Former Datadog engineers Sajid Mehmood and Conor Branagan have launched Niteshift, an AI coding startup that aims to provide companies with a model-agnostic platform for AI-generated code. The startup has secured a $7 million seed round led by Greylock’s Jerry Chen, with participation from notable investors including Reid Hoffman and Datadog’s Olivier Pomel and Alexis Lê-Quôc.
Niteshift’s platform is designed to mitigate the risks associated with relying on AI models from providers like OpenAI and Anthropic, who are expanding into various software markets. Mehmood, Niteshift’s CEO, draws parallels to Datadog’s early days, noting that many e-commerce businesses preferred not to build on Amazon Web Services due to competitive concerns. He anticipates a similar trend in the AI space, with companies seeking to avoid dependence on AI providers that may become competitors.
Unlike other AI coding tools, Niteshift doesn’t aim to replace existing models such as OpenAI’s Codex or Anthropic’s Claude Code. Instead, it offers a platform that allows users to switch between different AI models, including open-source options, based on project requirements. This flexibility is intended to reduce vendor lock-in and provide companies with greater control over their AI-generated code.
Greylock’s Jerry Chen supports this approach, stating that as AI providers move up the stack, there’s an opportunity to offer customers an alternative path by unbundling their agents from the infrastructure they run on. Niteshift is building a platform that enables this for coding agents, allowing customers to invest in their developer tooling without being locked into a single model or vendor.
In terms of business model, Niteshift charges for infrastructure usage on a per-minute basis, similar to cloud service providers, rather than selling tokens or labor replacement intelligence. This approach positions Niteshift as a provider of software to AI agents, focusing on the tools and infrastructure needed for AI-generated code rather than replacing human labor.
As the AI coding tools market becomes increasingly crowded, Niteshift’s emphasis on model independence and flexibility could appeal to companies wary of vendor lock-in. However, the startup will need to demonstrate the effectiveness and reliability of its platform to stand out among competitors.
Source: TechCrunch
