Live Stream Processing

Your data streams
run on autopilot

StreamPilot deploys AI agents that monitor your real-time data, detect what matters, and take action. No SQL. No Flink jobs. No babysitting pipelines.

Launch Dashboard → See How It Works
streampilot agent / production
00:01:34 postgres order_created — $4,200 — enterprise tier
00:01:35 kafka latency spike detected — p99 > 800ms
00:01:35 agent → alert sent to #eng-oncall, scaling up 2 replicas
00:01:37 webhook user_signup — 3rd from same company domain
00:01:37 agent → flagged as expansion signal, notified sales team
The Shift

Stream processing was built
for the SQL era

Flink, ksqlDB, Materialize, RisingWave. They all assume you'll write queries, build pipelines, and maintain them forever. StreamPilot assumes you won't.

Traditional

Write SQL, deploy pipelines, monitor dashboards

  • Hire a streaming engineer
  • Write and test SQL queries
  • Build alerting rules manually
  • Debug when pipelines break at 3am
StreamPilot

Describe what matters, agents handle the rest

  • Connect your data sources
  • Tell the agent what to watch for
  • It detects, decides, and acts autonomously
  • You get results, not maintenance burden
How It Works

Three primitives.
Infinite pipelines.

StreamPilot reduces stream processing to what actually matters: connecting data, defining intent, and letting AI handle execution.

01

Connect

Plug into Postgres, Kafka, webhooks, APIs. StreamPilot ingests your streams and understands the schema automatically.

02

Describe

Tell the agent what matters in plain English. "Alert me when latency exceeds p99 thresholds." "Flag repeat signups from enterprise domains."

03

Act

The agent monitors 24/7, detects patterns, and takes action: sends alerts, triggers webhooks, updates databases, notifies your team.

The last streaming engineer
you'll ever hire

StreamPilot watches your data so you don't have to. Built by engineers who spent years inside streaming databases and decided the whole paradigm needed to change.

Try It Now →