graph ai

Introducing graph safety suite Pharmacovigilance and patient safety are under growing pressure. From rising data volumes and fragmented systems to increasing regulatory expectations. Incremental automation and disconnected tools are no longer sufficient. graph safety suite is an AI-native, integrated patient safety platform designed to unify the entire safety lifecycle into a single connected ecosystem. Built as a single platform from the ground up, graph safety brings together source and intake, case processing, aggregate reporting, signal detection, risk management, and regulatory compliance, eliminating silos and enabling intelligence to flow seamlessly across safety operations. With data integrity, traceability, and regulatory readiness built in from the start, graph safety helps safety teams shift from reactive processes to connected, insight-driven decision-making, while keeping humans firmly in control. graph safety is purpose-built for modern drug safety organizations that need: - A unified view of safety data across systems and workflows - AI-native intelligence applied across the lifecycle, not bolted on - Confidence in compliance, audit readiness, and data provenance If you’re interested in learning more or seeing a demo of graph safety, you can sign up here : 👉 https://graphsafety.ai #graphaafety #PatientSafety #DrugSafety #Pharmacovigilance #AIinLifeSciences #graphai Raghavendra Parvataraju Vijay Ponukumati Mohan Konyala Ashutosh Bordekar Ashish Pedaprolu Vanita Nathalia Srinivasan

Introducing graph safety suite Pharmacovigilance and patient safety are under growing pressure. From rising data volumes and fragmented systems to increasing regulatory expectations. Incremental automation and disconnected tools are no longer sufficient. graph safety suite is an AI-native, integrated patient safety platform designed to unify the entire safety lifecycle into a single connected ecosystem. Built as a single platform from the ground up, graph safety brings together source and intake, case processing, aggregate reporting, signal detection, risk management, and regulatory compliance, eliminating silos and enabling intelligence to flow seamlessly across safety operations. With data integrity, traceability, and regulatory readiness built in from the start, graph safety helps safety teams shift from reactive processes to connected, insight-driven decision-making, while keeping humans firmly in control. graph safety is purpose-built for modern drug safety organizations that need: - A unified view of safety data across systems and workflows - AI-native intelligence applied across the lifecycle, not bolted on - Confidence in compliance, audit readiness, and data provenance If you’re interested in learning more or seeing a demo of graph safety, you can sign up here : 👉 https://graphsafety.ai #graphaafety #PatientSafety #DrugSafety #Pharmacovigilance #AIinLifeSciences #graphai Raghavendra Parvataraju Vijay Ponukumati Mohan Konyala Ashutosh Bordekar Ashish Pedaprolu Vanita Nathalia Srinivasan

Introducing graph safety suite. At DIA 2026, we’ll be unveiling graph safety suite, our AI native platform designed to help organizations modernize pharmacovigilance and patient safety. graph safety suite is built to simplify complexity, strengthen intelligence across the safety lifecycle, and support teams as they move from reactive processes to proactive vigilance. Built on an AI native foundation, graph safety suite unifies safety data, workflows, and insights to enable clarity, confidence, and continuity without adding friction. More to come. #DIAPV2026 #DIA2026PV #GlobalPharmacovigilance2026 #Pharmacovigilance #DrugSafety #PatientSafety #AIDrugSafety #AIPharmacovigilance #GenAIPV #GenAI #LiteratureSurveillance #SafetySurveillance #SafetyDatabase #graphai #graphsafety #graphsafetysuite #graphx Raghavendra Parvataraju Vijay Ponukumati Mohan Konyala Ashutosh Bordekar Ashish Pedaprolu Vanita Nathalia Srinivasan Suresh Balusu

Patient safety teams don’t lack data. They lack connection. Across the industry, safety organizations manage information spread across systems, formats, and functions, making it difficult to move from signal detection to confident decision making. The result is often reactive vigilance, manual effort, and delayed insights, even as expectations continue to rise. We believe the future of patient safety depends on connected intelligence, where data flows seamlessly across intake, cases, signals, risk, reporting, and compliance. This is the challenge we’re addressing at graph ai with graph safety and one we’ll be discussing at DIA 2026. #DIA2026 #PatientSafety #Pharmacovigilance #AIinLifeSciences #GraphSafety

We’re heading to the DIA Global Pharmacovigilance and Risk Management Strategies Conference from 26 Jan - 28 Jan 2026. graph ai will be participating at the DIA Global Pharmacovigilance and Risk Management Strategies Conference, joining global pharmacovigilance and patient safety leaders to discuss what’s next for the industry. Patient safety teams today face fragmented systems, rising volumes, and increasing regulatory expectations. We believe the future lies in AI-native, connected intelligence designed to support human expertise, not replace it. At the conference, we’ll be sharing how graph safety is helping organizations: • capture safety data across every source • correlate signals and context across the safety lifecycle • comply with confidence in an always-on regulatory environment Over the coming weeks, we’ll share more on what this means in practice. 📍 See you at the DIA Global Pharmacovigilance and Risk Management Strategies Conference 🔗 www.graphsafety.ai #DIAPV2026 #DIA2026PV #GlobalPharmacovigilance2026 #pharmacovigilance #drugsafety #patientsafety #AIPharmacovigilance #AIDrugSafety #GenAIPV #GenAI #LiteratureSurveillance #SafetySurveillance #graphsafety #graphx

