Volt Active Data
Real-Time Decision Layer for Mission-Critical Systems
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Latest posts
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Agents propose, something deterministic decides: closing the AI evidence gap in autonomous networks
I spent most of TM Forum Innovate Americas in Dallas on October 6-7, 2026, in back-to-back meetings and missed nearly every keynote. The hallway made up for it. In almost every conversation about autonomous networks, two topics came up: network APIs and agentic AI, often in the…
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Beyond the Network: The Real-Time Payment Realities Banks Face in 2027
Sibos 2026 was a week about the network. For me, the most important number of the week was about the bank. Over four days in Miami, from September 28 to October 1, the headlines focused on rails getting faster. Swift’s blockchain ledger is live, and most of its 17 first-mover…
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Fraud losses are up 430% since 2020. The window to stop them has not grown at all.
Key takeaway Reported consumer fraud losses reached $15.9 billion in 2025, up nearly 430% since 2020. The biggest losses come from payments victims are persuaded to authorize themselves, and the money moves fast. Detection keeps improving, yet losses keep compounding, because…
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The Systems Gap: Why the Model Is Rarely the Problem, and the Gap Between Systems Is
Fraud losses keep rising despite record investment in detection, because in most financial services stacks the systems that hold state, apply decision logic and enforce outcomes are separate. On instant payment rails, that gap has become a compliance problem. Closing it means…
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How Fast Is VoltDB in Reality? The TPS Pitfall
Why "how many transactions per second?" is the wrong first question, and what real-world PoC data tells us about VoltDB performance across telco, financial services, and autonomous network workloads The post How Fast Is VoltDB in Reality? The TPS Pitfall appeared first on Volt…
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When late is wrong: Charging at real scale
I spent the best part of a decade building online charging systems before I joined Volt, and I'll let you in on something: in a small market, charging is a solved problem. Ireland has a few million subscribers and you can drive across it in four hours. One central system, tight…
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Shiny Object Syndrome: Separating Real Fintech Value from Demo-Stage Hype
FinovateFall wrapped in New York last week: three days, dozens of live demos, and an agenda dominated by AI in nearly every form. If you are a bank or payments executive who attended, or watched the coverage, you came away with a long list of things that looked impressive on…
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What Turns an Agentic AI Recommendation Into an Automated Network Decision?
In June, in the middle of the World Cup, Jai Rajaraman of Ocient and I presented a webinar with STL Partners. We built it around a fan who commutes to work and has paid for a streaming subscription to watch a match. They don’t care that a few thousand people nearby have had the…
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The Decisioning Layer in Financial Services: Why a Late Decision Is a Wrong Decision
The gap nobody budgets for Financial services has never been better at detecting fraud. Models are accurate, scores arrive in milliseconds, and AI investment keeps climbing. Yet losses climb with it. That is not a detection problem. It is a decisioning problem. As AI models…
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The Kafka Tax: Where Cost, Complexity, and Latency Add Up When You Do Not Need the Full Cluster
In the first part of this series, I argued that Databricks and Snowflake are not walking away from Apache Kafka. They are targeting a narrower and more commercially interesting problem, which is the ingestion pipeline that exists purely to move data into a single downstream…