SqueezeBits
- Company typePrivate
- Founded2022
- HeadquartersSeoul, South Korea
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
SqueezeBits firmographics
Firmographics- Name
- SqueezeBits
- Legal name
- SqueezeBits
- Website
- https://squeezebits.com
- Company type
- Private
- Founded year
- 2022
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Ownership category
- akta.pro rank
SqueezeBits industry classification
Industry- Product category
- AI Model Optimization Software
- NAICS
- Computer Systems Design and Related Services (5415)
- akta.pro primary industry
- Edge AI Model Optimization & Compression (quantization, pruning, distillation) (HDAAAJAA)
- akta.pro secondary industry
- Model Compression & Optimization (Quantization, Distillation, Pruning) (HDAAACAL)
Keywords
Where SqueezeBits is headquartered
LocationHeadquarters
- HQ city
- Seoul
- HQ country
- South Korea
- HQ region
- Asia
Markets served
SqueezeBits business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Technology or R&D, Personnel, Marketing or Sales, Operations
Go-to-market motion1 record
Distribution channels2 records
Marketing channels2 records
SqueezeBits product offering
Product offeringCore offering
SqueezeBits develops AI lightweight and optimization technology that uses quantization to reduce memory usage and computational load in neural network models. The technology enables efficient deployment of AI services on edge devices with limited resources and supports a wide range of AI models and frameworks. Projects have been delivered to over 20 enterprise customers including Naver and SK Telecom.
Product overview
SqueezeBits offers AI lightweight and optimization technology focused on quantization to reduce memory usage and computational requirements. The company's core technology enables efficient AI service deployment on edge devices and supports various AI models and environments. Projects have been completed with over 20 companies including Naver and SK Telecom.
Differentiator
Problem solved
Functional benefit
Products and services
- AI Lightweight Technology Quantization-based AI optimization software that reduces memory usage and computational load, enabling efficient AI service deployment on edge devices and supporting various AI models and environments. Targeted at enterprise technology and telecom companies.
Quantifiable outcome
- Reduced memory usage and computational load for AI models
- +1 more outcomes
Companies that use SqueezeBits
Customer profileNamed customers2 records
Segments2 records
Ideal customer profiles2 records
SqueezeBits technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
AI capability1 record
Feature3 records
SqueezeBits partnerships and signals
Strategic signalPartnerships
One partnership is on record.
- Modular Inc.coreSqueezeBits signed a strategic partnership with US unicorn Modular Inc. to collaborate on AI infrastructure and expand into North America. The partnership includes joint projects on enhancing AI models and ecosystems, highlighted by a demonstration at NVIDIA GTC 2026.
Scale indicators3 records
Recent moves5 records
Expansion highlights5 records
SqueezeBits competitors and assessment
Company assessmentDirect peers
- OctoAI: AI inference optimization platform offering model compilation, quantization and hardware-aware deployment — directly comparable to SqueezeBits' core offering of optimizing AI models for efficient runtime, though OctoAI is more cloud-centric while SqueezeBits emphasizes edge.
- Neural Magic: Software-based model quantization and acceleration (now part of Red Hat) targeting CPU/GPU inference. Shares SqueezeBits' core thesis of using quantization to make AI models deploy efficiently on commodity and resource-constrained infrastructure.
- Deeplite: AI model compression and optimization focused on edge and resource-constrained devices — closely aligned with SqueezeBits' edge AI quantization focus and shared customer pain points around memory and compute.
- Latent AI: Edge AI optimization platform using quantization and pruning to deploy models on constrained hardware — direct competitor targeting the same edge AI deployment use cases as SqueezeBits.
- Edge Impulse: Edge AI development platform (now part of Qualcomm) for building and deploying optimized models on edge devices — overlaps with SqueezeBits' edge deployment focus and shares the Qualcomm ecosystem relationship.
Emerging players
- Arcee AI: Focused on small, efficient language models and model distillation/merging — an emerging player addressing the same customer pain point (efficient AI deployment) from a different angle, competing for the same budget.
Broad incumbents
- NVIDIA (TensorRT): TensorRT is NVIDIA's widely adopted model optimization and inference engine, bundled with NVIDIA GPUs and dominant in data center and edge AI — represents the most entrenched incumbent competing against SqueezeBits' offering.
- Intel (OpenVINO): OpenVINO toolkit optimizes and deploys AI models across Intel hardware (CPU, GPU, NPU) — broad incumbent offering overlapping with SqueezeBits' edge AI optimization thesis, particularly for Intel-based edge devices.
- Qualcomm AI Engine: Qualcomm's AI Engine SDK and Neural Processing SDK optimize models for Snapdragon platforms — broad incumbent in the same edge silicon ecosystem where SqueezeBits operates, and also an active partner via QAIPI.
- Hugging Face (Optimum): Hugging Face's Optimum library provides hardware-aware model optimization and quantization across many backends — a widely adopted open-source incumbent with significant developer mindshare in the same model optimization category.
Market position
Strengths4 records
Weaknesses4 records
Competitive moat4 records
Key risks6 records
Key highlights6 records
Customer concentration
SqueezeBits social profiles
Digital presenceSqueezeBits financial estimates
Financial estimateRevenue estimate
Valuation estimate
SqueezeBits leadership team
Management profileNumber of profiles
Profiles1 record
SqueezeBits funding detail
Funding detailFunding overview
Funding rounds2 records
Investors5 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
SqueezeBits M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about SqueezeBits
What does SqueezeBits do?
SqueezeBits develops AI lightweight and optimization technology that uses quantization to reduce memory usage and computational load in neural network models. The technology enables efficient deployment of AI services on edge devices with limited resources and supports a wide range of AI models and frameworks. Projects have been delivered to over 20 enterprise customers including Naver and SK Telecom.
Is SqueezeBits a public or private company?
SqueezeBits is a private company. It is classified as venture growth investor backed and is currently operating.
When was SqueezeBits founded?
SqueezeBits was founded in 2022. It employs 11 to 50 people.
Where is SqueezeBits based?
SqueezeBits is headquartered in Seoul, South Korea, in the Asia region.
Who are SqueezeBits's main competitors?
Direct peers on record are OctoAI, Neural Magic, Deeplite, Latent AI and Edge Impulse. Arcee AI is listed as an emerging player. Broad incumbents are NVIDIA (TensorRT), Intel (OpenVINO), Qualcomm AI Engine and Hugging Face (Optimum).
Does SqueezeBits have an API?
No public API is recorded for SqueezeBits.
What industry is SqueezeBits in?
SqueezeBits's product category is AI Model Optimization Software. Its primary akta.pro industry code is HDAAAJAA, Edge AI Model Optimization & Compression (quantization, pruning, distillation), with a secondary code of HDAAACAL, Model Compression & Optimization (Quantization, Distillation, Pruning). Its NAICS code is 5415.