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§ Private Profile · London, GB
Developer of an AI platform that automates control software engineering for physical systems using machine learning models.
Hyperpilot has raised $2.7M across 1 funding round.
Key people at Hyperpilot.
Hyperpilot has raised $2.7M in total across 1 funding round.
Hyperpilot develops an AI platform for automating control software engineering in physical systems using proprietary machine learning models. This platform is designed to streamline the complex process of control software development, aiming to significantly scale engineering efforts and reduce the incidence of human error across various applications. By automatically designing control software across diverse industrial and technological domains, Hyperpilot enables engineers to allocate their focus towards higher-level innovation and strategic challenges. Additionally, the organization provides HyperPilot, a free, accessible playground for developers to test and compare various AI browser agents, leveraging its foundational Hyperbrowser infrastructure. This initiative serves to foster the development of agent-based applications and promote the adoption of their core API. The organization was founded by Tim Chen.
Hyperpilot has raised $2.7M in total across 1 funding round.
Hyperpilot's investors include Join Capital, Octopus Ventures, Plug and Play, Tiny VC.
Hyperpilot has raised $2.7M across 1 funding round. Most recently, it raised $2.7M Hypercritical - Pre-Seed in December 2025.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Dec 4, 2025 | $2.7M Pre Seed | Join Capital | Octopus Ventures, Plug And Play, Tiny VC | Announced |
Key people at Hyperpilot.
Hyperpilot is the flagship product of Hypercritical, a London-based deeptech startup developing AI models to generate verifiable control software for safety- and mission-critical systems in sectors like automotive, aerospace, defence, and robotics.[1][3] It automates the creation of control algorithms by having engineers specify tests and safety constraints, after which the AI produces mathematically precise, error-free code that passes 100% of tests—delivering faster, cost-efficient development for physical systems where failures are catastrophic.[1][3] Hyperpilot is already deployed with engineering teams, alongside domain-specific "copilots" for QA and systems engineering, serving heavy industry clients needing reliable automation; the company recently raised £2M in pre-seed funding to scale its team and model training.[1]
Hypercritical solves the pain of lengthy engineering cycles, formal verification, and expensive testing in control software development, enabling unsupervised "Autopilot" generation and "Copilot" tools for immediate, domain-tailored output.[1][3] This positions it for growth in regulated industries demanding certification, with early customer deployments proving real-world viability amid rising investor interest in industrial AI.[1][3]
Hypercritical is a recently founded London-based AI startup, emerging amid renewed investor focus on logic-driven AI for industrial verification challenges; specific founding year and founders are not detailed in available sources, but it has quickly gained traction with £2M pre-seed funding led by Join Capital, joined by Octopus Ventures, tiny.vc, and Plug and Play.[1][3] The idea stems from reframing control software workflows: instead of probabilistic code generation prone to hallucinations, its novel logic-driven architecture uses specialized agents to design, verify, and optimize within strict safety bounds, addressing gaps in sectors like aerospace and defence.[1][3] Pivotal early momentum includes deploying Hyperpilot and copilots with customers, validating its approach in safety-critical environments, followed by the December 2025 funding to double the engineering team and fund cloud compute for proprietary model advancement.[1]
(Note: Separate "HyperPilot" products exist from other firms—DeepSea Technologies' maritime speed controller and TSAW's drone fleet board—but context points to Hypercritical's software as the primary match for "Hyperpilot" in AI/deeptech startup discussions.[2][4][6])
Hypercritical and Hyperpilot stand out in AI-driven software engineering through:
These enable 100% test passage in high-stakes environments, positioning it ahead of generic AI tools.[1]
Hypercritical rides the vertical AI wave, applying domain-specific models to under-digitized, regulated sectors like heavy industry—where proprietary data, compliance, and precision create moats against horizontal LLMs.[1][3][5] Timing aligns with investor surge in industrial AI for correctness/explainability, as seen in its £2M raise amid M&A interest in workflow-embedded tools.[1][3][5] Market forces favoring it include escalating demands for efficient control systems in EVs, drones, and autonomy, plus regulatory pushes for verifiable software amid talent shortages in verification.[1][3] It influences the ecosystem by pioneering automated certification pathways, potentially modernizing global standards and enabling leaner engineering teams in safety-focused industries.[1][3]
Hypercritical plans to double its team and intensify model training post-funding, targeting broader adoption in defence/robotics while proving certification scalability.[1] Trends like vertical AI agents and regulatory acceptance of AI-generated code will propel it, especially as industries chase 2-3x throughput gains without headcount bloat.[3][5] Its influence could evolve into ISO-standard shaper, redefining control software as a commodity—cementing Hyperpilot as the benchmark for mission-critical reliability, much like its funding validates amid industrial AI momentum.[1][3]
