TrialHub uses two NVIDIA L40S GPUs with Intel Ice Lake on Nebius AI Cloud to generate vector embeddings from medical and clinical-trial information. The customer story reports 100% GPU utilization. With Nebius expert support, it launched a production-ready, 250-million-vector database in days. Its MLOps-optimized stack integrates embedding workflows with a growing medical database. Raw inputs are stored in MongoDB and the embedding database in Zilliz. The customer story describes RAG-optimized LLMs and semantic search across more than 80,000 trusted medical sources, supporting research answers in its clinical-trial planning platform. Medical experts select sources for each use case, including medical guidelines, national reimbursement registries and peer-reviewed research articles. Semantic search retrieves disease information across countries to inform epidemiology and patient journey analysis.
TrialHub says traditional feasibility assessments took weeks of research through scattered medical guidelines and regulatory documents. Teams spent months synthesizing text-heavy sources, consulting experts and making judgments based on proxy data. Standard of Care assessments for just 10 countries could occupy the whole team for a week.
Nebius helped TrialHub meet tight deployment deadlines without in-house DevOps. The customer story reports domain-specific answers in seconds, 50% less time spent on feasibility assessments and three times faster patient recruitment. Nebius’s deployment post, shared by TrialHub’s company account, reports that trial delays and amendments were reduced by half. Nebius’s healthcare page reports 20 times faster research. TrialHub’s company post says Standard of Care research that took 20 hours now happens in minutes.
Nebius describes TrialHub generating embeddings on Nebius AI Cloud using two NVIDIA L40S GPUs with Intel Ice Lake. Medical experts select sources for each use case, including medical guidelines, reimbursement registries and peer-reviewed research. The resulting database supports semantic search for disease information across countries, informing epidemiology and patient journey analysis.
Nebius Customer story20 Aug 2025 · Nebius · Web pageNebius describes TrialHub generating embeddings on Nebius AI Cloud using two NVIDIA L40S GPUs with Intel Ice Lake. Medical experts select sources for each use case, including medical guidelines, reimbursement registries and peer-reviewed research. The resulting database supports semantic search for disease information across countries, informing epidemiology and patient journey analysis.
Cloud for Scientific AI and Healthcare
13 Oct 2026 · nebius.com · Web page
Nebius describes TrialHub’s MLOps-optimized vector embedding pipeline using NVIDIA L40s and Nebius expert support. It reports 250 million vectors, 80,000 analyzed sources, 20 times faster research and trial delays and amendments reduced by half.
Cloud for Scientific AI and Healthcare13 Oct 2026 · nebius.com · Web pageNebius describes TrialHub’s MLOps-optimized vector embedding pipeline using NVIDIA L40s and Nebius expert support. It reports 250 million vectors, 80,000 analyzed sources, 20 times faster research and trial delays and amendments reduced by half.
TrialHub company account
20 Aug 2025 · LinkedIn · TrialHub company account · Web page
TrialHub says Standard of Care assessments for just 10 countries could occupy the whole team for a week. It reports Standard of Care research falling from 20 hours to minutes and three times faster patient recruitment. It shares Nebius’s account of its embedding pipeline on Nebius AI Cloud, a 250-million-vector database and trial delays and amendments reduced by half.
TrialHub company account20 Aug 2025 · LinkedIn · TrialHub company account · Web pageTrialHub says Standard of Care assessments for just 10 countries could occupy the whole team for a week. It reports Standard of Care research falling from 20 hours to minutes and three times faster patient recruitment. It shares Nebius’s account of its embedding pipeline on Nebius AI Cloud, a 250-million-vector database and trial delays and amendments reduced by half.
Nebius Describes TrialHub's vector-embedding pipeline on Nebius AI Cloud
20 Aug 2025 · Nebius · Web page
Nebius describes TrialHub’s vector embedding pipeline deployed on Nebius AI Cloud with expert support. It reports a 250-million-vector database and trial delays and amendments reduced by half.
Nebius Describes TrialHub's vector-embedding pipeline on Nebius AI Cloud20 Aug 2025 · Nebius · Web pageNebius describes TrialHub’s vector embedding pipeline deployed on Nebius AI Cloud with expert support. It reports a 250-million-vector database and trial delays and amendments reduced by half.
TrialHub is FindMeCure Ltd’s clinical trial planning platform for pharmaceutical companies, biotechnology firms and contract research organizations. It combines clinical trial data, standard-of-care information and patient insights to help teams assess recruitment feasibility, select countries and research sites, and design study protocols. Its Standard of Care module covers treatment pathways, reimbursed medicines and access to care. TrialHub IQ adds an AI-powered conversational interface for searching medical guidelines, publications and customers’ own research documents.
