Automate your
streaming operations
End-to-end observability, AI-powered incident diagnosis, and QoE-aware multi-CDN.
Less firefighting, more viewing.
• QOE FIRST •
• AUTOMATION •
• STANDARDS •
Fewer incidents. Lower OPEX.
Fix issues before viewers notice
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ML spots outliers by device, app, CDN path, ISP
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Root-cause hints with clear fix steps into Slack/Jira/Teams
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Optional auto-actions: repackage titles, adjust routing
One source of truth
- CMCD + server/CDN + packaging/encoding logs aligned
- Session-level views and clean cohort comparisons
- Faster investigations with fewer blind spots
QoE-aware delivery
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Per-session steering via HLS/DASH Content Steering
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Mid-stream switches; enable low-latency only when it fits
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Balance QoE, cost, and energy
Streaming analytics and automation platform
From raw streaming data and system logs to actionable results: EINBLIQ.IO detects patterns, investigates root causes, and delivers hands-on guidance directly into your ops workflow.
What’s new
IBC 2026: Join us!
From streaming data to action: CMCD v2, machine learning and agentic investigation IBC is returning to Amsterdam from 11–14 September 2026, and this year EINBLIQ.IO will be exhibiting as part of the German Pavilion. Meet us at booth 3.B48c to see how high-fidelity...
Operational AI Beyond the Wrapper
As Germany takes the spotlight at VivaTech 2026, EINBLIQ.IO will be part of the German exhibition area in Paris. For us, the event is a great opportunity to discuss how AI can create real operational value, especially in media and streaming. From media data to action...
Are you really “fine” at 1.2% error rate?
Think a 1.2% error rate means your streaming service is healthy? Traditional dashboards often hide “long tail” delivery issues that frustrate users. Explore how EINBLIQ.IO’s Focus framework uses machine learning and AI agents to move from passive monitoring to automated, actionable streaming insights.