Hardware design startup CopperPilot has raised $390,000 in a pre-seed funding round led by Neon Fund, with participation from U.S.-based angel investors, as it opens version 1 of its AI design agent, codenamed Epsilon, to hardware engineers. The company also reported 25-fold growth in weekly active users since August 2026 and more than 6,000 design tasks, or artifacts, run on its platform to date.
Founded in October 2025 by Aditya NG, Mohit Bagur, and Anish Harsha, CopperPilot is developing an AI agent that automates parts of the PCB design process, from interpreting requirements and selecting components to drawing schematics, routing boards, and checking designs before manufacturing.
The company did not disclose its revenue or a user-to-paid-customer conversion rate. It said the new funding will support product research and engineering, improve the agent’s speed and reliability, and expand the engineering team.
The startup automates workflows within the EDA tools engineers already use, rather than requiring them to migrate their designs to a new environment. The platform supports KiCad, Altium, and LTspice, with its strongest integration centered on PCB design and firmware workflows.
View All Alongside its design tool integrations, CopperPilot said Epsilon can be used through AI coding agents, including Claude Code, Cursor, and Codex. This lets developers hand off board-design tasks from within those environments.
In an exclusive interview with EE Times, co-founder and CEO Aditya NG said the idea came from his experience working on hardware projects, including autonomous vehicles. “On almost every autonomous vehicle team I worked with, someone would eventually say it: A compute unit for six cameras is too hard to design, or a drive-by-wire unit is too much for us. Many teams stopped right there. The ones that kept going spent months staring at datasheets and paying for mistakes on board re-spins,” he said.
“I built CopperPilot so that no hardware team is ever blocked because a board is too hard to design,” he said.
Customers from startups to enterprises
The company serves a range of users, from individual engineers and startups to design service providers and larger businesses. Its customers and target markets span IoT, health and medical technology, battery technology, electric vehicles and other automotive applications.
CopperPilot said it has customers in the U.S., U.K., and Europe, alongside users in India and other countries. The company has dual headquarters in Bengaluru, India, and Houston, Texas. It identifies consumer electronics, renewables, energy storage, and robotics as further sectors that could benefit from its technology.
From plain English to schematics
Aditya explained that the agent can interpret plain-English design requirements, read component datasheets and manufacturer specifications, identify suitable components, and present alternatives for the engineer to choose from. It can then create schematics and custom symbols or footprints, proceed to PCB placement and routing, and check the design for electrical rule check (ERC) and design rule check (DRC) violations and manufacturing constraints.
Aditya said that it supports architectural decision-making by seeking clarification when requirements are incomplete or components do not meet design constraints. With sufficiently clear requirements, the agent can execute a sequence of design tasks autonomously, while allowing engineers to review or intervene at individual stages.
CopperPilot uses a combination of official application programming interfaces (APIs), direct file editing, and other methods to interact with EDA tools. “The method varies according to what works for a particular tool or task,” Aditya said.
The startup is also working toward cross-tool workflows. Traditionally, an engineer might need to inspect several tools and pieces of information separately, including the firmware code, PCB design, and communication protocols. CopperPilot aims to connect these pieces of information, identify possible interactions, and help engineers reason through problems that span hardware and software. The added value, he said, lies not just in the agent’s ability to analyze a circuit board or write firmware, but also in its ability to consider how different parts of an electronic system affect one another.
Validation is the hard part
Generating a schematic or PCB layout is only part of the work. A design must also meet electrical requirements and the constraints of the manufacturer that will build it.
Aditya explained that while ERC and DRC checks provide a baseline, they cannot catch every problem.
“While connecting two computers or two microcontrollers over a serial connection, you are supposed to connect the transmitter of one device to the receiver of the other, and the receiver of the first device to the transmitter of the other,” he explained. “It is very easy to reverse these connections, and it happens to many engineers. This is where CopperPilot really shines. It can catch mistakes that ERC and DRC checks cannot detect.”
But flagging problems is not enough. Engineers also need to know which issues matter most, what to fix first, and what remains unresolved. “For engineers preparing a design for manufacturing, the agent can produce a review report that separates blockers from non-blocking issues, prioritizes fixes, and explains the remaining problems,” Aditya said. “It may also identify design changes that could reduce cost.”
He explained that the startup built internal testing and benchmarking infrastructure because hardware design lacks a single equivalent to a software compiler or linter that can confirm whether an entire design is correct.
“With CopperPilot, we have internally built out our own harness, benchmarks, and tooling to validate the design,” he said. “The agent can read the datasheet, manufacturer specifications, and design tools, with the startup testing how well this process works through its harness and multi-agent framework.”
The company said it also develops manufacturer-specific test suites and maintains component information and examples of design failures. As the agent is used and tested, the team adds to its understanding of the ways generated designs can fail.
According to figures shared by Aditya, CopperPilot evaluated its system against approximately 49 test cases based on human-designed circuits. He said that the startup reported a task completion rate of 18% for its baseline system and 78% for CopperPilot. However, the baseline system was not specified in the information provided, and the results are based on a small, company-run benchmark that has not been independently verified.
In its press statement, the startup said that it publishes a new open-source board design each day, with around 30 designs published so far. The designs can be inspected in KiCad, giving engineers a way to examine the team’s builds rather than relying only on product demonstrations.
Plans, integrations, and data security
CopperPilot operates as a B2B software-as-a-service (SaaS) company, with plans for individual users, teams, and enterprise customers. Its individual offering includes a free Starter plan and paid Pro, Pro Plus, and Ultra plans. Team plans are paid, while enterprise customers can contact the company about specific requirements and internal deployments.
For enterprise customers, integration with existing tools and workflows is part of the proposition. CopperPilot can also connect with GitHub and ticketing systems to draw on an organization’s context and share knowledge. An engineer could create a reusable skill that checks a design against company manufacturing standards and share it with colleagues, allowing teams to bring their accumulated engineering experience into the agent’s workflow.
For organizations working with proprietary designs, CopperPilot said design data and chat history are stored locally on the user’s computer under its standard individual and paid plans, while information is sent to servers and a large language model (LLM) for processing. “CopperPilot has a zero data retention policy after an interaction,” he said at the time of the interview. “We also offer on-premises hosting as an option, although it has not yet been deployed for a customer.”
Reliability is the next test
CopperPilot’s immediate challenge is to make its agent reliable enough for engineers to use in their day-to-day work, while expanding adoption among individuals, startups, and larger design organizations. Its longer-term goal is to shorten the path from an idea to a manufacturable electronic product.
As Aditya put it, “Today, CopperPilot designs an AI camera board in about 30 minutes.” Drawing on his experience designing electronics for a student race car, he concluded, “The racecars of the future will be designed with CopperPilot.”
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