Through computational tools, Valthos analyzes biological data to design adaptive solutions against emerging threats. PHOTO: VALTHOS
Reimagining biodefense at the intersection of AI, biology and urgency.
Updated
November 27, 2025 3:26 PM
Through computational tools, Valthos analyzes biological data to design adaptive solutions against emerging threats. PHOTO: VALTHOS
Valthos has raised US$30 million in seed funding, led by the OpenAI Startup Fund, Lux Capital and Founders Fund, to advance its mission of building next-generation biodefense systems.
The company’s work comes at a time when biotechnology is evolving at an unprecedented pace. Biotechnology is moving at record speed. These new tools can lead to life-changing medical discoveries, but they also bring the risk of dangerous biological agents being developed faster than ever.
“The issue at the core of biodefense is asymmetry”, said Kathleen McMahon, co-founder of Valthos. “It’s easier to make a pathogen than a cure. We’re building tools to help experts at the frontlines of biodefense move as fast as the threats they face”. The gap Valthos aims to close is between the rapid rise of biological threats and the slower pace of developing cures. Therefore, the company is developing AI systems that can rapidly analyze biological sequences and significantly shorten the time needed to design medical countermeasures.
“In this new world, the only way forward is to be faster. So we set out to build a new tech stack for biodefense”, said Tess van Stekelenburg, co-founder of Valthos. “This software infrastructure strengthens biodefense today and lays the groundwork for the adaptive, precision therapeutics of tomorrow”.
The company was founded by van Stekelenburg, a partner at Lux Capital and McMahon, the former head of Palantir’s Life Sciences division. Together, they’ve built a multidisciplinary team of experts from Palantir, DeepMind, Stanford’s Arc Institute and MIT’s Broad Institute, bringing together deep experience in software engineering, machine learning and biotechnology.
“Technology is moving fast. An industrial ecosystem of builders, companies and solutions further democratizes AI to provide broad resilience, and ensures the U.S. continues to lead as AI increasingly powers everything around us. As AI and biotech rapidly advance, biodefense is one of the new industry verticals that helps maximize the benefits and minimize the risks”, said Jason Kwon, OpenAI’s Chief Strategy Officer. “Valthos is pushing the frontier of protection and defense in one of the most strategic intersections of multiple world-changing technologies, and with the team to do it”.
Looking ahead, Valthos plans to expand its engineering team and scale its software infrastructure for both government and commercial partners — moving closer to its goal of enabling faster, smarter and more adaptive biodefense capabilities.
Keep Reading
Examining the shift from fast answers to verified intelligence in enterprise AI.
Updated
November 28, 2025 4:18 PM
Startup employee reviewing business metrics on an AI-powered dashboard. PHOTO: FREEPIK
Neuron7.ai, a company that builds AI systems to help service teams resolve technical issues faster, has launched Neuro. It is a new kind of AI agent built for environments where accuracy matters more than speed. From manufacturing floors to hospital equipment rooms, Neuro is designed for situations where a wrong answer can halt operations.
What sets Neuro apart is its focus on reliability. Instead of relying solely on large language models that often produce confident but inaccurate responses, Neuro combines deterministic AI — which draws on verified, trusted data — with autonomous reasoning for more complex cases. This hybrid design helps the system provide context-aware resolutions without inventing answers or “hallucinating”, a common issue that has made many enterprises cautious about adopting agentic AI.
“Enterprise adoption of agentic AI has stalled despite massive vendor investment. Gartner predicts 40% of projects will be canceled by 2027 due to reliability concerns”, said Niken Patel, CEO and Co-Founder of Neuron7. “The root cause is hallucinations. In service operations, outcomes are binary. An issue is either resolved or it is not. Probabilistic AI that is right only 70% of the time fails 30% of your customers and that failure rate is unacceptable for mission-critical service”.
That concern shaped how Neuro was built. “We use deterministic guided fixes for known issues. No guessing, no hallucinations — and reserve autonomous AI reasoning for complex scenarios. What sets Neuro apart is knowing which mode to use. While competitors race to make agents more autonomous, we're focused on making service resolution more accurate and trusted”, Patel explained.
At the heart of Neuro is the Smart Resolution Hub, Neuron7’s central intelligence layer that consolidates service data, knowledge bases and troubleshooting workflows into one conversational experience. This means a technician can describe a problem — say, a diagnostic error in an MRI scanner — and Neuro can instantly generate a verified, step-by-step solution. If the problem hasn’t been encountered before, it can autonomously scan through thousands of internal and external data points to identify the most likely fix, all while maintaining traceability and compliance.
Neuro’s architecture also makes it practical for real-world use. It integrates seamlessly with enterprise systems such as Salesforce, Microsoft, ServiceNow and SAP, allowing companies to embed it within their existing support operations. Early users of Neuron7’s platform have reported measurable improvements — faster resolutions, higher customer satisfaction and reduced downtime — thanks to guided intelligence that scales expert-level problem solving across teams.
The timing of Neuro’s debut feels deliberate. As organizations look to move past the hype of generative AI, trust and accountability have become the new benchmarks. AI systems that can explain their reasoning and stay within verifiable boundaries are emerging as the next phase of enterprise adoption.
“The market has figured out how to build autonomous agents”, Patel said. “The unsolved problem is building accurate agents for contexts where errors have consequences. Neuro fills that gap”.
Neuron7 is building a system that knows its limits — one that reasons carefully, acts responsibly and earns trust where it matters most. In a space dominated by speculation, that discipline may well redefine what “intelligent” really means in enterprise AI.