Quasi ai
QuaSi (Nubri GmbH), based in Berlin, builds hybrid quantum-classical AI software that accelerates computational fluid dynamics simulations for HPC, semiconductor, optics, and cryogenic system applications.
- Company typePrivate
- Founded1987
- HeadquartersBerlin, Germany
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
What Quasi ai does
QuaSi (legally Nubri GmbH) is a Berlin-based, pre-commercial deep-tech company building hybrid quantum-classical AI software to accelerate computational fluid dynamics (CFD) simulations. Its core platform combines Physics-Informed Neural Networks (PINNs), DeepONets, and PINNFormer architectures with quantum submodules, positioned as drop-in accelerators for existing High-Performance Computing (HPC) workflows rather than full quantum replacements. The company targets three verticals: semiconductors and optics (via single crystal growth simulation), cryogenic system design (vessel optimization, fluid behavior, heat transfer, pressurization modeling), and HPC/scientific computing more broadly.
The product surface is anchored on the Quantum PINNs Framework for crystal growth modeling and the Cryogenic System Design Models documented in the public cryogenic_vessel_sim repository. Technically, the architecture pursues parallel co-processing where quantum and classical components collaborate on multi-step CFD pipelines, offloading bottlenecks such as spectral transforms, linear solvers, and uncertainty quantification. Distribution is community-led: open-source GitHub repositories serve as the top-of-funnel, with direct enterprise contact (email and website form) representing the only disclosed commercial channel. No pricing is publicly disclosed and there are no named customers, contracts, or strategic partnerships in the source data.
Commercially, the company is at the earliest stage of go-to-market. Headcount is reported at 1–10 employees, the only disclosed contact is founder/principal Aditya Seshaditya, and the single institutional signal is a 2025-10-20 listing with accelerator Alchemist Chicago (no disclosed capital). Revenue model is described as subscription or service-based licensing of quantum-enhanced AI simulation solutions, but no live contracts, ARR, or quantifiable outcomes are evidenced. The business is effectively a founder-led research venture transitioning toward commercialization through open-source credibility and accelerator participation.
Quasi ai firmographics
Firmographics- Name
- Quasi ai
- Legal name
- Nubri GmbH
- Website
- https://quasi.digital
- Company type
- Private
- Founded year
- 1987
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Short description
- QuaSi (Nubri GmbH), based in Berlin, builds hybrid quantum-classical AI software that accelerates computational fluid dynamics simulations for HPC, semiconductor, optics, and cryogenic system applications.
- Ownership category
- akta.pro rank
Quasi ai industry classification
Industry- Product category
- Quantum-Enhanced Computational Fluid Dynamics Simulation Software
- akta.pro primary industry
- Quantum Simulation Algorithms (Dynamics, Monte Carlo, Lattice Models) (HDAGADAG)
- akta.pro secondary industries
- Quantum Linear Algebra & Differential Equation Solvers (HDAGADAF), Quantum Simulation (Physics/Chemistry/Materials) Research (HDAGAMAG)
Keywords
Where Quasi ai is headquartered
LocationHeadquarters
- HQ city
- Berlin
- HQ country
- Germany
- HQ region
- Europe
Offices2 records
Markets served
Quasi ai business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Operations, Marketing or Sales
Revenue model
- Quantum AI Simulation Solutions: Licensing or service-based delivery of quantum-enhanced AI solutions for computational fluid dynamics, targeting organizations requiring advanced simulation capabilities for materials discovery and system optimization
Go-to-market motion1 record
Distribution channels1 record
Marketing channels2 records
Quasi ai product offering
Product offeringCore offering
Quasi AI develops and delivers hybrid quantum-classical AI software for computational fluid dynamics (CFD) simulations. Its Quantum PINNs Framework accelerates single crystal growth modeling for semiconductors and optics, while its Cryogenic System Design Models optimize cryogenic vessels through accurate prediction of fluid behavior, heat transfer, and pressurization dynamics. These offerings are built on a platform combining PINNs, DeepONets, and PINNFormer with quantum submodules that plug into existing HPC workflows as drop-in accelerators.
Product overview
QuaSi offers a unified platform of quantum-enhanced AI solutions for computational fluid dynamics and scientific computing. The core offerings include the Quantum PINNs Framework for crystal growth simulation and the Cryogenic System Design Models for vessel optimization. These products are built on hybrid quantum-classical architectures (PINNs, DeepONets, PINNFormer) that integrate as drop-in accelerators within existing HPC workflows, enabling parallel co-processing for spectral transforms, linear solvers, and uncertainty quantification tasks.
Differentiator
Problem solved
Functional benefit
Products and services
- Quantum PINNs Framework Hybrid quantum-classical physics-informed neural network framework that delivers high-precision simulation of single crystal growth, enabling materials discovery and process optimization for semiconductor and optics manufacturers and researchers.
- Cryogenic System Design Models Quantum-classical models for cryogenic vessel optimization that accurately predict fluid behavior, heat transfer, and pressurization dynamics for companies and research institutions designing cryogenic storage, aerospace, and scientific equipment.
