MyDecisive Raises $12M Seed to Cut Enterprise Observability Costs in the AI Era

Enterprise technology has developed an expensive habit. Every new application, cloud service, Kubernetes cluster, AI workload, and security platform generates another torrent of telemetry. Companies collect it because they might need it someday, vendors store it because someone is paying the bill, and finance eventually notices that observability costs are climbing faster than infrastructure itself.

That question sits at the center of MyDecisive's emergence from stealth. The company announced a $12M seed funding round led by Copper Sky Capital, giving it new capital to accelerate product development and expand go-to-market efforts across financial services, retail, telecommunications, and healthcare. Led by Co-founder and CEO Ari Zilka, MyDecisive is approaching observability with a simple but increasingly important premise: organizations should manage telemetry intelligently before it becomes another enterprise tax.

The timing matters because enterprise AI is not just creating smarter software. It is creating more operational complexity, more telemetry, more governance pressure, and higher infrastructure costs for the teams expected to keep everything online.

What Happened

MyDecisive emerged from stealth after securing $12M in seed funding led by Copper Sky Capital. The company develops enterprise infrastructure software focused on reducing unnecessary telemetry ingestion while improving operational visibility through automation, governance, and AI-assisted workflows. Its primary platforms include SmartHub, an open-source telemetry control layer, and Octant, a commercial suite for operational governance and automation.

SmartHub filters telemetry generated by OpenTelemetry and Kubernetes while the data is still moving through the pipeline, before organizations have already paid to ingest and store it. Octant extends that approach with governance, automation, security controls, and AI-driven operational workflows designed to help enterprises manage increasingly complex production environments. For companies already wrestling with exploding observability costs, the shift is philosophical as much as technical: stop collecting everything first and asking expensive questions later.

That sounds almost obvious until you remember how much enterprise software has been built around collecting every log, trace, and metric just in case someone eventually needs it. MyDecisive argues that intelligent filtering and policy decisions should happen upstream, where they can reduce noise before it becomes cost.

Why This Matters

Telemetry has quietly become one of the fastest-growing operational expenses inside modern enterprises. Cloud-native architectures generate enormous volumes of operational data, AI applications increase infrastructure utilization, security platforms add additional monitoring layers, and Kubernetes environments continuously produce events, metrics, and traces that organizations often retain because deleting information feels riskier than storing it.

The result is predictable: storage costs rise, processing costs rise, and engineering teams spend more time sorting through noise than identifying useful operational signals. MyDecisive is targeting that economic imbalance rather than simply offering another dashboard. That distinction matters because enterprises rarely complain about having too little visibility. They complain about paying for visibility that never turns into faster decisions.

Infrastructure does not become valuable because it collects more information. It becomes valuable when it helps people act with greater confidence using less effort, less waste, and less operational drag.

Market Context

Artificial intelligence has dominated enterprise technology headlines, but AI infrastructure depends on operational discipline that rarely receives equal attention. Every AI application increases demands on compute, storage, networking, security, and monitoring. Every additional inference workload creates another stream of telemetry, so organizations pursuing enterprise AI inherit a second challenge: operating increasingly complex systems without allowing costs to spiral alongside innovation.

MyDecisive enters the market at that intersection. Rather than competing directly with companies building larger language models or faster chips, the company focuses on making the surrounding infrastructure more economically sustainable. The next generation of infrastructure companies may not win because they collect more information. They may win because they help customers determine which information actually deserves attention.

Sometimes the smartest system is not the one producing the most data. It is the one disciplined enough to ignore what does not matter, preserve what does, and make the operational decision easier for the human or automated system downstream.

Competitive Landscape

MyDecisive also benefits from aligning with technologies enterprises already trust. Its architecture is built around OpenTelemetry, Kubernetes, and Prometheus rather than requiring organizations to abandon existing operational investments. That approach reduces adoption friction while fitting naturally into cloud-native environments already standardized around open technologies.

Enterprise customers rarely celebrate wholesale replacement projects. Founders often love talking about disruption because disruption photographs well on conference stages, but CIOs usually prefer incremental improvement that avoids creating another migration project with a 7-figure consulting budget. Open standards create leverage because they allow innovation without forcing unnecessary replacement cycles.

That practical reality often determines whether infrastructure software becomes widely adopted or remains an impressive technical demonstration. If MyDecisive can plug into existing telemetry pipelines, reduce waste, and preserve the signals enterprises actually need, it has a cleaner adoption story than another observability platform asking buyers to start over.

What This Signals

Ari Zilka brings unusual credibility to this challenge. His career includes foundational work spanning Terracotta, Ehcache, Walmart.com, Hortonworks, and New Relic, giving him experience across distributed systems, enterprise infrastructure, and observability. That background matters because infrastructure companies succeed by solving operational problems customers already understand intimately.

Enterprise infrastructure rarely rewards optimism alone. It rewards pattern recognition, and the people who build durable infrastructure platforms are often the ones who have watched production systems fail repeatedly, learned where complexity hides, and developed an appreciation for removing friction instead of adding features. MyDecisive appears focused on exactly that discipline.

The funding also signals continued investor interest in tools that make AI-era infrastructure more governable. As enterprise systems become more automated, the operational layer around those systems becomes more important, not less.

The Bigger Industry Shift

The broader significance of MyDecisive's $12M funding round extends beyond a single startup. Enterprise software is entering a phase where operational efficiency is becoming just as important as raw capability. Customers still want AI, automation, and observability, but they increasingly reject operating models where every new capability automatically creates another permanent cost center.

That makes telemetry optimization more than an infrastructure conversation. It becomes a financial conversation, a governance conversation, and ultimately a boardroom conversation. The companies most likely to define the next generation of enterprise infrastructure will not simply generate more intelligence. They will eliminate unnecessary complexity before it becomes someone else's invoice.

For operators building enterprise technology, that may be the most valuable signal hidden inside MyDecisive's funding announcement. The future of observability is unlikely to belong to whoever stores the most data. It will belong to whoever helps customers understand which data actually deserves to survive.