Which APAC AI robotics companies are most likely to be acquired in 2026?

Mujin (Japan) and Mech-Mind Robotics (China, with Singapore operations) are among the most acquisition-ready in the near term. Mujin holds deep integration with Toyota, Panasonic, and major logistics operators — a Japanese industrial strategic could justify an acquisition to secure exclusive access to its motion planning IP. Mech-Mind's 3D vision-guided robotics technology fills a capability gap for every major industrial robot OEM that has not yet built competitive machine vision. Bear Robotics (Korea), backed by LG and SoftBank, is a logical acquisition for LG CNS or an APAC food service platform operator. Rainbow Robotics (Korea), in which Samsung has taken a controlling stake, is effectively already being absorbed into the Samsung industrial ecosystem.

What valuation multiples do APAC AI robotics companies command?

Valuation benchmarks vary significantly by business model. Pure software robotics platforms (motion planning, simulation, fleet management) trade at 8-15x ARR, reflecting the SaaS premium on recurring revenue and low marginal cost of deployment. Hardware-software integrated robotics businesses trade at 3-7x revenue, with the multiple expansion driven by the proportion of recurring software and service revenue. Vision system software companies (Mech-Mind, similar to Cognex) trade at 12-20x earnings or 5-8x revenue. The relevant global comparables are Teradyne's acquisition of Universal Robots at approximately 6x revenue, Zebra Technologies acquiring Fetch Robotics, and Amazon's acquisition of Kiva Systems at a significant premium to revenue given the logistics moat. APAC companies should expect a 15-25% discount to US comparable transactions unless they hold APAC-specific IP or customer relationships that a US acquirer cannot replicate organically.

Who are the active acquirers of AI robotics companies in APAC?

Five acquirer types are active in APAC AI robotics. First, Japanese industrial conglomerates: Fanuc, Yaskawa Electric, Kawasaki Heavy Industries, and Mitsubishi Electric are all acquiring AI and software capability to upgrade their hardware product lines. Second, Korean conglomerates: Samsung (Rainbow Robotics stake), LG (Bear Robotics investor), Hyundai (Boston Dynamics, Motional) are systematically building robotics portfolios. Third, US automation and logistics platforms: Zebra Technologies, Rockwell Automation, Honeywell, and Amazon Robotics have active APAC acquisition mandates. Fourth, Taiwanese electronics manufacturers: Hon Hai (Foxconn), Delta Electronics, and Hiwin Technologies are acquiring AI robotics capability to automate their own manufacturing and offer it as a service. Fifth, sovereign investment vehicles: Singapore's Temasek and Korea's National Pension Service have co-invested in robotics platforms and could facilitate exits for APAC-native founders.

How does AI differentiate robotics companies from traditional robot OEMs for M&A purposes?

The traditional robotics industry is dominated by hardware OEMs: Fanuc, Yaskawa, ABB, KUKA, and Mitsubishi Electric collectively control the majority of the installed base of industrial robots. AI changes the competitive dynamic in three ways. First, AI enables robots to handle unstructured environments — picking irregular objects, adapting to variation in parts and materials, operating in settings where traditional programmed robots require extensive fixturing. Companies that solve unstructured manipulation command significant acquisition premiums because the problem has resisted the industry for decades. Second, AI converts robots from capital equipment into data assets: every task performed generates training data that improves future performance. A company with five years of real-world manipulation data in a target domain (food handling, semiconductor packaging, pharmaceutical dispensing) has a defensible moat a new entrant cannot buy. Third, AI enables robot fleets to be managed and updated through software, shifting the revenue model from one-time hardware sales to recurring software and service contracts. Fleet management software businesses trade at meaningfully higher multiples than hardware businesses.

What due diligence considerations are specific to AI robotics companies?

AI robotics due diligence involves both standard software diligence and a set of hardware-specific considerations that most software M&A teams are not equipped to conduct without specialist support. On the AI side, acquirers examine: training data provenance and exclusivity (is the model trained on proprietary operational data or public datasets?), real-world performance in deployment versus benchmark performance, model update cadence and the infrastructure required to retrain, and safety certification status (ISO 10218, ISO/TS 15066 for collaborative robots, and domain-specific standards for medical, automotive, or food-handling robots). On the hardware side, acquirers examine: gross margin on hardware (typically 25-40% for robotics versus 70-85% for pure software), warranty and service obligations, supply chain concentration in critical components (actuators, sensors, compute), and the split between recurring and non-recurring revenue. For APAC-based AI robotics companies specifically, acquirers examine customer concentration (a single Toyota or Samsung contract can represent more than 50% of revenue in early stages), regulatory certification requirements by market (Japan's labor law framework, Korea's industrial safety standards, China's robot certification process), and IP ownership when academic partnerships or government research grants are involved in the company's origin.