- Hybrid Quantum-Classical CFD Acceleration Platform Integrated platform combining physics-informed neural networks (PINNs), DeepONets, and PINNFormer with quantum submodules to deliver drop-in acceleration of computational bottlenecks, including spectral transforms, linear solvers, and uncertainty quantification, across existing HPC workflows for CFD.
Companies that use Quasi ai
Customer profileSegments3 records
Ideal customer profiles3 records
Quasi ai technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
AI capability3 records
Feature4 records
Quasi ai partnerships and signals
Strategic signalRecent moves5 records
Expansion highlights4 records
Quasi ai competitors and assessment
Company assessmentDirect peers
- Classiq: Direct peer — quantum software platform focused on hybrid quantum-classical algorithm development and HPC integration; targets enterprise and research customers with similar drop-in workflow integration messaging.
- Zapata AI: Direct peer — builds quantum-classical generative AI and physics-informed models for simulation and optimization across industrial verticals; shares Quasi AI's PINN/quantum-submodule technical stack and enterprise focus.
- QC Ware: Direct peer — enterprise quantum software company building hybrid quantum-classical algorithms for chemistry, materials, and optimization; competes for the same HPC-adjacent enterprise buyer.
- Multiverse Computing: Direct peer — develops hybrid quantum-classical AI solutions for industrial applications including materials simulation and finance, sharing Quasi AI's quantum-AI hybrid approach targeting real-world engineering workloads.
Broad incumbents
- ANSYS: Broad incumbent — enterprise CFD and multiphysics simulation software leader (Fluent, CFX) with announced quantum acceleration R&D partnerships; owns the incumbent CFD workflows Quasi AI aims to accelerate.
- Quantinuum: Broad incumbent — full-stack quantum hardware and software platform with hybrid quantum-classical HPC integration and simulation software; competes for the same enterprise quantum-acceleration narrative at much larger scale.
- Xanadu: Broad incumbent — photonic quantum hardware and software platform with HPC integration and quantum simulation tooling; competes in the hybrid quantum-classical CFD/simulation buyer conversation.
- Siemens Digital Industries Software: Broad incumbent — enterprise CFD/simulation portfolio (Simcenter STAR-CCM+, Simcenter FloEFD) exploring quantum acceleration through research partnerships; represents a customer-or-competitor risk to Quasi AI.
Emerging players
- Strangeworks: Emerging player — quantum computing platform providing hybrid quantum-classical compute orchestration to enterprises and researchers, comparable to Quasi AI's QC-HPC integration layer.
- 1QBit: Emerging player — quantum software company developing hybrid quantum-classical algorithms for materials, chemistry, and life sciences; shares Quasi AI's vertical focus on industrially relevant simulation workloads.
Market position
Strengths4 records
Weaknesses4 records
Competitive moat3 records
Key risks6 records
Key highlights5 records
Customer concentration
Quasi ai social profiles
Digital presenceQuasi ai financial estimates
Financial estimateRevenue estimate
Valuation estimate
Quasi ai leadership team
Management profileNumber of profiles
Profiles1 record
Quasi ai funding detail
Funding detailFunding overview
Funding rounds1 record
Investors1 record
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Quasi ai 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 Quasi ai
What does Quasi ai do?
Quasi AI develops and delivers hybrid quantum-classical AI software for computational fluid dynamics (CFD) simulations. Its Quantum PINNs Framework accelerates single crystal growth modeling for semiconductors and optics, while its Cryogenic System Design Models optimize cryogenic vessels through accurate prediction of fluid behavior, heat transfer, and pressurization dynamics. These offerings are built on a platform combining PINNs, DeepONets, and PINNFormer with quantum submodules that plug into existing HPC workflows as drop-in accelerators.
Is Quasi ai a public or private company?
Quasi ai is a private company. It is classified as founder individual operated bootstrapped and is currently operating.
When was Quasi ai founded?
Quasi ai was founded in 1987. It employs 1 to 10 people.
Where is Quasi ai based?
Quasi ai is headquartered in Berlin, Germany, in the Europe region.
How does Quasi ai make money?
One revenue line is on record: quantum AI Simulation Solutions.
Who are Quasi ai's main competitors?
Direct peers on record are Classiq, Zapata AI, QC Ware and Multiverse Computing. Broad incumbents are ANSYS, Quantinuum, Xanadu and Siemens Digital Industries Software. Emerging players are Strangeworks and 1QBit.
Does Quasi ai have an API?
No public API is recorded for Quasi ai.
What industry is Quasi ai in?
Quasi ai's product category is Quantum-Enhanced Computational Fluid Dynamics Simulation Software. Its primary akta.pro industry code is HDAGADAG, Quantum Simulation Algorithms (Dynamics, Monte Carlo, Lattice Models), with a secondary code of HDAGADAF, Quantum Linear Algebra & Differential Equation Solvers.