Software development at AI-driven speed.
AI agent teams led by senior AI engineers build the software: enterprise-grade, faster and more cost-effectively.
The rules of software development have changed.
Where a complex system used to need a team of ten to twenty people, an agent team directed by a senior AI engineer now does the work. The same engineering discipline, with a fraction of the coordination overhead.
Large companies are still working out how to bring AI into their development process. Here, AI is already part of the entire development process, which is why projects are delivered faster and more cost-effectively, with flawless quality.
Same system. Different team.
A complex project used to start with months of hiring and coordination between many people. In the AI-driven model, a senior AI engineer and an agent team are at work from day one.
Traditional model
A team of 10-20
- Project manager
- Business analyst
- Tech lead
- Backend developers
- Frontend developers
- Mobile developer
- QA engineers
- DevOps engineer
- UI/UX designer
Dehotech model
Senior AI engineer + 10-20 agents
- Architecture
- Backend
- Frontend
- Mobile
- Data model
- Integrations
- Testing
- Code review
- Security
- Documentation
- DevOps
- Refactoring
Senior AI engineer
- Ramp-up
- Traditional model: Hiring and onboarding, for weeks or months.
- Dehotech model: Capacity is available from day one.
- Coordination
- Traditional model: Many people, many meetings, slow decisions.
- Dehotech model: One accountable senior AI engineer per agent team, a short decision path.
- Cost
- Traditional model: Driven by headcount, running until the project ends.
- Dehotech model: Driven by the work, with no fixed headcount cost.
- Quality
- Traditional model: Depends on individual experience.
- Dehotech model: Engineering review and automated quality gates on every change.
End-to-end product development, from idea to launch.
From a website to an enterprise platform: design, development, quality assurance and handover, by engineers who direct agent teams.
Vue / Nuxt / React / Next.js / TypeScript
Websites and web applications
Fast, search-friendly, custom-designed interfaces, from a company website to a complex web application.
Flutter / React Native / Firebase
Mobile apps
iOS and Android apps from a single codebase, for the app stores or for internal company use.
Laravel / Node.js / PostgreSQL / MongoDB / Docker
Custom enterprise systems
Internal management systems, client portals and automated workflows, integrated with existing tools.
LLM / RAG / Agents / API
AI and agent integration
Language models and agents inside existing workflows: customer support, document processing, internal knowledge bases.
Headless / Payment gateways / Invoicing / Inventory
Online stores
Conversion-focused e-commerce with payment, invoicing and logistics integrations.
Figma / Design system / Prototype
UI/UX and brand identity
User experience, interface design and brand identity that scale with the product.
From small to large. Held to the same standard.
The method scales: the same engineering standard for a landing page and for an enterprise platform.
Launch
Landing page, MVP, prototype
Product
Web app, mobile app, online store
Enterprise system
Internal system, client portal, integrations
Platform
Multi-module, high-load platform
A transparent process, from idea to live system.
Every phase has a clear owner and a measurable outcome. Decisions always rest with the engineer; agents carry out most of the execution.
Discovery
Clarifying goals, users, risks and business metrics.
Outcome
Clear goals and scope.
Specification
System design, architecture and feature list with measurable acceptance criteria.
Outcome
Approved specification and schedule.
Build
Agents working in parallel deliver the features, directed by the senior AI engineer.
Outcome
Working, tested features.
Quality assurance
Engineering review, automated tests and security checks on every change.
Outcome
A verified, releasable version.
Handover
Deployment, documentation and full handover. Further development is optional.
Outcome
Live system, source code and documentation.
Feature by feature. No lock-in.
No annual contract and no dependency. Every feature or module is a standalone engagement, and the source code belongs to the client.
Modular engagements
Scoped, priced and delivered per feature or module.
No lock-in
Instead of a one or two-year contract, the collaboration lasts as long as it creates value.
The code belongs to the client
Full source code, documentation and access. Any team can take it further.
Optional maintenance
Operations and further development on request, never a requirement.
A new project, or one that has stalled?
After a short call, a concrete proposal follows: scope, timeline and budget.
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