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Cut Costs, Not Security: Smarter Data at Scale
Security teams face massive data volumes, rising infrastructure costs, and a continuous flood of alerts. Building and maintaining pipelines, noisy findings, and inefficient routing push budgets to the breaking point — without making teams any more secure.
The Solution
Most security budgets don't have a visibility problem — they have a data problem. Raw events from every source flood into the SIEM at full volume, and teams pay premium ingest rates to store data their detections never touch. Intelligent filtering and routing can drop the noise before it hits your most expensive tools, while cheap archive destinations absorb the rest. Monad handles all of that in-flight — so only high-value events reach your SIEM and everything else lands at a fraction of the cost.
The result is a pipeline that actively reduces spend without cutting coverage. Monad handles ingestion, normalization, and routing at scale — reducing reliance on expensive log collectors, eliminating manual ETL work, and giving engineering teams back the roughly 40 hours a month they were spending on pipeline maintenance.
Ingest Only What Matters
Too much raw data, not enough signal. Monad filters findings before ingestion, ensuring you only process what's truly relevant and route it directly to the right teams — cutting both ingestion and storage costs.
Reduce Infrastructure & Compute Costs
Monad handles security data ETL — ingesting, transforming, and routing at scale. Our efficient data streaming reduces reliance on costly log collection infrastructure, lowers storage and compute costs, and scales effortlessly to handle massive data volumes.
Free Up Engineering Time
Manual data wrangling slows everything down. Monad automates ingestion, transformation, and routing, allowing your team to focus on security, not pipeline maintenance.
Scale Without the Overhead
Growing data volumes shouldn't mean skyrocketing costs. Monad's cost-optimized, cloud-native architecture scales efficiently — without breaking the budget.
• Use Case:
Cut Costs, Not Security: Smarter Data at Scale
Security teams face massive data volumes, rising infrastructure costs, and a continuous flood of alerts. Building and maintaining pipelines, noisy findings, and inefficient routing push budgets to the breaking point — without making teams any more secure.
Real numbers from real pipelines.
Cut ingestion costs by filtering noise and normalizing your data before it hits your SIEM.
Operational logs can be routed to cold storage at 1/10th the cost of your SIEM.
New sources go live in minutes, with zero custom parsers to maintain.
Stop paying SIEM prices for security noise.
Walk through how a cost-optimized security pipeline takes shape in Monad — filter noise and normalize your data before it hits your SIEM, route only what matters to the right destinations, and cut ingestion costs without losing visibility.
Security data is expensive. Monad fixes the math.
Most security budgets don't have a visibility problem — they have a data problem. Raw events from every source flood into the SIEM at full volume, and teams pay premium ingest rates to store data their detections never touch. Intelligent filtering and routing can drop the noise before it hits your most expensive tools, while cheap archive destinations absorb the rest. Monad handles all of that in-flight — so only high-value events reach your SIEM and everything else lands at a fraction of the cost.
The result is a pipeline that actively reduces spend without cutting coverage. Monad handles ingestion, normalization, and routing at scale — reducing reliance on expensive log collectors, eliminating manual ETL work, and giving engineering teams back the roughly 40 hours a month they were spending on pipeline maintenance.
Built to drive down the cost of security data.
Every capability compounds the savings. Filter smarter, route precisely, normalize, scale further — without adding headcount or infrastructure.
Ingest Only What Matters
Too much raw data, not enough signal. Monad filters findings before ingestion, ensuring you only process what's truly relevant and route it directly to the right teams — cutting both ingestion and storage costs.
Reduce Infrastructure & Compute Costs
Monad handles security data ETL — ingesting, transforming, and routing at scale. Our efficient data streaming reduces reliance on costly log collection infrastructure, lowers storage and compute costs, and scales effortlessly to handle massive data volumes.
Free Up Engineering Time
Manual data wrangling slows everything down. Monad automates ingestion, transformation, and routing, allowing your team to focus on security, not pipeline maintenance.
Scale Without the Overhead
Growing data volumes shouldn't mean skyrocketing costs. Monad's cost-optimized, cloud-native architecture scales efficiently — without breaking the budget.
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