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Graph AI

Category: AI in Healthcare

AI-powered pharmacovigilance platform to automate drug safety monitoring and reporting Graph AI was founded in 2024. The company is led by Raghav Parvataraju. Based in Pleasanton, California, United States. Team size: 11-50. Total funding raised: $3 million. Latest round: Seed. Key investors include Bessemer Venture Partners.

Founded
2024
Headquarters
Pleasanton, California, United States
Team size
11-50
Total funding
$3 million

Value proposition

To transform the pharmacovigilance market by automating the traditionally manual, inefficient, and expensive processes for monitoring and reporting adverse drug events, leading to significant cost savings and improved accuracy

Products and solutions

Graph Safety Suite - unified AI platform for patient safety, Graph Safety /intake - multi-channel ingestion and intelligent triage, Graph Safety /nucleus - touchless case processing with causality validation, Graph Safety /report - adaptive generative reporting (Aug 2026), Graph Safety /signal - predictive surveillance (Nov 2026), Graph Safety /assure & /comply - QPPV governance and audit readiness (Jan 2027), GraphX - proprietary GenAI platform

Unique value

Graph AI's uniqueness lies in being the first GenAI-native platform specifically designed for pharmacovigilance. The platform combines vigilance, science, and AI to create an intelligent guardian that protects lives across the global safety landscape.

Target customer

Pharmaceutical companies, biotech companies, and contract research organizations (CROs)

Industries served

Life Sciences, Pharmaceuticals, Biotechnology, Medical Devices

Technology advantage

The key technological advantage is an AI-powered platform that can efficiently and accurately process unstructured data to identify and report adverse drug events. The platform achieves 70% productivity gains, 90% faster regulatory reporting, and substantial cost savings for customers.

How they differentiate

Graph AI positions itself as an AI-native challenger in the pharmacovigilance market. Their key differentiation lies in their specialized focus on patient safety and leveraging their proprietary AI-powered SaaS platform to automate and improve the efficiency of pharmacovigilance processes, achieving 70% efficiency gains and 90% faster reporting.

Main competitors

IQVIA, Accenture, Cognizant, Traditional pharmacovigilance service providers

Key partnerships

Bessemer Venture Partners (lead investor), Google Cloud (strategic GTM partner, Google Cloud Marketplace), Strategic partnerships with pharmaceutical companies and CROs

Notable customers

Not publicly available - early stage company

Major milestones

Secured $3 million in seed funding led by Bessemer Venture Partners in October 2025, Development and launch of their AI-powered SaaS platform for pharmacovigilance, Delivered remarkable traction with enterprise customers, Pipeline spanning over 7,000 drugs, Graduated from Google Cloud ISV Startup Springboard program, Graph Safety Suite launched on Google Cloud Marketplace (June 2026)

Growth metrics

92% faster processing, 66% cost savings, 90% reduction in effort, processing time reduced from 3+ hours to under 10 minutes per case, Pipeline spanning over 300 drugs monitored by enterprise customers

Market positioning

Graph AI is an emerging startup and a new entrant in the pharmacovigilance market, aiming to disrupt the industry with its AI-native approach. They are positioned as a technology-focused innovator challenging more established players in the $8 billion pharmacovigilance market.

Geographic focus

The company is based in California, United States, and is initially focused on the North American market, with plans for global expansion.

Patents and IP

Not publicly available

About Raghav Parvataraju

Raghav Parvataraju has extensive experience in the life sciences and technology sectors. He previously held leadership positions at LTI Mindtree and other global organizations. He has a background in product management, strategy, and business development, with a focus on AI and data analytics in the pharmaceutical industry.

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