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DevTools · Cybersecurity · 1000+ · Asia-Pacific #b039_18

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Context

We are a global security software vendor with a broad platform across endpoint, cloud and network, serving enterprises, small businesses and government worldwide.

Industry: DevTools & Software · Cybersecurity
Size: 1000+ employees
Region: Asia-Pacific
Tools budget: $20K+ per month
Needs: Guardrails for AI agents and LLM apps. Our engineers are wiring agents into internal systems faster than our policies can keep up, and we need runtime controls.
Today: guardrail framework built on partner reference designs plus its own policy engine · Urgency: this year
Cloud cost optimization. Running our platform across several hyperscalers at global scale makes cloud spend hard to allocate by product line.
Today: engineering and finance reviewing cloud and model-token spend after forecast overruns · Urgency: now
Data governance & catalog. Telemetry flows from customers in many jurisdictions, and cataloguing where each dataset may be processed is manual.
Today: central policies spanning many regions applied to product telemetry · Urgency: later
Who decides: cto · procurement
Expects from suppliers: Proven operation at very large global scale; Cost allocation by business unit and region; Enterprise procurement and legal readiness
Not a fit: Startups unable to meet global support needs; Tools limited to a single hyperscaler
Stack: multi-cloud, Kubernetes, LLM APIs in production, data warehouse: cloud
Buying triggers: AI adoption push, cost pressure

Needs

NEEDDevTools · Cybersecurity · 1000+ · Asia-Pacific #b039_18Unverified· DevOps

We run across several hyperscalers at global scale and can't cleanly allocate cloud spend by product line, business unit or region. Forecast overruns pushed engineering and finance into manual reviews, now including model-token spend. A good solution must be multi-cloud, attribute cost per business unit, cover LLM usage, and arrive enterprise-ready on procurement and legal.

Budget: $20K+Trigger: AI adoption pushStack: multi-cloud

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