We’re hiring for a Technical Support Specialist in our Customer Success team.   At graph ai, this role serves as the first point of contact for customers using our Graph Safety Product Suite and plays an important role in ensuring reliable, timely, and compliant support in a regulated healthcare and pharma environment.   The work focuses on: – Frontline technical support and issue triage – Managing the full lifecycle of customer support tickets – Coordinating closely with Engineering and Operations teams – Supporting customers on best practices and effective use of the platform   Role: Technical Support Specialist Experience: 3–5 years in Technical / Customer Support Location: Hyderabad, Telangana (In-office)   We’re looking for someone with strong troubleshooting skills, hands-on experience supporting software or SaaS products, and clear, empathetic communication. Experience in healthcare, pharma, or regulated environments is a plus.   If this sounds like you, or someone you know, we’d welcome a conversation. Apply: https://lnkd.in/exwX9gbP Email your resume to: careers@graphservices.ai Subject: Technical Support Specialist – India   #customersupport #technicalsupport #saasjobs #healthcareIT #GraphAI  

As the year comes to a close, I’ve found myself reflecting with a deep sense of gratitude and quiet pride in how far this journey has come. This was a year of conviction, validation, and delivery. We delivered unprecedented outcomes to customers who realized significant value and tangible results from what we built together. We also made one of the most important decisions of our journey to building Graph Safety as an AI native SaaS platform. It was a deliberate bet on where the future is headed, and the validation we received from customers, investors, advisors, and our own teams strongly affirmed that belief. We set out to challenge the traditional services model and build software that could truly transform outcomes. Along the way, graph ai was featured in “Roadmap Reinventing IT Services in the Age of AI” by Bessemer Venture Partners, reinforcing our belief that a new operating model for technology services is taking shape. Graph was also featured across multiple media outlets for how we are disrupting the IT services industry with a software centric approach. That growing momentum translated into deep belief from partners and investors who share our vision. Welcoming Bessemer Venture Partners as an investor was a meaningful milestone in that journey. At the same time, we built a strong foundation of domain and technology talent, expanded our engineering presence across India and Colombia, and launched Graph Safety as an integrated patient safety platform bringing intelligence, automation, and compliance together in a way that simply did not exist before. In parallel, our product roadmap evolved significantly, setting the stage for the market to see us launch multiple new capabilities in the year ahead. What I’m most grateful for, though, is the team. The belief, resilience, and ownership I see every day are what make this journey truly special. This is a group of people who care deeply about the problem we are solving and the impact we want to create. As the new year begins, I’m filled with excitement and optimism. There is so much ahead more to build, more to learn, and more impact to create. We are just getting started. Wishing everyone a very happy new year. May it be filled with health, purpose, and the courage to build what truly matters.

From all of us at graph ai, warm wishes for the festive season. We hope this time brings rest, reflection, and a positive start to the year ahead. Raghavendra Parvataraju Ashutosh Bordekar Vijay Ponukumati Mohan Konyala

We’re excited to welcome Rayeesa Khan to Graph AI as our Human Resources Manager. Rayeesa brings 12+ years of hands-on HR experience, spanning Hire-to-Retire operations, HR tech implementation, performance management, and employee engagement. She’s worked closely with growing teams to build strong HR foundations, simplify processes, and create a great employee experience — exactly what we need as we scale. At Graph AI, Rayeesa will focus on building scalable people processes and strengthening performance and engagement frameworks. We’re thrilled to have her join us at this exciting stage of our journey. Please join me in giving Rayeesa a warm welcome! graph ai

We’re excited to welcome Jorge Andrés Tafur Qui... to Graph AI as he joins us in the role of Senior Software Engineer to help build the next generation of our patient-safety platform. Based out of Colombia, Jorge is a Software Systems Engineer with 15+ years of experience across banking, accounting, and healthcare. He brings platform engineering expertise, having previously served as Staff Engineer at Commure, where he helped built high-volume data platforms, microservices, and critical healthcare integrations. He has also led engineering teams at Scotiabank, driving large-scale systems development and delivery.   At Graph AI, Jorge will play a key role in shaping our platform architecture, scaling our data and microservices ecosystem, and accelerating delivery across our patient-safety product suite. Jorge loves both dogs and cats and prefers walking over driving. Please join us in welcoming Jorge to the team. We’re thrilled to have him onboard as we continue building the future of patient safety! graph ai