Qdrant vs Neysa

Neither company has publicly disclosed a valuation, making a definitive size comparison difficult. Qdrant employs 50-200 people, while Neysa has 50-200 employees.

Neysa has raised more in total funding at $30M, compared to Qdrant's $28M — a gap of $2M.

Both Qdrant and Neysa share the same Awaira Score of 55/100. The Awaira Score is a composite metric that factors in valuation, total funding raised, company stage, employee count, and market category.

Neysa was founded by Shashank Samala in 2023. Qdrant's founder information is not currently available in our database.

Qdrant: Qdrant builds a high-performance vector similarity search engine and managed vector database service optimized for production AI applications requiring fast nearest-neighbor retrieval at scale. The engine is implemented in Rust for memory efficiency and throughput, and supports filtered vector search, payload indexing, and hybrid dense-sparse retrieval in a single system.\n\nThe company raised approximately 28 million USD and serves AI engineering teams across Europe and North America building recommendation systems, semantic search, computer vision pipelines, and RAG-based applications that require low-latency retrieval over large embedding collections. Qdrant is open-source with a managed cloud offering, following the commercial open-source model common in developer infrastructure.\n\nThe vector database market is consolidating around a handful of well-funded players as enterprises standardize their AI data stacks and look for production-grade infrastructure with strong SLAs and support. Qdrant differentiates from pure-cloud competitors through its Rust-based performance characteristics and its strong adoption in European markets where data sovereignty concerns make self-hosted options more commercially attractive than US-operated managed services. Neysa: Neysa builds cloud infrastructure purpose-built for AI workloads, offering GPU-accelerated compute, storage, and networking optimized for training and inference at scale. The platform targets enterprises and AI labs in India that need high-performance compute without the cost and complexity of hyperscaler lock-in.\n\nThe company raised approximately $30M in Series A funding and has attracted early adopters across the Indian AI startup ecosystem seeking affordable, low-latency GPU access. Neysa operates its own data centers with an emphasis on cost-per-token efficiency for large model training.\n\nAs Indian AI labs and enterprises scale their model development ambitions, Neysa sits at the center of a critical infrastructure gap. Domestic GPU cloud capacity is severely constrained relative to demand, and Neysa is one of the few India-headquartered players building the physical and software stack to address it.

Qdrant was founded first in 2021, giving it 2 years of additional market experience. Neysa was founded later in 2023. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Both Qdrant and Neysa report similar employee counts of approximately 50-200. Team size is often a proxy for operational scale, though lean AI companies can punch well above their headcount.

Yes, Qdrant and Neysa are direct competitors — both operate in the AI Infrastructure space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.