Home / Industries / AI Robotics

APAC AI Robotics: 8 Companies Compared

Eight AI-native robotics companies in APAC compared by funding, AI differentiation, M&A readiness, and likely acquirers in 2026.

Published April 25, 2026By Amafi TeamAI Robotics

AI roboticsrobotics M&AAPAC roboticsindustrial roboticsautonomous systemsAI manufacturingembodied AI

The global AI robotics market closed 2025 with approximately $18 billion in disclosed M&A and investment activity, up from $11 billion in 2024. APAC is driving a disproportionate share of this: Japan and Korea together account for more than 40% of global industrial robot installations, and both markets are at an inflection point where hardware OEMs are acquiring AI software capability rather than building it in-house.

This comparison covers eight AI-native robotics companies operating primarily in APAC: their AI differentiation, customer and data moats, financial scale, and the strategic rationale for acquisition. The analysis is prepared by Amafi Advisory for corporate development teams at industrial conglomerates, technology investors, and AI robotics founders assessing exit or fundraising options.

Why APAC Is the Defining Market for AI Robotics

Three structural factors make APAC the center of gravity for AI robotics development and M&A activity in 2026.

Labor cost inflection in manufacturing markets. Japan, Korea, Taiwan, and China are all experiencing labor cost increases and demographic contraction in the manufacturing workforce. Automation investment that would have been deferred as economically marginal ten years ago is now commercially mandatory. Japan’s manufacturing labor force is shrinking at approximately 1% per year; Korea faces a similar trajectory. This creates a structurally larger total addressable market than any regulatory or government initiative could produce.

OEM hardware incumbents without software capability. Fanuc, Yaskawa, ABB, and KUKA collectively control the installed base of industrial robots globally, but none of them has built competitive AI software capability in-house. Fanuc’s R&D is predominantly mechanical engineering and CNC hardware; Yaskawa’s software layer remains proprietary and difficult to integrate. This creates an acquisition market: every major OEM has an explicit strategy gap that an AI robotics software acquisition could close. The precedents include Teradyne’s acquisition of Universal Robots (collaborative robotics software), Rockwell Automation’s acquisition of Plex Systems (manufacturing SaaS), and Zebra Technologies’ acquisition of Fetch Robotics (autonomous mobile robots).

Sovereign investment in AI manufacturing. Japan’s government has committed $13 billion to AI and robotics through fiscal 2030 under its AI Strategy framework. Korea’s Ministry of Trade, Industry and Energy has a KRW 1.1 trillion robotics development plan through 2025. Singapore’s National Robotics Programme has funded 300+ robotics R&D projects. These programs create a pipeline of commercially viable AI robotics companies that emerge with government validation, customer references, and initial revenue — exactly the acquisition-ready profile that industrial strategics prefer.

AI Differentiation Tier Framework

Each company in this comparison is evaluated against a three-tier AI differentiation framework developed by Amafi Advisory to assess defensibility and acquisition premium:

Tier 1: AI is the product. The company’s core value proposition cannot exist without AI. Remove the AI layer and there is no product. These companies command the highest acquisition premiums because the AI capability is not replicable through traditional engineering.
Tier 2: AI transforms the product. The company operates in an existing market but AI changes the economics, performance, or accessibility of the product in a way that creates competitive separation. These companies are strong acquisition targets for incumbents facing competitive displacement.
Tier 3: AI as efficiency layer. The company uses AI to improve internal operations or reduce costs, but the product itself would exist without AI. These are operational improvements rather than defensible differentiation.

The Eight Companies

1. Mujin (Japan)

Founded: 2011 | HQ: Tokyo | Funding: Series D, approximately $85M raised | Revenue: Undisclosed, estimated $40-60M ARR

Mujin builds industrial robot controllers that eliminate the need for manual programming. Traditional industrial robots require specialist programmers to define every motion path, which limits deployment speed and restricts flexibility when production lines change. Mujin’s MujinController uses machine learning to compute motion plans in real time, enabling robots to operate in dynamic, unstructured environments without offline programming.

