Unum Cloud
Unum is a deep-tech research company building the I/O layer for AI: assembly-optimized search, storage, networking, and perception engines intended to make petabyte-scale data processing cheaper and faster. Its software targets modern data stacks, frontier AI labs, enterprises, and edge devices.
At a Glance
- Frontier AI labs and AI infrastructure teams
- Large enterprises and big-tech companies
- Database, analytics, and data-platform vendors
- Cloud, edge-computing, and telecommunications providers
- +3 more
AI Tools by Unum Cloud
(1)
USearch
Open Source Vector Search Engine
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Latest News
USearch v2.26.4 released on GitHub
Unum published FP8 Search & KV-Caching in USearch, describing Float8 vector search, KV-cache use cases, and new SIMD kernels for heterogeneous hardware.
OpenUK published a case study describing Unum's Armenian base, self-funded origins, open-core model, and planned international expansion toward Palo Alto and London.
Unum published benchmarks claiming USearch was 10x–100x faster than FAISS on 100M–1B-vector workloads using Intel Sapphire Rapids CPUs.
Products & Services
Open-source single-file similarity-search and clustering engine based on HNSW. It supports billion-scale vector search, arbitrary/user-defined metrics, quantized types, memory-mapped indexes, clustering, and native bindings across C++, Python, JavaScript, Java, Rust, C, Objective-C, Swift, C#, Go, Wolfram, SQLite, and WebAssembly.
Compact multimodal AI library and model family for understanding and searching images, text, and video, with applications including semantic search, image captioning, and visual question answering on edge and commodity hardware.
Multimodal transactional storage/database engine combining document, table, binary/media, graph, and vector data in one persistent associative layer. It provides ACID transactions, CPU/GPU acceleration, Apache Arrow interoperability, a PyTorch bridge, and Community and Performance editions.
Low-latency JSON-RPC and remote-procedure-call library using POSIX and io_uring networking, with Python and C interfaces, a CLI, and support for rich types such as images and NumPy arrays.
Market Position
Unum positions itself as a low-level, hardware-conscious alternative to general-purpose AI infrastructure and database components. USearch is presented as a faster, smaller, more portable HNSW alternative to Meta FAISS and Apache Lucene; UStore is positioned as a multimodal ACID layer that can consolidate document, graph, object/media, transactional, and vector workloads commonly split across MongoDB, Neo4j, Elasticsearch, PostgreSQL, and object storage; UCall competes with REST/FastAPI and gRPC on latency and throughput. Its differentiation is assembly/SIMD optimization, portability, minimal dependencies, mixed precision, and open-core commercialization.
Leadership
Founders
Ash (Ashot) Vardanian
Computer science and AI researcher and long-time systems programmer; he started coding as a child, founded Unum as a research project in 2015, and is identified by Unum, LinkedIn, GitHub, and OpenUK as its founder. He is also associated with the open-source projects USearch, UForm, UStore, UCall, StringZilla, and NumKong.
Executive Team
Ash (Ashot) Vardanian
Founder
Computer science and AI researcher specializing in high-performance, low-level infrastructure; creator of multiple Unum open-source projects and founder of Unum Cloud.
Founding Story
Ash Vardanian started Unum in 2015 as a research project after committing his career to AI infrastructure. The initial vision was a deep-tech research lab that would redesign low-level computing infrastructure and create scalable, efficient algorithms for search, storage, networking, and AI rather than merely build application-layer AI. The company was self-funded in its early years and later established its core team in Armenia.
Business Model
Revenue Model
Open-core model: open-source Community editions are offered alongside proprietary Performance/Enterprise editions optimized for higher efficiency and scale. The company describes its commercial focus as enterprise and large-scale customers, including AI labs, major technology companies, and public-sector users.
Pricing Tiers
Open-source versions of the core projects, including USearch, UForm, UStore, and UCall; USearch is Apache-2.0 licensed.
Proprietary optimized edition of UStore with higher scalability, described on the UStore product page.
Enterprise offering is presented on the product pages, but public price details were not provided.
Target Markets
- Frontier AI labs and AI infrastructure teams
- Large enterprises and big-tech companies
- Database, analytics, and data-platform vendors
- Cloud, edge-computing, and telecommunications providers
- Government and public-sector organizations
- Scientific computing, chemistry, and biology users
- Vector and semantic search
- Retrieval-augmented generation and LLM KV-cache search
- Image, video, text, molecule, genomics, DNA/RNA, and protein search
- Real-time edge perception and media vectorization
- Clustering, deduplication, fuzzy joins, and data integration
- Multimodal data lakes and transactional databases
- ClickHouse
- DuckDB
- TiDB
- YugabyteDB