October 23, 2026 - Kivo Daily

Mach9 Raises $34 Million for AI Engineering Software

Kivo Daily Staff 2 on October 23, 2026

Mach9 secured $34 million in Series A funding after redirecting its business from robotics hardware to AI-powered computer-aided design software for civil engineering and infrastructure projects. Co-founded by CEO Alex Baikovitz, the company developed its software around the challenge of converting laser-scanning and imaging data into engineering-ready designs.

Key Takeaways

Mach9 raised $34 million in Series A funding following its shift from robotics hardware to AI-powered CAD software.
Co-founder and CEO Alex Baikovitz led the company’s move toward software for civil engineering and infrastructure projects.
The platform converts laser-scanning and imaging data into engineering-ready designs.
Nearly 100 customers participated in the company’s private beta across more than 2,500 projects.
The company planned to use the funding for product development, hiring and operational expansion.

Mach9 Secures $34 Million in Series A Funding

Mach9 AI software company Mach9 raised $34 million in Series A funding to expand its software business serving civil engineers and infrastructure professionals. The company, co-founded by Alex Baikovitz, shifted away from robotics hardware to develop tools that convert infrastructure scanning data into engineering-ready designs.

The funding provides capital for product development, hiring and business expansion. Mach9’s software targets a stage of engineering work in which professionals must turn large volumes of laser-scanning and imaging data into usable design documents.

The company’s approach combines infrastructure data collection with software designed to reduce the manual work involved in preparing engineering designs. Rather than concentrating on the hardware used to capture information, Mach9 now focuses on processing that information into outputs that civil engineering teams can use.

The $34 million Series A round followed the company’s decision to concentrate on this software opportunity. Its business now centers on applying artificial intelligence to technical workflows associated with infrastructure projects.

For Mach9, the pivot changed the focus of its product development and commercial strategy. The company moved from building robotics hardware toward supplying software that addresses the work required after infrastructure data has been collected.

Robotics Hardware Origins Led to a Software Pivot

Mach9 began as a robotics-focused business. Its original approach involved developing hardware for visual inspections in civil engineering, where infrastructure teams need reliable information about existing structures and conditions.

The company’s experience with potential customers helped identify a different problem in the workflow. Collecting infrastructure data was not the only challenge engineers faced. Turning that data into usable survey documents and designs also required substantial effort.

Mach9 redirected its work toward this processing stage. The company changed its focus from collecting information through hardware to developing software that could transform captured data into engineering-ready outputs.

The change also involved dropping “Robotics” from the company’s name. The revised identity reflected its concentration on software rather than robotics hardware as the primary product offering.

Baikovitz’s company therefore shifted its development priorities toward the needs of engineers who work with scanning and imaging data. Instead of treating data capture as the main product opportunity, Mach9 focused on the steps required to make the collected information useful for design and planning.

This decision established a more specific product direction: using AI to support the conversion of infrastructure data into CAD designs. Other founders have also redirected their businesses toward more focused markets, including the startup pivot into a niche market that helped Whatnot develop its marketplace around collectibles before expanding into live shopping.

Mach9’s subsequent funding round will support further development of that software-centered business.

AI-Powered CAD Tools Address Civil Engineering Workflows

Mach9’s platform processes laser-scanning and imaging data to produce engineering-ready designs. Computer-aided design, commonly known as CAD, is used by engineers to create and work with technical drawings and models.

Infrastructure projects can involve large volumes of visual and spatial information. Engineers need to convert those records into documents that support design work, assessments and planning. Mach9’s software is designed to automate parts of that conversion process.

The platform generates an initial design that licensed professionals can review and refine. This distinction matters because the software supports the engineering workflow rather than removing the need for professional review.

Mach9 has reported that its technology can accelerate parts of the design process by up to ten times. The reported figure relates to the process the software is intended to improve, rather than establishing that every project will achieve the same time savings.

The software’s intended users include civil engineering and infrastructure professionals who work with scanning data. By focusing on a defined technical task, Mach9 is addressing a specific part of the engineering process instead of offering a general-purpose AI tool.

Its product direction connects data capture with the preparation of usable design documents. That workflow is central to the company’s business model following its move away from robotics hardware.

Customer Projects Provide Early Evidence of Product Adoption

Mach9’s private beta included nearly 100 customers working across more than 2,500 projects. These figures provide an indication of the platform’s early use in civil engineering and infrastructure workflows.

The customer participation covered projects in which scanning data needed to be converted into engineering-ready outputs. The company’s software was developed to address that processing requirement, allowing engineering teams to work with information gathered from infrastructure sites.

The number of participating customers and projects provides context for the company’s commercial development. However, participation in a private beta does not by itself establish how many customers have purchased subscriptions, the revenue generated by the platform or the rate at which customers continue using it.

For Mach9, customer projects provide opportunities to apply its software to real engineering tasks. Those applications are relevant to product development because the company is focused on a technical workflow with specific requirements for accuracy and usability.

The company’s approach also fits within a wider range of specialized engineering software applications. AI tools for engineering design are being developed for technical work involving complex products and infrastructure, although different platforms target different stages of the design process.

The reported adoption figures also help explain the company’s emphasis on software development. Mach9’s product is intended to process infrastructure information that engineering teams already collect, rather than requiring the business to concentrate solely on producing data-capture hardware.

The company’s future expansion plans include improving the platform and hiring people with relevant industry expertise. Those activities will support its efforts to develop software for engineering customers and expand its operations.