AI differentiation tier: Tier 1. The motion planning intelligence is the product. A Mujin-controlled robot handles variation in object position, orientation, and shape without reprogramming; a conventional robot cannot.

Data moat: Mujin has deployed controllers across Toyota, Panasonic, Aeon, and 100+ other Japanese manufacturing and logistics customers. Each deployment generates motion planning data that feeds back into the core model. The breadth of deployment across Japanese manufacturing creates a data corpus that a new entrant would need five to eight years and hundreds of customer deployments to replicate.

M&A readiness: High. The founding team has signaled openness to strategic partnership. Toyota’s involvement as a strategic customer creates a natural pathway for a deeper relationship, and Panasonic has made AI software acquisitions in adjacent categories. US automation platforms (Rockwell, Honeywell) lack Japan-specific customer relationships and regulatory familiarity; a Mujin acquisition would provide both.

Likely acquirers: Toyota Industries (strategic customer consolidation), Fanuc (motion planning AI to layer onto CNC hardware base), Rockwell Automation (Japan market entry through software), NTT (industrial IoT expansion into manufacturing).

2. Preferred Networks (Japan)

Founded: 2014 | HQ: Tokyo | Funding: Series B, approximately $115M raised | Investors: Toyota, Fanuc, NTT | Revenue: Undisclosed, primarily R&D services model

Preferred Networks develops deep learning infrastructure for physical systems, primarily robotics and autonomous driving. The company’s core technology includes distributed deep learning frameworks (MN-Core custom AI accelerator hardware) and robotics manipulation software. Toyota invested to access autonomous driving AI; Fanuc invested to access industrial robotics AI; NTT invested for autonomous network management applications.

AI differentiation tier: Tier 1. Preferred Networks builds the AI models that sit at the base of their partners’ automation investments.

Data moat: The partnerships with Toyota, Fanuc, and NTT provide access to proprietary operational datasets that are not available to any external researcher or competitor. The Toyota autonomous driving dataset alone represents years of closed-course and real-world driving data that Preferred Networks uses to improve its core deep learning research.

M&A readiness: Lower than others on this list. Preferred Networks has structured itself as a research partnership vehicle, and the existing investor relationships create complexity for a full acquisition. The more likely outcome is a deeper strategic integration with one of the existing investors (Toyota, Fanuc) rather than a third-party acquisition. However, a US AI lab acquisition (Nvidia, Google DeepMind, or similar) to access Japan’s manufacturing AI research talent is a non-trivial probability given the depth of the team.

Likely acquirers: Toyota (to vertically integrate autonomous driving AI), Nvidia (talent and research access, Japanese market footprint), Fanuc (convert R&D partner to captive capability).

3. Mech-Mind Robotics (China, APAC)

Founded: 2016 | HQ: Beijing, operations in Singapore and Germany | Funding: Series D, approximately $195M raised | Investors: Bosch Ventures, Matrix Partners China | Revenue: Undisclosed, estimated $30-50M ARR

Mech-Mind builds 3D vision-guided robotics systems for industrial applications: bin-picking, assembly, quality inspection, and palletizing. The company produces both proprietary 3D cameras and AI software that interprets camera output to guide robot motion. The camera-software integration creates a closed-loop system that outperforms configurations using third-party cameras.

AI differentiation tier: Tier 1 for 3D vision inference. The AI models that interpret irregular object scenes and compute grasping coordinates are the core product; the cameras are a delivery mechanism for high-quality training data.

Data moat: Mech-Mind has deployed systems in automotive manufacturing (SAIC, BYD supply chain), electronics assembly, and pharmaceutical logistics. The variety of object types, lighting conditions, and surface materials across deployments creates a 3D point cloud training dataset that is among the largest in the industry outside of structured academic datasets.

M&A readiness: Moderate. The China headquarters creates regulatory complexity for US acquirers (CFIUS review likely). European industrial buyers (Bosch, ABB, Kuka parent Midea) face fewer restrictions. Singapore operations reduce jurisdictional risk for non-China acquirers. Bosch Ventures’ investment positions Bosch as the most likely strategic acquirer if the company pursues an exit.

