EXPLAINABLE PREDICTIVE MAINTENANCE

A Python edge agent reads your existing PLCs and historians over OPC UA, Modbus TCP, CSV file watch, or JSON file watch. Three deterministic anomaly detectors score every machine with a published formula, and a multi-tenant audit chain keeps every action traceable for seven years.

01

Edge agent on your network

The Python edge agent runs on any Linux box next to your machines. Configure each ingest source over OPC UA, Modbus TCP, CSV file watch, or JSON file watch. Telemetry is buffered locally in SQLite, so the agent keeps collecting even if the WAN drops for days and auto-flushes when connectivity returns. No new sensors, no proprietary hardware.

02

Works through WAN outages

The edge agent keeps a local SQLite buffer. Telemetry continues to be collected through outages that last days or weeks. When connectivity returns, buffered readings auto-flush to the cloud in order, and a schema-version check clears stale data after upgrades so silent corruption is not possible.

03

Deterministic anomaly detection

Three independent detectors run in parallel against every reading: a z-score against a rolling baseline, an EWMA that adapts to gradual drift, and a rate-of-change check that catches velocity anomalies even when the absolute value is still in range. The 0 to 100 health score follows a published deduction table, not a black-box model, so every score traces back to specific events.

04

CMMS workflow and ten notification channels

Anomalies above threshold can open a CMMS work order in the same platform, with parts pulled from inventory, an assigned operator, and a digitally signed completion record. Ten outbound notification channels keep the rest of your stack in the loop: Webhook, Email, Slack, SMS, Microsoft Teams, PagerDuty, Opsgenie, Telegram, ServiceNow, and Jira.

BUILT TO SCALE

From a 10-machine pilot to a 10,000-machine fleet

Every number here is the actual platform capability you can put into a contract. No marketing approximations, no asterisks, no "results may vary".

4 Input protocols (OPC UA, Modbus TCP, CSV, JSON)
3 Deterministic anomaly detectors
10 Outbound notification channels
5 UI languages out of the box
3 ERP adapters (SAP, Oracle, Dynamics)
7 years HMAC-SHA256 audit chain retention
10,000 Machines per tenant at full scale
< 100 ms WebSocket push from sensor to browser
05

Sub-100 ms real-time fleet view

Per-tenant WebSocket channels push readings to the browser in under 100 ms from sensor to screen. JWT-authenticated, scoped to your tenant, with connection caps that keep a noisy neighbour from impacting your fleet.

06

Tamper-evident audit grade

Every audit log row carries a monotonic sequence number and an HMAC-SHA256 hash chained to the previous row. Append-only database triggers block deletes without an explicit retention flag. PostgreSQL Row-Level Security pins every query to the current tenant, and the audit chain is retained for seven years to support SOC 2 CC2.2 and CC4.1.

07

Predictable per-machine billing

Per-machine pricing tailored to your fleet size. Paddle is the merchant of record so VAT and sales tax are handled in every country. Request a quote for the figure that applies to your deployment.

08

International from day one

Five UI languages out of the box: English, German, Spanish, Hungarian, and Chinese. Country names are localised at render time, app-level SSO with Google and Microsoft uses OAuth 2.0 with PKCE, and tenant-level SAML or OIDC connects to your corporate identity provider. US-hosted by default.

STOP REACTING. START PREDICTING.

Connect Haltless to your existing PLCs, validate the explainable health score on your own equipment, and we come back with a tailored quote. No new hardware, no proprietary sensors, no consultants.

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