Startup employee reviewing business metrics on an AI-powered dashboard. PHOTO: FREEPIK
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.
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Can SPhotonix’s optical memory technology protect data better than today’s storage?
Updated
December 17, 2025 2:47 PM
SPhotonix's 5D Memory Crystals™. PHOTO: SPHOTONIX
SPhotonix, a young deep-tech startup, is working on something unexpected for the data storage world: tiny, glass-like crystals that can hold enormous amounts of information for extremely long periods of time. The company works where light and data meet, using photonics—the science of shaping and guiding light—to build optical components and explore a new form of memory called “5D optical storage”.
It’s based on research that began more than twenty years ago, when Professor Peter Kazansky showed that a small crystal could preserve data—from the human genome to the entire Wikipedia—essentially forever.
Their new US$4.5 million pre-seed round, led by Creator Fund and XTX Ventures, is meant to turn that science into real products. And the timing aligns with a growing problem: the world is generating far more digital data than current storage systems can handle. Most of it isn’t needed every day, but it can’t be thrown away either. This long-term, rarely accessed cold data is piling up faster than existing storage infrastructure can manage and maintaining giant warehouses of servers just to keep it all alive is becoming expensive and environmentally unsustainable.
This is the problem SPhotonix is stepping in to solve. They want to store huge amounts of information in a stable format that doesn’t degrade, doesn’t need electricity to preserve data and doesn’t require constant swapping of hardware. Instead of racks of spinning drives, the idea is a durable optical crystal storage system that could last for generations.
The company’s underlying technology—called FemtoEtch™—uses ultrafast lasers to engrave microscopic patterns inside fused silica. These precisely etched structures can function as high-performance optical components for fields like aerospace, microscopy and semiconductor manufacturing. But the same ultra-controlled process can also encode information in five dimensions within the crystal, transforming the material into a compact, long-lasting archive capable of holding massive amounts of information in a very small footprint.
The new funding allows SPhotonix to expand its engineering team, grow its R&D facility in Switzerland and prepare the technology for real-world deployment. Investors say the opportunity is significant: global data generation has more than doubled in recent years and traditional storage systems—drives, disks, tapes—weren’t designed for the scale or longevity modern data demands.
While the company has been gaining attention in research circles (and even made an appearance in the latest Mission Impossible film), its next step is all about practical adoption. If the technology reaches commercial viability, it could offer an alternative to the energy-hungry, short-lived storage hardware that underpins much of today’s digital infrastructure.
As digital information continues to multiply, preserving it safely and sustainably is becoming one of the biggest challenges in modern computing. SPhotonix’s work points toward a future where long-lasting, low-maintenance optical data storage becomes a practical alternative to today’s fragile systems. It offers a more resilient way to preserve knowledge for the decades ahead.