Likely acquirers: Bosch (existing investor, industrial automation portfolio), Cognex (vision system complementarity, APAC market entry), Zebra Technologies (expanding from mobile computing to vision-guided robotics).

4. Rainbow Robotics (Korea)

Founded: 2011 | HQ: Daejeon | Funding: KOSDAQ-listed, Samsung acquired 14.99% stake in 2023 | Revenue: KRW 42 billion (approximately $32M) in 2024

Rainbow Robotics builds collaborative robots (cobots) for industrial and service applications. The company developed HUBO, the bipedal humanoid robot, at KAIST, and transitioned to commercial cobot products (RB series) sold for manufacturing assembly, welding, and quality inspection. Samsung’s investment in 2023 signaled an intent to integrate cobot technology into Samsung’s semiconductor fab and electronics manufacturing operations.

AI differentiation tier: Tier 2. Rainbow’s core robots are hardware products; the AI layer (collision avoidance, adaptive force control, vision integration) is differentiating but the hardware would exist without it. The Samsung relationship moves this toward Tier 1 for Samsung-specific applications.

Data moat: Samsung’s manufacturing environments represent a closed, high-volume deployment that generates proprietary operational data. The semiconductor manufacturing domain is particularly valuable: process variation, wafer handling, and cleanroom constraint data from Samsung’s fabs is not available to any external researcher.

M&A readiness: High in principle, complex in practice. Samsung’s 14.99% stake (below the threshold requiring board representation under Korean corporate governance rules) appears to be a precursor to a deeper integration. A full Samsung acquisition is the most probable medium-term outcome, likely structured as a tender offer or block trade given the public listing.

Likely acquirers: Samsung (controlling stake progression is the most likely outcome), LG (competing cobot capability to match Samsung industrial automation), Hyundai (expanding robotics portfolio beyond Boston Dynamics into industrial applications).

5. Bear Robotics (Korea, US-origin)

Founded: 2017 | HQ: Redwood City, Korea operations | Funding: Series B, $81M raised | Investors: SoftBank, LG Technology Ventures, Reyes Holdings | Revenue: Undisclosed, food service deployment model

Bear Robotics builds autonomous food service robots: Servi, a robot waiter that navigates restaurant environments and delivers food to tables. The company expanded aggressively into Korea in 2022-2024, partnering with Lotteria, CJ Foodville, and major Korean restaurant chains. LG Technology Ventures’ investment positions Bear for integration with LG’s commercial appliance and service robotics business.

AI differentiation tier: Tier 2. The navigation AI (obstacle avoidance, table routing, human co-presence) is differentiating; the food delivery function itself is not AI-native. However, fleet management across hundreds of simultaneous deployments generates operational AI that improves continuously.

Data moat: Bear Robotics has deployed Servi units across more than 2,000 restaurant locations globally, with the Korea deployment representing the highest density anywhere. The human-robot co-presence data from these deployments — how servers, customers, and children interact with an autonomous robot in a chaotic food service environment — is proprietary and commercially valuable for any company building robots for public environments.

M&A readiness: Moderate-to-high. SoftBank’s investment history suggests a long hold unless a strategic acquirer emerges. LG Technology Ventures’ involvement makes LG CNS or LG Electronics the most natural acquirer. The Korea restaurant chain customer base creates natural synergies for any Korean conglomerate with food service operations.

Likely acquirers: LG Electronics (extend into commercial robotics adjacent to home appliance business), Samsung (competitive response to LG investment), Yum Brands or McDonald’s corporate (vertically integrate food service robotics to control unit economics at scale).

6. GITAI (Japan, US)

Founded: 2016 | HQ: Tokyo, Los Angeles | Funding: Series B, $30M raised | Investors: JAFCO, Sozo Ventures | Revenue: Pre-revenue (development contracts)

GITAI builds autonomous robots for space operations: in-space assembly, satellite servicing, and lunar surface operations. The company’s robotics technology is designed for unstructured, teleoperated, and fully autonomous operation in environments where human intervention is impossible. GITAI has development contracts with JAXA (Japan Aerospace Exploration Agency) and commercial satellite operators.

AI differentiation tier: Tier 1. The AI system must handle unstructured manipulation and error recovery in real time, with no possibility of human override. The operational domain is exclusive: no other company is building general-purpose autonomous manipulation robots for in-space commercial applications in APAC.

