built into the product.

  • Sources
  • Validation
  • Review gates
04

Operational dashboards

Internal tools for teams working with messy data, status changes, filters, files, and approvals.

  • Workflow
  • State
  • Permissions

Technology

The stack behind the work.

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.

Next.js

Application framework for routed pages, server-rendered screens, and public site delivery.

React

Interface layer for reusable product screens, interactive workflows, dashboards, and internal tools.

TypeScript

Keeps data contracts, component props, workflow state, and integration boundaries explicit across the stack.

Tailwind CSS

Used for responsive layout, component styling, and fast interface iteration.

Drizzle ORM

Typed database modeling for records, relationships, migrations, and domain-specific operational data.

NextAuth

Authentication layer for protected routes, sessions, staff tools, and authenticated product workflows.

Cloudflare Workers

Edge runtime for application pages, API routes, file handling, and deployment workflows.

Cloudflare D1

Cloudflare-native relational storage for Workers-deployed apps and structured product data.

Cloudflare R2

Object storage for media, generated assets, document artifacts, and file-backed workflows.

Stripe

Payment and billing infrastructure for subscriptions, checkout, and account commerce.

Python

Used for pipeline work, AI tooling, data repair, extraction, enrichment, and operational scripts.

PyTorch

Modeling and prototype ML layer for sequence analysis, evaluation, and applied AI research workflows.

NumPy

Numerical foundation for compact inference paths, model artifacts, and data-heavy Python operations.

SQLite

Local and embedded relational storage for development, prototypes, imports, and focused operational datasets.

Pydantic

Python-side validation for AI, extraction, and service workflows where structured inputs and outputs matter.

Zod

Runtime validation for form inputs, server actions, API payloads, and typed workflow boundaries.

OpenNext

Bridges Next.js apps into Cloudflare deployment targets while preserving the App Router model.

Vitest

Test runner for focused unit and integration coverage around parsing, data transforms, and product logic.

If the work crosses design, data, AI, and infrastructure, bring it early.

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