World’s Leading Agentic AI Observability Platform for Highly Regulated Industries.
Patent-pending compression for 90% cost reduction on observability.
The most compliance-heavy industries cut cost without ever sacrificing data integrity — every record preserved, provable, and audit-defensible. Frontier agentic AI investigates each incident, surfaces the root cause, and files the ticket.
Overview
COSTS SAVED
$4.29M
live · blended SIEM rate
LOGS COMPRESSION
18.1×
+16.2× vs gzip
TRACES COMPRESSION
27.7×
OTLP · tail-sampled
METRICS COMPRESSION
30.3×
OTLP + Prom remote-write
EVENTS PROCESSED
14.3B
all 14.3B cold · 3.1B mirrored hot
TRACES IN CATALOG
42.6M
queryable · 30-day window
STORAGE SAVED
94.1%
218 TB less to store
ACTIVE TROLLS
247
all healthy · 0 stale
Cost Savings — last 24h
Optimization Ratio — last 24h
Where every byte must be retained for audit.
Compliance-heavy industries cannot use lossy observability tools. Regulators do not accept “1,247 similar events suppressed” in a forensic investigation. Sasquatch is engineered for the buyers who pay the most and audit the hardest.
Finance & Banking
Trades, settlements, treasury, AML. Retention measured in years, not days. Every system-of-record event must survive an examiner walk-through. Lossless retention is non-negotiable.
FinServ & Insurance
Claims, underwriting, brokerage, KYC. Regulator-grade audit trails across every customer interaction. Lossy data is a compliance violation, not an optimization.
Healthcare & Pharma
PHI, clinical trials, GMP manufacturing, EHR. Every patient touchpoint and every batch record must be preserved exactly as recorded. Forensic-grade integrity.
Government & Defense
Air-gapped deployments, sovereign clouds, classified workloads. No external SaaS dependency. Observability that stays inside the perimeter, audit-grade by default.
Aviation & Aerospace
Flight ops, maintenance, telemetry, ATC integration. Forensic-grade retention for incident reconstruction. Lossless or it is not evidence.
Energy, Utilities & Manufacturing
OT and IT convergence. Plant floor telemetry, grid sensors, asset health. Audit trails that satisfy regulators and incident investigators, including the moments before a fault.
The SIEM bill is the tip.
Observability costs stack seven layers deep — logs, traces, and search compute each carry their own invoice. Only the first one shows up on the marketing page.
The line item you approved when you bought the tool.
Every ingested GB is parsed and indexed. Often 15× the ingestion fee.
Raw + archived in your bucket. Compounds with every retention extension.
Every audit, Tap Out, and rehydration pays egress. NAT stacks on top.
Compliance wants 12 months searchable. SIEM defaults are 15–30 days.
Spans outnumber logs 5–10×. Priced per span, billed in parallel with logs.
For active tenants, search compute routinely exceeds the ingestion line.
Ask out loud. It finds the root cause and files the ticket.
Sasquatch agents reason across every log, trace, span, and metric in your stream. Investigate any incident end to end, talk to any agent about what it is seeing live, and open the ticket in Linear, Jira, or ServiceNow. By voice or one click.
Every signal, one root cause.
Point an agent at an error and it does the legwork: pulls the full trace, walks each errored span, correlates the logs, and checks service health and error-rate metrics. Then it writes the root cause with the evidence and a fix, and files the ticket, pre-filled and linked back to the trace.
- Reasons across traces, spans, logs, and metrics together
- Cites the exact spans and log lines it used
- Files the ticket only when you say so
payments-service exhausted its DB connection pool (50/50); requests waited 3000ms then 503'd, cascading to api-gateway.
Ask your fleet anything, live.
Every Sasquatch agent (a Troll) sees everything flowing through its node. Talk to it directly: which services are erroring, how payments is doing, any slow traces in the last hour. It answers from the live stream with real numbers. Voice-native, with no query language to learn.
- Talks straight to the ingestion point, not a stale index
- Services, incidents, and system health on demand
- Hand off to a full investigation, then file the ticket
Pay less. Keep everything.
Sasquatch learns your telemetry shape at the edge, compresses every byte losslessly, and stores the result in your own cloud. Same data. Same compliance. ~91% less spend.
Calibrated to your environment.
The compression model adapts to the shape of your telemetry — the patterns and structure unique to your stack. Not a generic compressor. That calibration is where the 15–18× comes from.
Every byte survives.