Data moat: Relatively limited in volume by nature of the domain, but the quality and specificity of the data is unparalleled. Microgravity manipulation data, satellite docking simulation data, and JAXA-funded test environment data are not available to any external researcher.

M&A readiness: Low to moderate near-term. The space robotics market is at an early commercial stage, and GITAI’s value is primarily in its team and IP rather than revenue. The strategic acquirer universe is unusual: Mitsubishi Heavy Industries (JAXA prime contractor), NEC (satellite systems), or a US space platform (Astroscale, Maxar Technologies, or Northrop Grumman) looking to acquire APAC sovereign space capability.

Likely acquirers: Mitsubishi Heavy Industries (space systems division), JAXA commercial affiliate, Northrop Grumman (in-space servicing expansion).

7. Movel AI (Singapore)

Founded: 2018 | HQ: Singapore | Funding: Series A, approximately $10M raised | Investors: NTUitive, Enterprise Singapore | Revenue: Undisclosed, small commercial stage

Movel AI builds autonomous navigation software for mobile robots operating in indoor environments: hospitals, warehouses, hotels, and manufacturing facilities. The core product is SESTO, an autonomous mobile robot (AMR) platform, and the underlying navigation AI stack that enables multi-robot fleet coordination. Singapore’s government-funded robotics deployment in healthcare (Institute of Mental Health, Changi General Hospital) provides reference customer validation.

AI differentiation tier: Tier 2. The navigation AI (SLAM-based mapping, dynamic obstacle avoidance, multi-agent coordination) is differentiating versus commodity mobile robot platforms, but the AMR hardware is a commodity.

Data moat: Healthcare AMR deployments generate unusual operational data: patient interaction patterns, clinical corridor navigation constraints, infection control zone awareness. This domain-specific dataset is valuable for any AMR company targeting the healthcare vertical.

M&A readiness: High — the company is at a stage where strategic acquisition is a more realistic outcome than an independent Series B-to-IPO trajectory. Singapore Enterprise Singapore and IMDA funding creates a stable runway, but the total addressable market accessible from Singapore alone is insufficient to justify an independent growth path. A regional expansion through acquisition by an APAC logistics or healthcare technology platform is the most realistic exit.

Likely acquirers: DHL Supply Chain (autonomous logistics in APAC healthcare and warehouse operations), ST Engineering (Singapore defense and industrial systems), Nidec (Japanese precision motor manufacturer expanding into AMR platforms).

8. Humanoid AI Research (Korea, emerging)

Founded: 2023 | HQ: Seoul | Funding: Seed, backed by Kakao Ventures and Korea Development Bank Venture Capital | Revenue: Pre-revenue (R&D stage)

Korea’s government-backed humanoid robotics initiative has produced a cluster of early-stage companies building whole-body control, dexterous manipulation, and AI-native motion planning for bipedal humanoid robots. This category company represents the emerging Korean humanoid robotics sector rather than a single company, given the early stage and limited public information. The Korean government’s commitment to deploying 100,000 humanoid robots in manufacturing by 2030 creates a structured demand signal that makes Korean humanoid robotics a strategically relevant acquisition category.

AI differentiation tier: Tier 1 for successful whole-body control AI. Bipedal locomotion combined with dexterous manipulation remains an unsolved AI problem; companies that demonstrate real-world task completion in unstructured environments have defensible IP.

Data moat: Early-stage, limited. The value is team and research IP rather than operational data.

M&A readiness: Low near-term. The sector is at a research stage in Korea, with most companies 12-24 months from commercial-scale validation. US humanoid robotics acquirers (Figure AI, Physical Intelligence, 1X Technologies) have expressed interest in Korean talent rather than company acquisitions at this stage.

Likely acquirers: Hyundai Robotics (stated commitment to humanoid expansion), Samsung Advanced Institute of Technology, or a US humanoid platform acquiring Korean engineering talent through an acqui-hire structure.