Funding Supports Product Development and Business Expansion

Mach9’s $34 million Series A round was co-led by First Round Capital and Bessemer Venture Partners. Prudence and Quiet Capital also participated in the financing.

The company planned to direct the funding toward product improvements, hiring and operational expansion. These priorities align with its shift toward AI-powered CAD software and its focus on civil engineering and infrastructure customers.

Product development is a central part of the plan because the platform must convert scanning and imaging data into designs that professionals can review and refine. Continued work on that process will determine the software’s capabilities as Mach9 expands its offering.

Hiring is another stated use of the funding. Adding employees with relevant industry expertise can support product development and the company’s work with engineering customers. The company also intends to expand its operations as it develops the software business.

The financing follows a strategic change in which Mach9 moved away from robotics hardware and concentrated on the software required to process infrastructure data. Its product development, customer work and expansion plans are now organized around that focus.

Frequently Asked Questions

How much funding did Mach9 raise?

Mach9 raised $34 million in Series A funding. The company planned to use the capital for product development, hiring and operational expansion.

Who founded Mach9?

Alex Baikovitz is a co-founder and CEO of Mach9. He led the company’s shift from robotics hardware toward AI-powered software for civil engineering and infrastructure work.

Why did Mach9 pivot from robotics hardware to AI software?

Mach9’s work with potential customers revealed that converting collected infrastructure data into usable survey documents was a major challenge. The company redirected its business toward software designed to process scanning and imaging data into engineering-ready designs.

What does Mach9’s AI-powered CAD software do?

The platform converts laser-scanning and imaging data into engineering-ready designs. It generates initial designs that licensed professionals can review and refine.

How does Mach9 plan to use its Series A funding?

Mach9 planned to invest in product development, hire employees with relevant expertise and expand its operations. These priorities support the company’s software-focused business.

The L-1B Visa Turns on One Question: Is the Knowledge Really Company-Specific?

Kivo Daily Staff on October 23, 2026

The L-1 visa lets a company transfer its own employees from an overseas office into its US operation. It has two branches: L-1A carries executives and managers, and L-1B carries something rarer, employees whose value is specialized knowledge of the company’s products, processes, or systems.

When a growing company decides to move an engineer from the overseas office to the US team, the internal logic feels obvious: she built the platform, she should deploy it. USCIS applies a narrower test. The question is not whether the employee is an expert, but whether her knowledge belongs to this company specifically, and the petitions that struggle are the ones that document expertise without documenting that difference. The corporate requirements, the evidence that persuades, and the filing process all follow from that one distinction.

The corporate frame comes first

Every L-1 transfer rests on a qualifying relationship between the two companies, and the relationship can run in either direction: the foreign company may be the parent, or the US company may be. A US startup transferring from its overseas subsidiary and an overseas group staffing its American branch both qualify.

Within that frame, choosing the branch correctly matters, because the evidence for each looks different. An L-1A case is proven with organization charts and decision-making authority. An L-1B case is proven with systems, methods, and the employee’s history inside them. A transfer framed in the wrong branch invites exactly the scrutiny it could have avoided.

What the adjudicator is testing

The recurring Request for Evidence triggers in L-1 cases map the weak points: thin proof of the corporate relationship, vague or generic role descriptions, and, for L-1B specifically, knowledge that reads as general professional skill rather than company-specific expertise.

That last trigger is the heart of the category, and the working distinction is worth spelling out. Knowing a programming language is a professional skill available on the open market. Knowing the architecture of the company’s own platform, the internal methodology it developed, or the processes it built for specific clients is knowledge the market cannot supply. A strong petition demonstrates the second kind with specifics: which systems, which projects, which years, and why an outside hire could not step into them.

This also changes who the right transferee is. The most senior engineer is not automatically the strongest candidate; the strongest candidate is the person whose knowledge is hardest to replace from outside the company.

Process, timing, and costs

The employer files the petition, and three outcomes are possible: approval, a Request for Evidence, or denial. An RFE is not a denial; the case remains pending, and the response window runs up to 84 days.

Where the case concludes depends on where the employee is. A beneficiary already in the US on another status can change status without leaving, with approval documented on Form I-797. An applicant abroad continues through the consulate: after the I-129 approval, the DS-160 is completed and an interview is scheduled at the US embassy or consulate.

The government costs are known in advance: the asylum program fee ($600, $300, or $0 depending on employer type), the $500 fraud prevention fee, optional premium processing at $2,965, and I-539 fees for family members ($470 on paper, $420 online). Spouses and children come in L-2 status, and L-2 children may attend public or private school.

If the answer is no

A denial ends the petition, not the options. The company can refile with stronger evidence, file a Motion to Reopen or Reconsider, or pursue an alternative category such as H-1B or O-1. Which path makes sense depends on what the denial notice actually says, so the notice deserves a careful read before the next move is chosen.

Start with the knowledge inventory

The most useful preparation in an L-1B case happens before any form: listing what the employee knows that the market does not, tied to named systems, projects, and dates. An L-1B visa lawyer builds the petition on that inventory, and Grape Law’s L-1B guide covers the requirements, the evidence standard, and the process step by step for companies moving product knowledge into US teams.

Fees and rules were verified against USCIS records as of September 2026.

Disclaimer: This article is for general informational purposes only and does not constitute legal advice. Immigration requirements, fees, processing times, and visa availability may change. Every case depends on its specific facts and circumstances. Consult a qualified immigration attorney regarding your situation.

Day: October 23, 2026

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