NEW VERSION 2.0
Trusted by engineering teams at

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Intelligent clustering via
semantic context
Our cutting-edge engine groups incoming data streams by context using vectorembeddings, allowing for automated classification and routing.
Automated Classification
Reduce engineering time by tagging events based on semantic meaningand recurrence patterns.

Granular Control
Reduce engineering time by tagging events based on semantic meaningand recurrence patterns.
Filter Rules
Where
region
And
latency
Or Group
Where
status

Centralize your data ingestion
Capture telemetry across any infrastructure interaction—from server logs to API webhooks—and normalize it into a single structured stream linked to your data warehouse.
Nexastream integrates seamlessly with the tools you already use, so you cancreate pipelines directly from your cloud providers, SaaS platforms, orcustom event emitters without managing complex schema registries.
Explore integrations
Ingestion Sources
Stream Processing
POST /v1/ingest/webhook
{"source":"stripe", "event":"charge.failed", "amount":490…
24ms

NORMALIZER

Filter Rules
failed_payment_event
id: evt_1N4k... • queue: retry-high
24ms
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Data Pipeline Automation
Automated ETL workflows for enterprise scale.
Streamline Studio
Berlin, Germany
Real-time Analytics
Low-latency dashboards for fintech.
ingest_rate: 50k/s
latency: <10ms
buffer_overflow: false
DataOps Labs
San Francisco, US
Webhook Listener
Pipeline Pros
London, UK
Ready to unify your
data stack?
Join engineering teams at high-growth companies who trust Nexastream for mission-critical data ingestion.
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