Scaling Intelligence Rebuilding the core Data infrastructure
for the age of AI
Read the Docs
We are Researchers and Engineers on a
mission to advance every step of the
modern Data Processing – from Storage and Analytics, to Search and Modelling.
modern Data Processing – from Storage and Analytics, to Search and Modelling.
Our Products
UniStore
Fastest Transactional Database
Our transactional persistent database can store media, tabular, document-like, network-like, or even vector data, combining unseen universality, with revolutionary speed.
– Any Data Format– Machine Learning Ready– Open Source and Enterprise Versions
learn more

Coming Soon
UniStore
Fastest Transactional Database
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– Real-time Semantic Search – Hardware Accelerated– Non-metric Spaces
Coming Soon
UniStore
Fastest Transactional Database
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– Multi-Lingual – Multi-Modal Transformers– Light Weight
Technology behind
For every of our products we created custom tech for storage, networking,
compute, or AI modelling
compute, or AI modelling
NETWORKING
UJPRC
SEARCH
UniSearch
SEARCH
UniSearch
ENCODER
UniForm
ML
UML
Open source contributions
Our team created and is Maintaining the following Repositories.
Universal Keys & Values
Universal DBMS for Docs • Graphs • Blobs • Vectors × in Local • Remote × RocksDB • LevelDB • UMem • UDisk × from C • C++ • Python • Java • GoLang
Unexceptionally Consistent Set
If only std::set was a DBMS: collection of templated ACID in-memory exception-free thread-safe and concurrent containers in a header-only library
Uncluttered Navigable Small Worlds
Tiny Approximate Nearest Neighbors Search library for large point clouds in not necceserily metric spaces, with online updates, and hardware acceleration with x86 AVX2, AVX-512, and Arm Neon
Uninterrupted JSON Remote Procedure Calls
Remember FastAPI? This is 100x Fast-ER-API, implementing JSON-RPC, and based on interrupt-less IO technologies, like io_uring, and wrapped into a familiar Python interface
Top Technical Articles from our Blog
Nov 30,2022
Pandas, CuDF, Modin, Arrow, Spark, and a Billion Taxi Rides
Choosing the right in-memory tabular processing framework
Pandas, CuDF, Modin, Arrow, Spark, and a Billion Taxi Rides
Choosing the right in-memory tabular processing framework
Nov 30,2022
879 GB/s Parallel Reductions in C++ and CUDA
Pushing the limits of memory-bound tasks on DDR4-powered CPUs and GDDR6-powered GPUs
879 GB/s Parallel Reductions in C++ and CUDA
Pushing the limits of memory-bound tasks on DDR4-powered CPUs and GDDR6-powered GPUs
Nov 30,2022
CuPy = 50x Faster NumPy
Finding the easiest ways to accelerate your Linear Algebra workloads on modern GPUs
CuPy = 50x Faster NumPy
Finding the easiest ways to accelerate your Linear Algebra workloads on modern GPUs
Lets Work Together!