Datadog veterans launch AI coding startup Niteshift on a bet against Big AI lock-in
AI coding agent startup Niteshift has raised a $7 million seed round from a who's who of angels. It's betting companies will want power over, not lock-in with model makers.
AI coding agent startup Niteshift has raised a $7 million seed round led by Greylock’s Jerry Chen. That’s a modest sum by AI standards, but the startup, founded by two former early Datadog engineers, has attracted some big-name angels like Reid Hoffman, Datadog’s Olivier Pomel and Alexis Lê-Quôc, Ankur Goyal of Braintrust, and Misha Laskin of Reflection AI.
Founded by Sajid Mehmood and Conor Branagan, who helped grow Datadog from its early days to a multi-billion valuation, the company has entered the crowded AI coding space with a compelling idea: Why would any company trust its most sensitive assets — code that runs its products — directly to model makers like OpenAI and Anthropic, given that those companies are constantly “killing” startups and businesses by launching competing apps?
Mehmood, who is CEO, likens it to Datadog’s early growth, when the monitoring company won e-commerce customers who refused to build on Amazon Web Services. It was a reasonable concern, given that Amazon was simultaneously putting many of those same retail stores out of business in what became known as the “ retail apocalypse .”
The AI equivalent, as Mehmood sees it, is already underway. Anthropic, OpenAI, and others are moving fast into vertical software markets — what some are calling the SaaSpocalypse .
“At Datadog we saw this clearly,” Mehmood said. “A big part of our multicloud business came from e-commerce businesses who did not want to run on Amazon, right? … We are absolutely going to see the same dynamic as Anthropic goes to compete in legal and healthcare and finance and whatever else.”
The bet is that companies will increasingly seek infrastructure that separates the coding model from all the other orchestration needed to ensure AI-generated code is properly vetted and maintained (and that they’ll want a vendor without a competing agenda).
To be clear, Niteshift isn’t replacing Claude Code or Codex, the two most popular coding agents. It argues that it reduces dependence on them.
Niteshift’s AI coding cloud will route between those models — along with open source options and others — based on the needs of each project.
“Being able to switch between GPT and Claude models is important,” Mehmood said, “Everybody’s worried about getting stepped on by these giants.”
That idea is what got Greylock’s Chen to bite.
“As the frontier labs move up the stack, there’s an opportunity to offer customers an alternate path: unbundling their agents from the infrastructure they run on,” Chen told TechCrunch. “Niteshift is building the platform that enables this for coding agents, letting customers invest deeply in their developer tooling without locking themselves into a single model or agent vendor.”
More than that, Niteshift isn’t selling tokens. It sells infrastructure, charging like a cloud provider, with per-minute usage rates.
“Everybody else is selling labor replacement intelligence,” Mehmood said. “We’re selling software to agents, as opposed to humans — but we’re still out here selling software.”
Even so, Niteshift is entering a crowded market of AI coding tools. Model independence isn’t a novel idea, and Niteshift’s competitors have a massive head start. That includes Cursor, though it could soon be gobbled up by SpaceX ; Cognition, which just raised $1 billion at a $26 billion valuation ; Amazon Bedrock; and AI gateway platform OpenRouter, which just raised $113 million at a $1.3 billion valuation . The list goes on.
Mehmood’s answer to all of that is the founding team’s depth. Mehmood and Branagan didn’t just study these problems — they lived them, scaling Datadog through the exact growing pains that large engineering organizations now face with AI-generated code. Teams, he said, need to run, test, and verify software autonomously in their real production environments, and they need infrastructure built by people who’ve done it at scale.
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Pontos-chave
- A Niteshift propõe uma alternativa ao lock-in das grandes empresas de IA, oferecendo maior controle às empresas sobre suas soluções de codificação.
- A flexibilidade de alternar entre diferentes modelos de IA pode ser um diferencial importante para empresas brasileiras em busca de inovação.
- O movimento da Niteshift pode impulsionar uma demanda crescente por soluções de IA personalizadas e seguras no Brasil.
Análise editorial
A fundação da Niteshift por ex-engenheiros da Datadog destaca uma tendência crescente no setor de tecnologia: a busca por maior controle e autonomia em relação às ferramentas de IA. No Brasil, onde o ecossistema de startups está em plena expansão, essa abordagem pode ressoar com empresas que temem a dependência de gigantes da tecnologia, como OpenAI e Anthropic. A ideia de que as empresas devem ter a capacidade de gerenciar suas próprias soluções de IA, sem o risco de serem 'substituídas' por produtos concorrentes, é particularmente relevante em um mercado onde a inovação é rápida e a competição é feroz.
Além disso, a Niteshift entra em um espaço saturado, mas com uma proposta diferenciada que pode atrair empresas que buscam não apenas eficiência, mas também segurança em suas operações. A possibilidade de alternar entre diferentes modelos de IA, como GPT e Claude, pode oferecer uma flexibilidade que muitas empresas brasileiras ainda não exploraram completamente. Isso pode ser um diferencial importante para startups e empresas que estão desenvolvendo soluções específicas para o mercado local.
O movimento da Niteshift também pode influenciar a forma como as empresas brasileiras abordam a adoção de IA em suas operações. À medida que mais startups e empresas estabelecidas reconhecem a importância de evitar o lock-in com fornecedores de IA, podemos esperar um aumento na demanda por soluções que ofereçam maior controle e personalização. Isso pode levar a um ecossistema mais diversificado e inovador, onde as empresas se sintam mais capacitadas a experimentar e implementar tecnologias de IA de forma independente.
Por fim, é importante observar como a Niteshift se posicionará em um mercado que já conta com soluções consolidadas. A capacidade de se diferenciar e oferecer valor real será crucial para o seu sucesso. O que se segue será a forma como a startup conseguirá escalar sua operação e conquistar a confiança de empresas que buscam alternativas viáveis e seguras para suas necessidades de codificação com IA.
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Fonte original:
TechCrunch AISobre este artigo
Este artigo foi curado e publicado pelo AIDaily como parte da nossa cobertura editorial sobre desenvolvimentos em inteligência artificial. O conteúdo é baseado na fonte original citada abaixo, enriquecido com contexto e análise editorial. Ferramentas automatizadas podem auxiliar tradução e estruturação inicial, mas a decisão de publicar, a revisão factual e o enquadramento de contexto seguem responsabilidade editorial.
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