M&A Deal Log: Global AI Robotics Precedent Transactions

Year	Acquirer	Target	Deal value	Key rationale
2022	Hyundai Motor	Boston Dynamics	$880M (majority stake)	Logistics and manufacturing robotics AI
2022	Zebra Technologies	Fetch Robotics	$290M	AMR fleet management for warehousing
2021	Teradyne	AutoGuide Mobile Robots	~$58M	Complementary AMR portfolio
2020	Nuro	—	$500M raise (SoftBank)	Autonomous delivery validation
2017	Softbank	Boston Dynamics (from Alphabet)	Undisclosed	Humanoid and quadruped platform
2012	Amazon	Kiva Systems	$775M	Fulfillment center automation moat

The APAC-specific deal flow includes Toyota’s ongoing structured R&D investment in Preferred Networks (not a full acquisition but deeper than a standard VC investment), Samsung’s Rainbow Robotics stake, and LG’s Bear Robotics investment. The pattern suggests Japanese and Korean conglomerates are moving toward partial stakes and integration partnerships as a precursor to full acquisitions, likely to evaluate technology fit and team retention before committing to full transaction premiums.

Acquirer Landscape and Strategic Rationale

Japanese Industrial Conglomerates

Fanuc, Yaskawa Electric, Kawasaki Heavy Industries, and Mitsubishi Electric each have the same strategic problem: they sell hardware at hardware margins. Their customers increasingly expect integrated AI software — robots that learn, adapt, and improve through deployment — and none of these OEMs has built competitive AI capability in-house. The acquisition opportunity is clear, and the financial capacity is substantial: Fanuc holds approximately $7 billion in net cash.

The barrier is cultural: Japanese conglomerates have historically preferred in-house development. The cultural shift toward acquisition is occurring, but slowly. Advisors supporting AI robotics founders pursuing a Japanese industrial strategic must understand that the negotiation timeline, due diligence process, and integration planning expectations are meaningfully different from a US platform acquisition.

Korean Conglomerates

Samsung, LG, and Hyundai are all pursuing AI robotics with urgency. Samsung’s stake in Rainbow Robotics, LG’s investment in Bear Robotics, and Hyundai’s acquisition of Boston Dynamics are not isolated decisions: they represent a coordinated view across Korean industry that robotics will be a strategic differentiator in manufacturing, logistics, and consumer electronics. The Korea National Pension Service and Korea Investment Corporation are available as co-investors for APAC robotics transactions.

US Platform Acquirers

Zebra Technologies, Rockwell Automation, Honeywell Intelligrated, and Amazon Robotics each have acquisition mandates for APAC AI robotics capability. US acquirers have the financial sophistication to move quickly on a properly structured process, the institutional experience to conduct technical AI diligence, and the integration capability to absorb a founder-led AI company. The disadvantage is that US acquirers lack APAC customer relationships and regulatory familiarity — which is precisely why they need to acquire rather than build.

Valuation Framework

Business model	Typical revenue multiple	Key driver
Motion planning AI software (pure SaaS)	8–15x ARR	Recurring revenue, low churn
3D vision software (software-dominant)	12–20x earnings	Gross margin, R&D moat
AMR hardware + software (integrated)	4–7x revenue	Revenue split, service attach
Hardware OEM with AI layer	2–4x revenue	Margin profile, commoditisation risk
Pre-revenue with government contracts	3–6x capital raised	Team quality, IP exclusivity

The most common valuation gap in APAC AI robotics transactions is the mismatch between hardware-trained acquirer teams (using revenue or EBITDA multiples appropriate for equipment businesses) and the software economics underlying AI robotics platforms. A company that sells robots at 30% gross margin but generates 80% gross margin on the recurring software and support layer is not a 3x revenue business: it should be valued on the software layer at a software multiple, with the hardware treated as a customer acquisition mechanism.

Advisory Note

“The APAC AI robotics M&A cycle is running three to five years behind the US, which means the acquisition premiums paid in US transactions in 2020–2023 are only beginning to appear in APAC deal flow now. Japanese industrials in particular are transitioning from ‘we will develop this in-house’ to ‘we need to acquire now or fall behind’, and that transition creates a window for AI robotics founders with commercial traction and proprietary data to achieve strong outcomes. The key variable is not valuation methodology but acquirer readiness: the processes that work with a US platform buyer do not work with a Japanese conglomerate, and conflating them is the most common advisory mistake in this sector.”

— Daniel Bae, Founder and CEO, Amafi Advisory (former Citi TMT Investment Banking London, Moelis)

Amafi Advisory advises AI robotics companies on sell-side M&A, buy-side acquisition of robotics capability, and fundraising from strategic and financial investors. Talk to our team about a transaction in the AI robotics sector.

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