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TypeScript Development Services

Types shared across frontend and backend so contract mismatches show up at build time, well before production.

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How we work

TypeScript adds a static type layer on top of JavaScript, checked at build time and erased before the code runs. It changes almost nothing about how JavaScript executes and almost everything about how confidently a team can change code without breaking something they cannot see. The compiler catches a whole class of errors before shipping (wrong shape of data, a renamed field, a missing null check).

We write nearly everything in TypeScript by default, across React, Vue, Node.js and React Native projects, because the cost of adding types is small and the cost of not having them shows up later as production bugs that a type checker would have caught in seconds. On projects with both a frontend and a backend under our control, we go further and share type definitions for API request and response shapes between the two, so a backend change that breaks the contract fails the frontend build immediately instead of failing silently at runtime.

Fit

When TypeScript is the right choice, and when it is not

Good fit

  • The codebase will be maintained by more than one developer, or by the same developer six months from now who will not remember every implicit assumption
  • You have an API boundary between a frontend and backend, or between services, where a shared type definition catches contract drift before it reaches production
  • The application has non-trivial data shapes (nested objects, discriminated unions, optional fields) where a typo in a property name is easy to make and hard to spot in plain JavaScript
  • You are building something intended to last years rather than a one-off script, since types pay for themselves most during refactors and onboarding
  • The team already has some TypeScript experience and the incremental cost of setup is small relative to the codebase's expected lifespan

Consider something else

  • You are writing a short, disposable script or a one-time data migration where the code will be deleted within days and the type annotations would take longer to write than the script itself
  • The team has zero TypeScript experience and the project has a hard, immovable deadline that does not allow for the initial learning curve on generics and utility types
  • You are prototyping an idea where the data shapes are still changing daily; strict typing on a design that is not settled yet can slow exploration more than it helps
  • You have inherited a large, untyped JavaScript codebase and the immediate priority is shipping a specific feature and a migration would delay it; converting piecemeal without a plan often creates half-typed code that is harder to reason about than either fully typed or fully untyped code

What we build

What we build with TypeScript

  • Shared types between frontend and backend

    API request and response types defined once and imported on both sides of the boundary, so a backend field rename or removal fails the frontend's build instead of failing quietly in the browser.

  • Strict compiler configuration

    Strict mode enabled from day one on new projects (no implicit any, strict null checks), which catches far more real bugs than a loosely configured TypeScript setup that only checks syntax.

  • Type-safe API and database layers

    Zod or similar runtime validators paired with static types so the shapes checked at compile time are also enforced at runtime, at the boundary where external data enters the system.

  • Large-scale refactor safety

    Renaming a field, changing a function signature or restructuring a module, with the compiler listing every call site that needs to update instead of relying on manual search and testing.

  • Monorepo type sharing

    Shared type packages consumed across multiple applications in a monorepo (web app, admin panel, mobile app) so a domain model changes in one place.

Ecosystem

Libraries and tools we pair it with

  • Zod for runtime validation that mirrors static types
  • tRPC for end-to-end typed APIs without a separate schema language
  • Prisma or Drizzle for typed database queries generated from the schema
  • TypeScript ESLint for enforcing type-aware lint rules
  • Turborepo or Nx for managing shared types across a monorepo
  • ts-reset or type-fest for filling gaps in the standard library's types

Migrating an existing JavaScript codebase

A full-codebase rewrite to TypeScript is rarely the right move; TypeScript supports incremental adoption because it can type-check a mix of .ts and .js files in the same project. We typically start by enabling `allowJs` and `checkJs`, adding types to the modules with the most bugs or the most churn first, and letting the rest of the codebase convert opportunistically as files are touched for other reasons.

The modules worth converting first are usually the ones defining shared data shapes: API clients, core domain models, utility functions used everywhere. Converting those early gives the rest of the migration a typed foundation to build on, rather than typing UI components first and hitting untyped data flowing in from everywhere.

Where strict typing helps less than expected

Type safety at compile time does not replace runtime validation at the edges of a system. Data from an external API, user input, or a third-party webhook has a shape the compiler cannot verify, because the compiler only checks the code you wrote, not the data arriving from outside it. A common failure mode is a team trusting a TypeScript interface for a shape that was never actually validated at runtime, and getting a production crash when the external service sends something slightly different than expected.

We pair static types with Zod schemas at every external boundary specifically to close that gap: the schema validates the data is what it claims to be, and infers the TypeScript type from the same definition, so there is one source of truth instead of two that can drift apart.

  • Static types cover code you control; runtime validation covers data you do not
  • Zod schemas at API boundaries generate the TypeScript type, removing duplication
  • A typed interface with no runtime check is a promise the compiler cannot enforce

FAQ

Questions about TypeScript

Does adding TypeScript slow down initial development?

Slightly, in the first few weeks while a team gets used to writing type annotations and reading compiler errors. Past that point it usually speeds development up, because the compiler catches mistakes immediately instead of a developer discovering them later through manual testing or a bug report.

Can we migrate an existing JavaScript codebase incrementally?

Yes, TypeScript is designed for incremental adoption and can type-check a mix of JavaScript and TypeScript files in the same project. We usually convert shared data models and API clients first, then let the rest convert as files are touched for other feature work rather than as a dedicated rewrite.

Is TypeScript only useful for large teams?

It helps most visibly on larger teams and longer-lived codebases, but a solo developer benefits too, mainly during refactors and when returning to code written months earlier. The main case where it adds little value is a short-lived script that will be deleted within days.

How do you keep frontend and backend types in sync?

On projects where we control both sides, we define request and response types once in a shared package and import them on both the API and the client, so a contract change that breaks the other side fails the build immediately. Where the backend is external, we generate types from its OpenAPI schema instead.

Does TypeScript catch bugs from bad data, not just bad code?

Not on its own. Static types check the code you wrote against itself; they cannot verify that data arriving from an external API or user input actually matches the shape you declared. We pair TypeScript with runtime validation (Zod) at every external boundary specifically to cover that gap.

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