Built for Pharma & Biotech knowledge complexity

Turn fragmented documents into trusted, connected knowledge

Verbis Graph helps teams find answers faster, connect regulatory, clinical, scientific, and quality information across silos, and make decisions with more confidence.

Verbis Graph is a multi-tenant AI application for document understanding, knowledge extraction, and graph-based retrieval.

What Verbis Graph solves

Pharma and Biotech teams do not suffer from lack of information. They suffer from slow access, disconnected repositories, repeated internal requests, and low visibility across critical knowledge.

Grounded Q&A

Ask questions in natural language and retrieve contextual answers from real documents.

Knowledge Graphs

Reveal relationships across studies, products, processes, documents, and teams.

Cross-Functional Access

Help Regulatory, Clinical, Quality, Medical, and R&D work from the same knowledge layer.

Enterprise Ready

Support secure environments, multilingual teams, and practical enterprise adoption.

Knowledge exists. Access does not.

Valuable information is often spread across regulatory documents, clinical materials, SOPs, quality records, scientific publications, internal reports, technical files, and operational content.

Information silos

Knowledge lives in separate repositories, formats, and functions, making cross-document visibility difficult.

Slow retrieval

Teams lose time manually searching, validating, and rechecking content across systems.

Low confidence

In regulated environments, answers must be grounded, traceable, and explainable.

From documents to usable knowledge

Verbis Graph transforms large collections of structured and unstructured content into an intelligent, connected knowledge environment.

  • Ask questions in natural language across large document collections
  • Reveal hidden relationships between topics, entities, processes, and documents
  • Reduce manual review and repeated internal requests
  • Support faster discovery and better reuse of institutional knowledge

Where Verbis Graph creates value

Regulatory Affairs
Clinical Operations
Medical Affairs
Quality & Compliance
R&D and Scientific Teams
Manufacturing & Operations

Built for industries where accuracy and speed matter

By improving how knowledge is accessed and connected, Verbis Graph helps organizations reduce friction across departments, improve knowledge reuse, and unlock more value from existing information assets.

Interactive Knowledge Graphs

Transform documents into connected structures that are easier to navigate and understand.

Natural-Language Q&A

Let teams retrieve grounded answers using plain language instead of manual searching.

Secure Enterprise Adoption

Support controlled deployment and evaluation with enterprise-ready flexibility.

Benchmark released

HPC Evaluation Results for Verbis Graph

We are excited to share the results from our HPC evaluation of Verbis Graph on CINECA infrastructure.

We first established a baseline GraphRAG retrieval model on the NFCorpus medical benchmark dataset. After analyzing the initial results, we optimized the retrieval pipeline and introduced a lexical retrieval layer. The comparison below highlights the resulting improvements in retrieval quality, demonstrating significant gains before integrating our upcoming ontology-enhanced reasoning layer.

Metric
First CINECA Test
(Previous Result)
Latest NFCorpus
(New Result)
Improvement
Hit Rate
Of queries with at least one relevant result
89.16%
92.26%
↑ +3.10 pp
Mean Recall
Average proportion of relevant documents successfully retrieved
44.56%
46.57%
↑ +2.01 pp
MRR
Mean Reciprocal Rank – how early the first correct result appears
0.303
0.578
↑ +90.8%
Verbis Graph shows consistent improvement across all key retrieval metrics, with MRR nearly doubling — meaning relevant information is now ranked much higher.

For retrieval systems, the challenge is not only finding similar text. The difficult part is finding relevant information, ranking results correctly, traversing graph relationships, handling ambiguity, and supporting more complex retrieval patterns across connected knowledge.

Following the successful optimization of our retrieval pipeline, we validated Verbis Graph on the SciFact scientific benchmark, demonstrating that the improvements generalize beyond a single dataset.

SciFact Scientific Benchmark
Hit Rate 98.0%
Mean Recall 98.0%
MRR 0.601
Hit@1 51.0%
Hit@10 77.7%
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Test Verbis Graph with your own use cases

We offer a clear, practical way to evaluate the platform: a 1-month PoC/Pilot so your team can test Verbis Graph with real documents, validate relevance for your workflows, and decide based on actual results.

View Marketplace Options

Choose your cloud platform and deploy Verbis Graph instantly with integrated billing and enterprise support.

Available in AWS Marketplace Approved

AWS Marketplace

Deploy Verbis Graph in AWS Marketplace and evaluate it against enterprise-scale document collections with streamlined procurement and cloud-native adoption.

Available in AWS Marketplace
Microsoft Marketplace Approved

Microsoft Marketplace

Access Verbis Graph through Microsoft Azure Marketplace or AppSource and start a 1-month pilot in a familiar enterprise cloud ecosystem.

Get it from Microsoft Azure Marketplace Get it from Microsoft AppSource

Start a 1-month PoC/Pilot via AWS or Microsoft Marketplace and evaluate Verbis Graph with your own enterprise content.

NVIDIA Inception Program

Part of the NVIDIA Inception Program

Prodigy AI Solutions is a member of NVIDIA Inception, supporting our roadmap for scalable, high-performance AI infrastructure for enterprise knowledge retrieval, GraphRAG, and AI agent systems.

Verbis Graph Logo

Enterprise Knowledge Retrieval System. Accelerate your AI adoption with our unified graph platform.

View Marketplace Options

Choose your cloud platform and deploy Verbis Graph instantly with integrated billing and enterprise support.

Available in AWS Marketplace Get it from Microsoft AppSource

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