TrialHub uses two NVIDIA L40S GPUs with Intel Ice Lake on Nebius AI Cloud to generate vector embeddings from medical and clinical-trial information. The customer story reports 100% GPU utilization. With Nebius expert support, it launched a production-ready, 250-million-vector database in days. Its MLOps-optimized stack integrates embedding workflows with a growing medical database. Raw inputs are stored in MongoDB and the embedding database in Zilliz. The customer story describes RAG-optimized LLMs and semantic search across more than 80,000 trusted medical sources, supporting research answers in its clinical-trial planning platform. Medical experts select sources for each use case, including medical guidelines, national reimbursement registries and peer-reviewed research articles. Semantic search retrieves disease information across countries to inform epidemiology and patient journey analysis.
TrialHub says traditional feasibility assessments took weeks of research through scattered medical guidelines and regulatory documents. Teams spent months synthesizing text-heavy sources, consulting experts and making judgments based on proxy data. Standard of Care assessments for just 10 countries could occupy the whole team for a week.
Nebius helped TrialHub meet tight deployment deadlines without in-house DevOps. The customer story reports domain-specific answers in seconds, 50% less time spent on feasibility assessments and three times faster patient recruitment. Nebius’s deployment post, shared by TrialHub’s company account, reports that trial delays and amendments were reduced by half. Nebius’s healthcare page reports 20 times faster research. TrialHub’s company post says Standard of Care research that took 20 hours now happens in minutes.
Nebius describes TrialHub generating embeddings on Nebius AI Cloud using two NVIDIA L40S GPUs with Intel Ice Lake. Medical experts select sources for each use case, including medical guidelines, reimbursement registries and peer-reviewed research. The resulting database supports semantic search for disease information across countries, informing epidemiology and patient journey analysis.
Nebius Customer story20 Aug 2025 · Nebius · Web pageNebius describes TrialHub generating embeddings on Nebius AI Cloud using two NVIDIA L40S GPUs with Intel Ice Lake. Medical experts select sources for each use case, including medical guidelines, reimbursement registries and peer-reviewed research. The resulting database supports semantic search for disease information across countries, informing epidemiology and patient journey analysis.
Cloud for Scientific AI and Healthcare
13 Oct 2026 · nebius.com · Web page
Nebius describes TrialHub’s MLOps-optimized vector embedding pipeline using NVIDIA L40s and Nebius expert support. It reports 250 million vectors, 80,000 analyzed sources, 20 times faster research and trial delays and amendments reduced by half.
Cloud for Scientific AI and Healthcare13 Oct 2026 · nebius.com · Web pageNebius describes TrialHub’s MLOps-optimized vector embedding pipeline using NVIDIA L40s and Nebius expert support. It reports 250 million vectors, 80,000 analyzed sources, 20 times faster research and trial delays and amendments reduced by half.
TrialHub company account
20 Aug 2025 · LinkedIn · TrialHub company account · Web page
TrialHub says Standard of Care assessments for just 10 countries could occupy the whole team for a week. It reports Standard of Care research falling from 20 hours to minutes and three times faster patient recruitment. It shares Nebius’s account of its embedding pipeline on Nebius AI Cloud, a 250-million-vector database and trial delays and amendments reduced by half.
TrialHub company account20 Aug 2025 · LinkedIn · TrialHub company account · Web pageTrialHub says Standard of Care assessments for just 10 countries could occupy the whole team for a week. It reports Standard of Care research falling from 20 hours to minutes and three times faster patient recruitment. It shares Nebius’s account of its embedding pipeline on Nebius AI Cloud, a 250-million-vector database and trial delays and amendments reduced by half.
Nebius Describes TrialHub's vector-embedding pipeline on Nebius AI Cloud
20 Aug 2025 · Nebius · Web page
Nebius describes TrialHub’s vector embedding pipeline deployed on Nebius AI Cloud with expert support. It reports a 250-million-vector database and trial delays and amendments reduced by half.
Nebius Describes TrialHub's vector-embedding pipeline on Nebius AI Cloud20 Aug 2025 · Nebius · Web pageNebius describes TrialHub’s vector embedding pipeline deployed on Nebius AI Cloud with expert support. It reports a 250-million-vector database and trial delays and amendments reduced by half.
TrialHub is FindMeCure Ltd’s clinical trial planning platform for pharmaceutical companies, biotechnology firms and contract research organizations. It combines clinical trial data, standard-of-care information and patient insights to help teams assess recruitment feasibility, select countries and research sites, and design study protocols. Its Standard of Care module covers treatment pathways, reimbursed medicines and access to care. TrialHub IQ adds an AI-powered conversational interface for searching medical guidelines, publications and customers’ own research documents.
