Company profile: EnCharge AI
1.1 - Company Overview
Company description
- Provider of analog in-memory-computing AI chips and AI compute solutions spanning edge to cloud, emphasizing efficiency and sustainability. Offers analog in-memory computing platforms, including charge-based and current-based IMC, plus chiplets, ASICs for specific AI tasks, and PCIe cards that integrate its technology for use in various computing systems to enable seamless AI deployment.
Products and services
- Charge-based Analog IMC: Custom-engineered analog in-memory computing that performs charge-domain computation using metal capacitors to overcome traditional analog processing limitations and boost efficiency by reducing data movement
- Analog In-Memory Computing: Edge-to-cloud AI computing platform that enhances compute efficiency and minimizes data movement, enabling advanced AI models without power or space constraints and emphasizing sustainability
- PCIe Cards: Standard-form-factor assemblies that integrate EnCharge AI’s analog in-memory computing technology into various computing systems, enabling seamless AI deployment and catering to various business needs
Key contacts
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Financial details
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1.2 - Competitors and similar companies to EnCharge AI
Anova
HQ: United States
Website
- Description: Provider of an end-to-end 360-degree analytics framework that shifts operators from reactive to proactive, delivering out-of-the-box analytics applications to unlock the untapped potential of network assets across functions such as marketing, monetization, customer care, and network.
- Rationale: This competitor operates in a highly similar market segment with overlapping features.
- Company type: Private company
- Employees: ●●●●●
- Total funding raised: $●●●m
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SiMa.ai
HQ: United States
Website
- Description: Provider of a software-centric edge machine learning platform, including MLSoC, a high-performance, low-power system-on-chip for ML at the edge; Palette Software to develop, deploy, and manage models with push-button ease; a Developer Kit to evaluate, prototype, and demonstrate computer vision ML applications; and Palette Edgematic, a no-code drag-and-drop environment for edge ML development.
- Rationale: This competitor operates in a highly similar market segment with overlapping features.
- Company type: Private company
- Employees: ●●●●●
- Total funding raised: $●●●m
- Backers: ●●●●●●●●●●
- Acquisitions: ●●
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EdgeConneX
HQ: United States
Website
- Description: Provider of edge infrastructure and data center solutions from hyperlocal to hyperscale, optimizing data delivery by placing Edge Data Centers, Edge Small Cells, and Edge PoPs near end users and delivering edge services with space, power, and connectivity. Offers build-to-suit and build-to-density facilities and sustainable operations targeting carbon, waste, and water neutrality by 2030, including zero waste to landfill.
- Rationale: This competitor operates in a highly similar market segment with overlapping features.
- Company type: Private company
- Employees: ●●●●●
- Total funding raised: $●●●m
- Backers: ●●●●●●●●●●
- Acquisitions: ●●
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Macrometa
HQ: United States
Website
- Description: Provider of a Global Data Network delivering a global data mesh, edge compute, and built-in data protection for building real-time apps and APIs. Offers a distributed cloud platform with a multi-model data store, complex event processing, and compute runtimes across more than 175 worldwide edge data centers, an AI CDN (PhotonIQ), and a real-time eCommerce platform.
- Rationale: This competitor operates in a highly similar market segment with overlapping features.
- Company type: Private company
- Employees: ●●●●●
- Total funding raised: $●●●m
- Backers: ●●●●●●●●●●
- Acquisitions: ●●
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Cartesiam
HQ: France
Website
- Description: Provider of edge AI tools and hardware for STM32 platforms, including NanoEdge AI Studio for adding data processing capabilities with outlier detection, classification and prediction on microcontrollers; STM32Cube.AI and Developer Cloud to optimize and deploy neural network models; X-LINUX-AI libraries for OpenSTLinux integration; STM32 Model Zoo of pre-trained models; and STM32 microcontrollers, microprocessors and smart sensors.
- Rationale: This competitor operates in a highly similar market segment with overlapping features.
- Company type: Private company
- Employees: ●●●●●
- Total funding raised: $●●●m
- Backers: ●●●●●●●●●●
- Acquisitions: ●●
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2.M&A buyers
2.1 Potential strategic acquirers in the sector
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2.2 - Strategic buyer groups for EnCharge AI
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Buyer group 3: ████████ ████████
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3. Investors and private equity firms
3.1 - Buyout funds investing in similar companies to EnCharge AI
2.2 - Growth funds investing in similar companies to EnCharge AI
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4 - Top valuation comps for EnCharge AI
4.2 - Public trading comparable groups for EnCharge AI
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