From Manual Metadata to Intelligent Video Search asd
Turning 2.5 million videos into searchable, time-addressable assets with a cost-efficient hybrid AI pipeline.
A video discovery platform with millions of high-value assets
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Search and tagging had become a serious bottleneck
With millions of videos, search and tagging had become a serious bottleneck.
Manual tagging didn't scale
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OperationsManual tagging didn't scale
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OperationsManual tagging didn't scale
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OperationsManual tagging didn't scale
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OperationsA hybrid AI video intelligence pipeline built for scale
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Intelligent video processing platform
A hybrid architecture balancing performance, security, and cost.
7-step AI pipeline
Each component is modular and optimized for cost and reliability.
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Real outcomes, measurable impact
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Cost comparison by architecture approach
Relative cost normalized to cloud-only baseline (100%)
Open-source intelligence, cloud applied selectively
The pipeline combines open-source models with selective cloud services, running primarily on on-prem GPU infrastructure to deliver production-grade accuracy while avoiding cost, lock-in, and unpredictability.
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Open SourceThis hybrid approach delivers production-grade accuracy while avoiding the cost, lock-in, and unpredictability of cloud-only architectures — making large-scale video intelligence economically sustainable at 2.5M+ video scale.
A searchable, time-addressable catalogue spanning millions of hours
What was previously locked behind sparse tagging and manual review is now discoverable at scale — while balancing cost efficiency with production-grade reliability.
Hours per batch of manual tagging
Hours per batch of manual tagging
Hours per batch of manual tagging
Hours per batch of manual tagging
Minutes of spot-check per batch
Minutes of spot-check per batch
Minutes of spot-check per batch
Minutes of spot-check per batch
The catalogue is now discoverable by:
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Project Based FAQ
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Real outcomes, measurable impact
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