TecnologíaDesarrollo de Producto

Cómo Cypris Usa Elasticsearch para Potenciar la Investigación de I+D con IA en 500 Millones de Puntos de Datos

Cypris es una plataforma de inteligencia de I+D impulsada por IA que permite a los equipos analizar más de 500 millones de puntos de datos técnicos y de mercado en segundos. La empresa construyó su arquitectura RAG principal en Elasticsearch para búsqueda vectorial y recuperación semántica. La plataforma ahora genera informes de investigación detallados en 15 minutos en lugar de semanas, apoya un crecimiento empresarial trimestral del 30% y gestiona más de 10 terabytes de datos indexados sin restricciones de escalabilidad.

Impacto

Weeks → 15 minutes

Tiempo de generación de informes de investigación

~30% per quarter

Tasa de crecimiento trimestral de clientes empresariales

500 million+

Total de documentos indexados

1 billion+

Escala de documentos prevista en un año

Desafío

El proveedor de búsqueda anterior de Cypris causaba fallos en los clústeres y tiempos de espera bajo carga máxima, bloqueando la entrega confiable de su plataforma de investigación de IA a clientes empresariales y gubernamentales que realizan rigurosas auditorías de seguridad en cada componente del sistema.

Solución

Elasticsearch se implementó como la base de datos principal de búsqueda y vectores para el pipeline RAG de Cypris, utilizando consultas de vectores densos, puntuación híbrida BM25/vectores y pipelines de inferencia semántica para recuperar contexto preciso para su capa de IA generativa en más de 500 millones de documentos.

Herramientas y tecnologías

Lo que dicen los líderes

Aprovechar eficazmente la búsqueda semántica para identificar contexto relevante para un LLM externo es clave para nuestra solución RAG. Usar Elastic en lugar de construir nuestro propio motor de búsqueda basado en vectores nos ahorró una cantidad considerable de tiempo y recursos.

Steve Hafif, CEO, Cypris

Elastic es el socio de IA ideal para nuestro negocio. Se aseguran de que la búsqueda semántica inicial sea altamente precisa y eficiente para que podamos optimizar el rendimiento de las integraciones posteriores con modelos de lenguaje de gran escala.

Steve Hafif, CEO, Cypris
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Historia completa

Cypris is redefining how R&D teams conduct research. Its AI platform enables scientists, engineers, and strategists to analyze more than 500 million data points—spanning global patents, scientific papers, funding databases, organizations, and market news—in seconds. The platform serves clients across manufacturing, defense, and pharmaceuticals, including organizations within the U.S. Department of Energy and Department of Defense that require the highest security standards.

Building a platform of this scale and precision is a technical challenge. Cypris needed a search engine that could handle massive document volumes, support hybrid retrieval (vector similarity + traditional keyword search), and enable the fine-tuned dense vector encoding that makes its RAG pipeline accurate. Its previous search provider caused timeouts and cluster failures under peak load—an unacceptable failure mode for a product selling on reliability.

Cypris selected Elasticsearch as the foundation for its search and RAG infrastructure. The platform uses dense vector queries and semantic search inference pipelines to encode a rich representation of its data, while hybrid scoring—combining vector similarity with multi-match, filtering, and fuzziness—enables precision across niche research queries. Elasticsearch’s native vector database let the team go from zero to a working semantic search implementation quickly, without building vector infrastructure from scratch. The generative AI layer then processes Elasticsearch-retrieved context within a narrow, innovation-focused context window to minimize hallucination and deliver accurate, source-grounded reports.

The performance improvement was transformative. Report generation that previously required weeks of manual research now completes in 15 minutes. The platform handles over 500 million documents totaling more than 10 terabytes with no scalability constraints—timeouts and cluster failures are gone. Government clients, including DoE and DoD agencies, pass rigorous security audits that examine every component of the Cypris stack, including Elastic.

Cypris is growing at nearly 30% per quarter in enterprise customers, a rate it attributes directly to the competitive advantage of its search infrastructure. The company anticipates surpassing one billion stored documents within the next year through expanding data partnerships. Elasticsearch scales with that trajectory without requiring a platform change.

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