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Partners & technologies

The technologies behind our systems.

Our engineers choose their tools project by project, based on your systems, your data and the team that will run the solution. Here are the ones behind the systems we have built, and the part each one plays.

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How we choose

  1. The code and the accesses are yours at the end of the project.

  2. We take no commission from the vendors we recommend.

  3. The AI model is chosen need by need, from across the market.

Web and mobile interfaces

Tools we use

  • Next.js

    The framework of our websites and web applications, from the public page to the back office.

  • React

    The library we build every interface with, from a form to a dashboard.

  • TypeScript

    The language of our custom builds, on the interface and the server alike, which surfaces part of the errors before release.

  • Vite

    The tool that bundles our business applications written in React.

  • Tailwind CSS

    The styling system that keeps our screens consistent from one page to the next.

  • Expo (React Native)

    Our mobile applications and the notifications sent to teams' phones.

Servers and data

Tools we use

  • Node.js

    The engine of our servers and APIs, written in the same language as our interfaces.

  • Express

    The base of our business APIs, which connect the interface, the database and your other tools.

  • PostgreSQL

    The database behind most of our business applications, whether it holds orders, stock, contracts or files.

  • Prisma

    The layer between our code and the database, which keeps a history of every change to its structure.

  • Redis and BullMQ

    The task queues that run document reading or reminder sending in the background, without slowing the interface.

  • Object storage (MinIO, S3-compatible)

    Storage for files and photos, served through access links that expire.

Artificial intelligence

Tools we use

  • Claude (Anthropic)

    The models and the agent development kit, the Claude Agent SDK, that our agents and copilots run on.

  • OpenAI models

    The models we pick when they suit the task better, for instance to draft answers or read documents.

  • Qdrant

    The vector database behind our document search assistants, which finds the right passage before the model answers.

  • Model Context Protocol (MCP)

    The protocol that opens a piece of software to an AI assistant, with permissions set tool by tool.

Integration and deployment

Tools we use

  • REST APIs and webhooks

    How our systems exchange data with your existing tools, in both directions.

  • Python

    The scripts and automations behind our internal tools and our data analysis.

  • Docker

    The containers our systems run in, the same way in testing and in production.

  • GitHub and GitHub Actions

    Versioned code and automated deployments, with separate environments for development and production.

  • Vercel

    Hosting for our websites, this one included.

  • n8n

    Claro's internal automations and the flows between our tools.

Let's discuss your priorities

Let's talk about your systems.

Tell us which tools you already use and what you want to build. We'll tell you how we would go about it, and with what.

  • The call lasts thirty minutes, by video.
  • You speak directly with a Claro expert.
  • Afterwards, we email you the next step we recommend.

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