Manufacturing on live streams.
Sensor readings, machine logs, MES/ERP state and partner scans all decay in seconds. A pipeline running next to the line sees drift before it becomes downtime — and opens the work order with the context in it.
Every line, one live stream
Gateways publish sensor readings over MQTT or HTTP; machine logs stream in via file-tail; MES and ERP state joins from JDBC sources. Dedup absorbs the retries that flaky industrial networks produce, and event-time ordering keeps readings honest even when a gateway buffers offline and uploads late.
Baselines per machine, drift in minutes
Keyed state per asset maintains rolling baselines: avg, stddev, min/max over sliding windows. Deviation from a machine's own baseline — not a fleet-wide constant — trips deterministic rule stages in microseconds. A sensor that stops reporting is caught by keyed timers: silence is a signal too.
From anomaly to work order
When a baseline breaks, an LLM stage drafts the context — what drifted, how fast, against which history — and an MCP stage opens the work order in your CMMS and notifies the technician. Statistical baselines work out of the box; your own failure model plugs in as a stage when you have one.
Correlate the order with reality
A stream-stream join matches purchase orders with shipment scans and goods receipts inside a window — the gaps are the alerts: shipped-but-never-scanned, received-but-never-ordered, late against promise. Every partner system plugs in via webhook, polling or file drops.
Built for the plant floor
Runs next to the line, not across the WAN.
Edge-sized footprint
Pulse runs as a single self-hosted process with an embedded engine — an industrial PC in the cabinet is enough. No cloud round-trip in the alarm path.
Survives the restart
Per-agent offsets and checkpointed window state persist — a power cycle doesn't reset your baselines or replay yesterday's alarms.
OT stays inside
Self-hosted means process data never leaves the plant network unless you route it out. LLM stages can run against a local runtime on the same segment.
Honest boundary
"Predictive" means your physics, our plumbing.
StreamFlow doesn't ship a pretrained failure model for your machines — nobody credibly can. What it ships: per-asset statistical baselines (drift, spread, gaps) that catch a large class of degradation out of the box, and a pipeline where your own model — vibration analysis, RUL estimation, whatever your reliability team trusts — slots in as a stage. The alert path, the work-order automation, the audit trail and the replay are the parts you don't have to build.
What it looks like
A condition watch is one file.
Telemetry streams in per asset; baselines are computed in windows; a break opens a work order with context.
1# pulse.yaml — condition watch
2source:
3 kind: webhook # gateway posts telemetry
4
5stages:
6 - name: baseline
7 engine: streaming
8 operators:
9 - window: 15m sliding
10 keyBy: asset_id
11 aggregations:
12 vib_avg: avg(vibration)
13 vib_stddev: stddev(vibration)
14 temp_max: max(temperature)
15
16 - name: detect
17 engine: rule-based
18 rules:
19 - "vib_stddev > baseline_band || temp_max > limit"
20
21 - name: contextualize
22 engine: llm # local runtime on the plant segment
23 systemPrompt: |
24 Summarize the drift for the technician:
25 what moved, how fast, vs. history.
26
27 - name: workorder
28 engine: mcp
29 mcpTools: [ cmms.createWorkOrder ]
30
31sink:
32 kind: webhook # maintenance board
33 url: ${secret:MAINT_BOARD_WEBHOOK}
34- 1
Scaffold.
pulse new condition --source webhook --stage streaming:baseline --stage rule-based:detect --stage llm:contextualize --stage mcp:workorder --sink webhook - 2
Point the gateways at it.
MQTT or HTTP from your edge gateways; file-tail for machine logs; JDBC for MES context.
- 3
Deploy & watch.
pulse deploy . && pulse events tail --topic condition.detect.outEvery baseline break, live.
- 4
Prove the save.
Deterministic replay reconstructs the exact drift behind any work order — evidence for the reliability review.
Hear the machine before it stops.
See telemetry stream into baselines and alerts in minutes — no install, no signup. Then self-host it next to the line.
Pulse is free and self-hosted. Multi-node HA, geo-replication and governance come with StreamFlow Enterprise.