n o t
o n l y
t e c h n o l o g y
New Software Products

Built AI-Native
From Day One


End-to-end development for new software products, with AI built into every stage, from idea to launch.

About

We take greenfield projects from concept to production in weeks

  • Greenfield moves faster – the architecture, stack, and AI layer – all designed for current needs, with nothing inherited slowing you down.

  • Interactions, data, architecture, build, and ongoing evolution, delivered inside a governed framework with agentic power at every stage.

When to Consider?
  • You have a new product to build, leveraging all the speed and quality AI now enables.
  • When speed to market matters, and the first version needs to hold up as the product scales.
  • You're entering a new market or business line and want the technical foundation built clean.
  • When your product needs to keep evolving with user behavior, with a team built for continuity.
Greenfield projects

A greenfield project is a new software product built from scratch while respecting organizational-wide architectural standards and available data sources. We build AI-native at every step, from discovery and design to development and deployment. You get software that is more adaptive, resilient, and aligned with your long-term business needs.

Greenfield MVP delivered in weeks with the Notch 3S Method™

The Notch 3S Method™ is how we structure every greenfield MVP engagement. Three phases, one continuous team.

1–3 weeks

SCOPE

Your decision-makers and our team, working together. Sovera AI™, our agent-orchestration platform, runs the domain research, surfaces edge cases, and flags assumptions. You leave with a prototype and a plan.

4–12 weeks

SHIP

The plan becomes working software in front of real users. NotchForge™ - Notch's delivery framework - governs how agents operate and where humans sign off. Short cycles, progress is visible every week.

Ongoing

STRENGTHEN

Two parallel tracks: Harden (performance, security, observability) and Evolve (next user journeys informed by real user behavior). Monthly checkpoints. The same team stays on.

Notch 3S Method™ Principles

  • 1
    Excellent
    Excellent work, measured honestly: We build working software, not demos dressed up as MVPs.
  • 2
    Courageous
    Courageous scope: Say no early, so the first version proves the idea.
  • 3
    Trustworthy
    Trustworthy timelines: Issues flagged in week one, not week eleven.
  • 4
    Human
    Human judgment with agent support: Agents accelerate, but a human stays in the loop on every decision.
Excellent work, measured honestly: We build working software, not demos dressed up as MVPs.
Courageous scope: Say no early, so the first version proves the idea.
Trustworthy timelines: Issues flagged in week one, not week eleven.
Human judgment with agent support: Agents accelerate, but a human stays in the loop on every decision.

Launch your MVP with real users in twelve weeks.

Book a scoping call

Your benefits

  • 1
    Fast to market
    From brief to working product in 12 weeks. The Notch 3S Method™ makes that the default.
  • 2
    Built to last
    Clean architecture and documented decisions from day one. A codebase built to extend.
  • 3
    One team, full lifecycle
    The engineers who scope it - build it. Continuity is structured into every engagement.
From brief to working product in 12 weeks. The Notch 3S Method™ makes that the default.
Clean architecture and documented decisions from day one. A codebase built to extend.
The engineers who scope it - build it. Continuity is structured into every engagement.

Process

Discovery Specification-driven development Architecture & harness design Development QA & evaluation Deployment Strengthen
01
Discovery

Defining the business goals, user needs, and data flows before making any architectural or build decisions.

02
Specification-driven development

Every feature is defined, reviewed, and approved before implementation begins. Coding agents work from confirmed specs at every stage.

03
Architecture & harness design

System architecture, data model, and harness design - clean foundations support years of product growth, upgrades, and pivots.

04
Development

Iterative build cycles with coding agents integrated into delivery. Short cycles, progress is visible every week.

05
QA & evaluation

Continuous testing throughout the build, including behavioral validation for agentic components - integrated at every stage.

06
Deployment

Production deployment with full documentation and a codebase your team can open, understand, and extend from day one.

07
Strengthen

Ongoing hardening for scale and evolution, driven by real user behavior, with structured checkpoints and clear next steps.

How we build
New software product development runs on the AI-native software development lifecycle (SDLC)
Spec-driven development, coding agent-enhanced delivery, and continuous evaluation at every stage. The 3S Method is how that methodology is applied to greenfield MVP products.
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Who's involved?

How they contribute
Smooth operator

Ensures the project stays within the agreed budget, scope, and timeline, with consistent status reports and smooth stakeholder communication.

Anadea
How they contribute
Value acceleration

Defines requirements, creates clear specifications for everyone, and guarantees the software delivers the expected value.

