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Algorizk Labs

Mathematical, Cryptographic & Hardware R&D

Algorizk Labs is a research and engineering initiative within Qoosmo, focused on challenging computational problems at the intersection of mathematics, cryptography, software, and hardware.

We develop and study algorithms, proof-system components, and acceleration architectures for applications where computational performance and mathematical correctness are both critical.

What We Work On

Zero-Knowledge Proofs & Verifiable Computation

Research and engineering around modern proof systems, including:

  • Sumcheck and multilinear polynomial protocols
  • FRI and low-degree testing
  • Polynomial commitment techniques
  • Folding and recursive verification
  • Finite-field and polynomial algorithms
  • Prover architecture and performance analysis

Our work ranges from mathematical protocol analysis to implementation-oriented optimization.

High-Performance Mathematical Computing

Many cryptographic systems ultimately depend on a small number of expensive mathematical kernels.

Algorizk studies and develops efficient approaches for:

  • Finite-field arithmetic
  • Polynomial evaluation
  • FFT/NTT and related transforms
  • Multilinear evaluation and folding
  • Hashing and proof-system kernels
  • Memory and compute optimization

The objective is not optimization in isolation, but understanding the algorithm well enough to determine the appropriate software or hardware architecture.

FPGA & Hardware Acceleration

Algorizk explores hardware acceleration for computationally intensive cryptographic workloads.

Our work includes:

  • FPGA feasibility analysis
  • Algorithm-to-hardware architecture
  • Modular arithmetic datapaths
  • Sumcheck and polynomial-evaluation kernels
  • Hardware/software co-design
  • RTL prototyping and verification
  • Performance and resource benchmarking

Hardware is treated as one part of the optimization stack: algorithm first, architecture second, and implementation when justified.

Applied R&D

Algorizk works on technical problems that may require a combination of mathematical research and engineering.

Typical work can include:

  • Technical and performance assessments
  • Algorithm and architecture analysis
  • Cryptographic protocol R&D
  • FPGA acceleration feasibility studies
  • Research prototypes
  • Benchmarking and experimental validation
  • Specialized implementation work

The objective is to move from a difficult technical question to a validated engineering direction.

Research

Our public research explores mathematical and computational foundations for efficient verifiable computation and cryptographic systems.

Multilinear Polynomials via Tree-Based Circuit and the Sumcheck Protocol

Ali Mkhida, Adil Iguider
Cryptology ePrint Archive, Report 2026/1469

https://eprint.iacr.org/2026/1469

Current research directions include multilinear polynomial evaluation, folding techniques, transparent proof systems, finite-field algorithms, and hardware-oriented prover architectures.

Selected Engineering Work

FPGA Sumcheck

Algorizk has developed and benchmarked an FPGA-oriented Sumcheck implementation as part of its work on accelerating proof-system primitives.

Case study:

https://www.algorizk.xyz/case-studies/fpga-sumcheck

Research Notes

Longer mathematical developments, working notes, definitions, proofs, computational experiments, and open research directions are maintained separately:

https://research.algorizk.xyz

Public & Private R&D

This repository is the public GitHub entry point for Algorizk Labs.

It is intentionally not a mirror of our internal development repositories.

Selected research results, technical notes, reproducible experiments, benchmarks, and case studies may be released publicly.

Client work, production RTL, implementation-specific architectures, unpublished research, and proprietary Algorizk IP remain private.

Links

Website
https://www.algorizk.xyz

Research
https://research.algorizk.xyz

Contact / Project Inquiry
https://www.algorizk.xyz/contact


Algorizk Labs · Qoosmo

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Research and engineering in cryptography, verifiable computation, mathematical computing and hardware acceleration.

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