Trajectory Raises $45M Series A to Automate AI Model Training for Non-Technical Users
Founded by three Stanford classmates with Google DeepMind or Apple backgrounds, the 18-person startup reached a $300M valuation after a $45M Series A led by Sequoia. Its platform continuously retrains models using feedback from businesses’ own apps, targeting fields such as law and finance.
Trajectory, a one-year-old AI startup, announced in November 2026 that it has raised $45 million in a Series A round at a $300 million valuation. The round was led by Sequoia, with participation from Nvidia, Bessemer Venture Partners, and Bain Capital Ventures.
The 18-person company was founded by three Stanford classmates — Ronak Malde, Michael Elabd, and Arjun Karanam — each with experience at Google DeepMind or Apple. Its platform allows businesses to continuously retrain AI models using feedback collected from their own applications, without requiring dedicated research teams or outside engineering consultants.
The core problem Trajectory addresses is that AI models, whether from OpenAI, Anthropic, or open source alternatives, do not learn from mistakes without additional training. Adapting these models for specialized fields like law or finance typically requires expensive internal teams or contractors. Trajectory’s platform aims to automate that process, enabling professionals such as lawyers and doctors to improve models themselves based on their organization’s standards of quality.
Co-founder Malde described foundational models as “a very smart PhD student who’s always starting a new job,” contrasting that with the value of experience built over time. Trajectory’s continual learning approach connects to a business’s existing applications, collects performance feedback, and uses it to retrain the underlying model on an ongoing basis.
Current customers include Harvey, Rogo, Decagon, Mercor, and Nvidia. Alongside the funding announcement, Trajectory is making its post-training platform publicly available.
The startup operates in a competitive space. Trajectory identifies Thinking Machines Lab — founded by former OpenAI CTO Mira Murati — Applied Compute, valued at $3.25 billion, and Prime Intellect as direct competitors.
Co-founder Elabd noted that keeping humans involved in the training loop distinguishes Trajectory’s approach from autonomous self-improvement, which he said could lead to unintended or dangerous outcomes. Co-founder Karanam added that the platform’s interface is specifically designed to make post-training accessible to non-technical users.