Your data lake is your warm data.
Cut observability and SIEM costs by turning your existing data lake into a fast, searchable warm tier — without changing ingest, moving data, or replacing your stack.
- 10×
- Lower SIEM cost
- 50×
- Lower lake compute
- 30×
- Faster investigations
Data is surging out of closed SIEMs into open data lakes.
Cloud providers, data platforms, and observability vendors are all moving with it.
Observability / SIEM stays
The analyst workflow layer remains, but the data layer is becoming open.
Data moves
Open formats and cloud-native lakes are replacing proprietary hot storage.
Real-world examples
Major platforms already participating in the shift to open security data lakes.
Security teams are stuck between hot bills and cold archives.
Hot tier is expensive
Hot tier costs snowball fast. Retention bloat keeps the bill climbing.
Investigations demand speed
Security teams have no choice but to keep data hot. When an investigation hits, slow access is not an option.
Cold tier is too painful
Cut costs and you cripple investigations. Keep it queryable and the bill keeps bleeding — a trap with no clean exit.
Most cost tools fight the wrong battle.
Existing tools focus on ingest: deduplication, filtering, routing — deciding what to send to the SIEM.
Our focus is different. We reduce how much data must stay in the expensive SIEM hot tier by making the cold tier queryable and 10× cheaper — without touching ingest at all.
Putting data in cold tier makes investigations both costly and slow — defeating the purpose of keeping the data.
Cold is cheap. Hot is fast.
Warm is now critical.
The missing layer is warm: retained like cold, usable like hot, and built for AI-era workflows.
Long-horizon data
In the AI era, teams need historical data that's accessible and affordable — not a tradeoff between expensive hot and painful cold.
Built to fit workflows
A practical warm tier: cheap, fast, and seamless inside the SIEM and analyst tools your team already uses.
AI needs context
Cold storage hides costly rehydration and query delays. AI needs historical correlation — not just the latest hot data.
One layer between your lake and your analysts.
DAG sits over your existing customer data lake — adding context-aware indexing and query acceleration without moving a byte.
- EDR
- Firewalls
- Identity
- Cloud audit
- Network
Customer data lake (warm tier)
- Splunk
- Sentinel
- AI agents
- Hunters
- IR teams
From 90 days hot to 1–7 days hot.
Older data is searched directly from the data lake — fast and seamless.
See how much you'd save with DAG.
Adjust your environment below to estimate the cost reduction from shifting hot SIEM data into a DAG-powered warm tier.
The rest stays warm in your data lake — queryable in seconds.
Estimate based on industry-standard SIEM hot ingest of $2.50/GB/month and warm-tier lake storage + DAG indexing of $0.10/GB/month. Actual savings depend on your stack.
Built for your lake, not against it.
- Not another observability / SIEM
- Not proprietary storage
- Not another ingest pipeline
- Not basic federated search
Context-aware indexing and query acceleration over your existing lake.
Purpose-built for regex, free-text, IOC, and behavioral analysis — at warm-tier price with hot-tier speed.