Let AI agents do the routine work, you decide.

• HOROZ

  In internal use

  An office for AI coding agents such as Claude Code, Codex and Gemini CLI that runs them as a team in one desktop app.

  An Electron app that gives each agent its own memory and mailbox while a lead agent hands out the work. The team is shown working in a 3D office.

• ArkaYüz

  Site live

  An independent scanner for food products in Turkey: scan a barcode to see a score from 0 to 100, three reasons and a better alternative. It takes no ads or brand money.

  A data pipeline that matches open food data with manufacturer pages, scoring that cites its sources, the arkayuz.net site and its waitlist. The mobile app is a prototype.

  arkayuz.net

• ArchMind

  In development

  An iPhone app for interiors and gardens: photograph a space, pick a style, and AI redraws it in that style and suggests products with prices.

  A SwiftUI iPhone app and a backend that queues the image renders and matches products with vector search.

1. 1

   Discovery

   We listen to your goals, data and constraints and define the problem worth solving.

2. 2

   Prototype

   We test the approach early on real data with a small, working prototype.

3. 3

   Build

   We develop in short cycles and show a working version at the end of each one.

4. 4

   Launch and support

   We deploy and monitor the system and keep improving it as your needs change.

Where should your project start?

Which service fits my needs?

Start with consulting if you are still deciding what to automate. A custom assistant can be a starting point when a team repeatedly searches the same documents; process automation can help when work involves moving data between tools. Explore LLM integration if you want to add an AI feature to an existing product.

What should I prepare for the first conversation?

Describe how you do the work today, which tools you use and where you lose time. An example task, the expected output and how you would measure success help define the scope. You do not need to send passwords, customer records or confidential documents in your first message.

What can a prototype tell us?

For a solution that extracts fields from incoming documents, successful examples tell only part of the story. Documents with missing information, incorrect outputs and steps that require a person to check them also need evaluation. A prototype helps make these limits visible before a larger development effort.

• November 1, 2026

  Common process automation mistakes and how to fix them

  Common mistakes in process automation projects: how to avoid unmapped processes, missing data, misused AI and a lack of measurement.

• November 1, 2026

  AI software development methodologies: a guide

  Compare AI software development methodologies and learn which approach fits your project, how to start a pilot project and how to choose a consultant.

• October 19, 2026

  Are AI agents compliant with KVKK? The 2026 guide

  Are AI agents compliant with KVKK? We walk through the data controller role, explicit consent, cross-border transfer and hallucination risk step by step.