DitchNow is an active participant in the application and orchestration layers of the AI agent stack. They specifically focus on the delivery of agentic features like RAG-based knowledge copilots and automated data pipelines. For founders and companies that have the vision for an AI agent but lack the internal engineering capacity to wire together models, vector databases, and ingestion flows, DitchNow is the implementation partner that converts those concepts into shipped software.
In the broader ecosystem, DitchNow is a champion of the 'product-first' approach to agents. They prioritize building agentic systems with strict evals and guardrails, which is a critical step for moving from brittle AI demos to reliable enterprise tools. Their relevance lies in their ability to bridge the gap between high-level LLM capabilities and specific, sellable agent use cases, making them a key player for startups attempting to build the next generation of AI-driven SaaS.
DitchNow is a technical execution partner designed for the specific constraints of the current AI boom. Founded by Metin, a builder with 15 years of experience and five previous startups, the company is based in Haarlem, Netherlands. It targets a perennial problem in the startup world: the non-technical founder who has a market wedge but cannot find a technical co-founder to build the initial product. In the era of LLMs, this gap has become more acute as the speed of the market outpaces the speed of traditional hiring. DitchNow is an attempt to institutionalize the 'technical co-founder' role as a service, allowing founders to trade capital for immediate shipping velocity.
The service is structured to avoid the 'prototype trap' where products cycle through endless proofs-of-concept without ever reaching production. DitchNow operates through three distinct tiers: the Prototype, the MVP Build, and Launch + Iterate. Each tier has a defined investment range and timeline. A Prototype is a 7-to-10 day sprint aimed at technical feasibility and fundraising demos, while the MVP Build is a 4-to-6 week process that delivers a usable v1. By using flat-fee pricing—ranging from €2k for basic sprints to €35k for full MVPs—the company aligns itself with the founder’s goal of launching quickly, rather than an agency's goal of billable hours.
DitchNow focuses heavily on the implementation of Retrieval-Augmented Generation (RAG) and knowledge copilots. They build the underlying plumbing required for AI products to be reliable, including data ingestion pipelines, chunking strategies, and retrieval tuning. This isn't just about wrapping an API; it involves building the 'eval harness' and guardrails necessary for a product to survive contact with real users. Their 'Data + Model Pipeline' service is specifically for startups that need to turn raw datasets into functional product features, handling the ETL, storage, and monitoring that usually requires a senior infrastructure hire.
The philosophical foundation of DitchNow is the belief that AI will enable the rise of 'one-man unicorns'—highly profitable businesses with minimal headcount. To support this, they offer a 'Fractional Builder-Owner' role, providing ongoing infrastructure and ops oversight without the founder having to hire a full engineering team. This model is particularly attractive to solo founders and scaleups that need to ship specific AI features without taking on significant reliability debt. DitchNow acts as the technical anchor, managing the backlog and scope control while the founder focuses on distribution and customer acquisition. They provide the handoff kits and documentation required for a startup to eventually transition to an in-house team once they have reached sufficient scale.
A clickable, testable AI product prototype delivered in days.
End-to-end production of a usable AI-powered v1 product.
DitchNow is hiring.