Vinko Borcic
How they contribute
User-centered products

Creates interactive prototypes that help you envision and verify your product based on insights from user research, user flows, personas, and storyboards.

Mia Vučemilović
How they contribute
From design to reality

Transforming design into a live solution with HTML, CSS, and JavaScript, partnering with backend teams to deliver full functionality and engaging interactivity.

Ivan Rastegorac
How they contribute
Seamless performance

Making databases and applications work seamlessly by building, maintaining, and securing server-side systems, developing APIs, optimizing performance, and integrating with the front end.

Relja Medic
How they contribute
Scalable solutions

Software structure design, technology recommendation, definition of technical standards and frameworks, and sharing of best practices.

Mario Mijić
How they contribute
Quality assurance

Leading the overall quality assurance process, defining test strategies, and coordinating manual and automated testing activities, ensuring compliance with quality standards.

Emanuel Ružić
How they contribute
Predictive modeling

Analyzing data to extract insights and build predictive models of your solution, supporting data-driven and informed decision-making and optimizing performance.

Ivan Vrtarić
How they contribute
Optimizing AI models

Unlocking software improvements and process automation by leveraging data processing and machine learning to optimize AI models and enhance software functionality.

Matea Antolić

Technologies, tools & frameworks we use

Java Scala Go Kotlin .NET Node.js Python JavaScript TypeScript React Angular Vue
SpringBoot Spring Framework Akka Hibernate ASP.NET Express.js React Redux NgRX Less React Router Vuex MochJS/Jest/Jasmine Pydantic AI DSPy Claude Agent SDK Sovera AI
Kafka SQL NoSQL Databases Kubernetes Git/GitHostingplatforms Relational databases Messaging systems Docker Vite/Yarn/Gulp/Grunt ESLint/TSint Cypress npm Webpack Selenium Logfire LangFuse Tessl OpenAI Agent Builder Claude Code Open Code
Agile/Scrum/Kanban NotchForge™ Notch 3S method
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Your AI tools are live. Your operating model never changed.

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FAQ
Themes
New Software Products
What is a greenfield project, and how is it different from rebuilding an existing software product?

A greenfield project is a new software product built from scratch – while respecting organizational-wide architectural standards and available data sources. Unlike a rebuild or modernization, you’re not working around existing systems. The architecture, stack, and AI layer are all designed for current needs from day one. You get software that is more adaptive, resilient, and aligned with your long-term business needs.

How long does it take to go from idea to a working software product?

The Notch 3S Method is structured to deliver a working MVP in roughly twelve weeks. The first three weeks (Scope) cover working sessions, prototyping, and a signed-off build plan. Weeks four through twelve (Ship) turn that plan into working software in front of real users. Timelines flex depending on complexity, but twelve weeks is the default – not the exception.

What does “AI-native” mean in practice?

It means AI isn’t bolted on after the product is built. From discovery through deployment, we use agent orchestration (Sovera AI™) and coding agents (NotchForge™) at every stage – domain research, specification, development, testing, and evaluation. The product itself is architected to support AI-driven features and agentic components from the start, not retrofitted later.

What happens after the greenfield MVP is deployed?

The same team stays on. The Strengthen phase runs two parallel tracks: Harden (performance, security, observability) and Evolve (next user journeys informed by real behavior). Monthly checkpoints keep priorities aligned. The goal is a product that keeps improving, not a handoff and a goodbye.

How do you make sure the software product is built to scale, not just to demo?

Clean architecture and documented decisions from day one. Every feature goes through Specification-Driven Development (SDD) – defined, reviewed, and approved before implementation begins. The codebase is built so your team can open it, understand it, and extend it. We design for years of growth, upgrades, and pivots, not just a launch milestone.

How involved does our team need to be during the build of a new software product?

Collaboration is structured into every phase. During Scope, your decision-makers join working sessions to align on goals and sign off on the build plan. During Ship, progress is visible every week – short cycles, no black-box periods. You’re in the room, not waiting for a final reveal. The level of daily involvement is flexible, but the principle is collaboration over handover.

What tech stack do you use for new software products?

It depends on the product. We work across modern programming languages and frameworks, with AI-specific tooling including Pydantic AI, DSPy, Claude Agent SDK, and our own Sovera AI™ platform. Development tooling includes Logfire, LangFuse, Claude Code, and others. The stack is chosen to fit the product’s needs, not forced from a template.

Let’s get you from idea to working software product in 12 weeks.
Schedule a scoping call
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