SHA-256 compare on decompress vs the original, verified on every event. Not “less than 1% data loss.” Not “statistically similar.” Exact bytes. Every time.
Cold logs are never gone.
Pull any time range from your bucket, decompress on demand, forward to any SIEM in seconds. Re-hydrate for incidents or audits without paying twice to ingest.
Use the query language your team already runs.
Sasquatch ships its own query engine, Snowman, that speaks the protocols your existing tools already speak. Drop our endpoint into Grafana, point your Splunk dashboards at it, keep your PromQL alerts. The chunks are yours, in your bucket — we just make them queryable.
The single largest observability surface on the market. Point your existing Datadog Logs and APM searches at Sasquatch — same tag-and-facet syntax, same dashboards, same alerts. Cut the ingest line item, keep the workflow your team already lives in.
service:payments status:error @duration:>500ms | stats count by host
SPL parser + REST API shim. Splunk-shaped searches resolve against your Sasquatch chunks — no Splunk indexer required to search them.
index=app sourcetype=k8s_pod level=error timeout | stats count by service
Drop in Sasquatch as a Loki datasource. Your existing Grafana dashboards, alert rules, and ad-hoc Explore queries keep working — same LogQL, same response shape.
{namespace="payments",level="error"}
|~ "timeout"
| rate(5m)Kibana queries (KQL) and Lucene-shaped searches resolve through the same adapter. Your existing Discover boards, Lens visualizations, and alert rules keep working — point them at Sasquatch instead of the Elastic ingest pipeline.
service:"payments" AND level:"error" AND @timestamp > "now-5m" AND duration > 500
OTLP traces compressed at the edge, queryable from the same Tempo datasource panel. Trace ID lookup is fast against your cold storage — no full-bucket scan.
{ resource.service.name = "api-gateway"
&& status = error
&& duration > 500ms }PromQL adapter over the metric chunks Sasquatch already compresses. Existing alert rules and recording rules continue to evaluate against the same series labels.
rate(http_requests_total{
status=~"5.."
}[5m])No re-indexing
Indexes are baked into the chunk format. No separate ElasticSearch cluster, no nightly rebuild — query directly against your cold storage.
Cost is yours, not the SIEM's
Query compute is the line item that breaks SIEM budgets. With Sasquatch the marginal cost of a search is cloud egress + a slice of CPU — not a licensed search-compute unit.
Migrate without lifting
Run your existing dashboards against Sasquatch in shadow mode. Same Loki / SPL / PromQL output, same result counts. Cut over when you're sure.
Kubernetes, bare metal, big-data clusters. One agent. One wedge.
Whatever shape your telemetry comes in, Sasquatch reads it where it’s generated. Containers, host syslog, Hadoop NameNode, Spark drivers, MongoDB rotated logs — same lossless compression path, your choice of cloud bucket.
EKS · GKE · AKS · self-managed.
A DaemonSet drops one agent per node. CRI log tail picks up /var/log/containers; an OTLP receiver on :4317 / :4318 takes traces and metrics straight from your apps. Native cloud identity — IRSA on AWS, Workload Identity on GCP, Managed Identity on Azure. No service-account sprawl, no extra credentials.
syslog · journald · file tail.
Static-musl binary plus signed DEB and RPM packages on apt + yum repos. Tail rotated logs, listen on syslog (RFC 3164 / 5424 over UDP or TCP), or pull from journald. Datacenter, branch site, air-gapped network — same agent, no Kubernetes required, no internet round-trip on the hot path.
Hadoop · Spark · Mongo · Postgres.
A second agent variant covers two new shapes. Text mode (CLP-T) compresses Hadoop, Hive, OpenStack, and Java application logs. JSON mode (CLP-S) compresses MongoDB, CockroachDB, Elasticsearch, and Spark event logs. Same engine, one --format flag, beats the reference open-source compressor on every published corpus.
Compressed chunks land in your bucket of choice — S3, GCS, Azure Blob, R2, MinIO.
Hot events mirror to the SIEM you already run. Full destination list on /integrations.
See what you stop paying.
Send us a sample of your actual log traffic. We’ll run it through Sasquatch, verify it decompresses byte-for-byte, and hand back a real number — your projected monthly spend on your current stack, vs on us.
No contract, no “qualification call,” no sales funnel. Engineers talking to engineers.
Our one promise
“You should not pay more for observability than for the app infrastructure you’re observing. And you should never have to choose between good observation, audit trails, and cost.”