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Manufacturing · head to head

Augury vs Seeq

Augury logo

Augury

Manufacturing

Machine health monitoring sold as a per-machine annual service including sensors, installation and analyst diagnostics

From
On request
Rated
-
Seeq logo

Seeq

Manufacturing

Self-service analytics for process manufacturing time-series data sitting on top of existing historians

From
On request
Rated
-

The short version

  • Each has a real cost: Augury the per-machine annual fee never stops, so over a five to eight year horizon the total exceeds buying sensors and software outright and running the programme yourself.; Seeq named-user pricing suits a small core team but scales badly: a site wanting a hundred engineers with occasional access pays for a hundred licences that mostly sit idle, which is why deployments often stay artificially narrow.
  • They diverge on capability: Augury covers Halo sensors, Seeq covers Query in place.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Augury and Seeq actually diverge.

Attributes where Augury and Seeq differ
AttributeAugurySeeq
PlatformsWeb, iOS, AndroidWeb, Cloud, On-premise, Windows, Linux

Identical on both: starting price (On request), pricing model (quote), free tier (No), user rating (Not yet rated), category (Manufacturing).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Augury

  • Halo sensors
  • Diagnostics as a Service
  • Named fault diagnosis
  • Process Health
  • CMMS integration
  • Installation included
  • Fleet views
  • Unlimited users

Only in Seeq

  • Query in place
  • Capsules
  • Asset trees
  • Seeq Data Lab
  • Organizer
  • Multi-source joins

What people use each for

The jobs each tool is most often brought in to do.

Augury

  • A food plant with 200 similar motors and pumps and no vibration analyst on staffnot Seeq
  • A multi-site manufacturer that needs one reliability picture across plants without standardising their maintenance teamsnot Seeq
  • An operator whose capex budget will not approve sensor hardware but whose opex budget will approve a servicenot Seeq
  • A site trying to move from calendar-based motor overhauls to condition-based intervals with defensible evidencenot Seeq

Seeq

  • A pharmaceutical plant comparing hundreds of batches against a golden batch profile without exporting historian data into spreadsheetsnot Augury
  • A reliability engineer investigating why a compressor trips, needing to overlay vibration, process and maintenance data across two years of historynot Augury
  • Refinery process engineers building a recurring shift report that pulls live values rather than being rebuilt by hand each weeknot Augury
  • A site whose data lake project has stalled and that needs engineers analysing plant history now, without waiting for an ingestion pipelinenot Augury

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Augury

  • The per-machine annual fee never stops, so over a five to eight year horizon the total exceeds buying sensors and software outright and running the programme yourself.
  • Coverage is aimed at standard rotating equipment; reciprocating compressors, very low-speed machinery and non-rotating assets are poorly served, so you still need a second monitoring approach.
  • Diagnoses depend on Augurys analysts, which means the quality of your programme is set by a vendor queue you do not control and turnaround is not something you can escalate internally.
  • The sensors and the analytics are one system, so leaving Augury means removing the hardware and starting again; there is no path to keep the sensors and change the software.
  • Pricing is unpublished and negotiated per fleet, so buyers have no benchmark and comparable plants can pay materially different per-machine rates.

Seeq

  • Named-user pricing suits a small core team but scales badly: a site wanting a hundred engineers with occasional access pays for a hundred licences that mostly sit idle, which is why deployments often stay artificially narrow.
  • Seeq inherits whatever quality exists in the historian, so plants with unstructured tag names and no asset model spend real effort building asset trees in Seeq that should have been fixed upstream.
  • Certain historian connectors are charged separately, so the licence quote and the actual cost of connecting your specific data sources are two different numbers.
  • It is analysis, not control or action; findings still have to be carried into a CMMS or a control change by hand, so value depends on a workflow Seeq does not provide.
  • The product assumes competent process engineers. Organisations without that skill in-house get little from it, because Seeq deliberately does not ship prebuilt failure models the way condition monitoring vendors do.

Pricing, plan by plan

Augury

On request
  • Machine Health$undefined/year
    • Flat annual fee per monitored machine
    • Sensors, gateway, connectivity and installation included
    • Unlimited users and unlimited diagnostic reviews

Seeq

On request
  • Seeq$undefined/year
    • Licensed per named user, not per tag
    • Separate charges for certain historian connectors
    • Cloud-hosted and self-hosted deployments quoted differently

Which should you pick?

Choose Augury if

  • You need halo sensors.
  • You work on Web, iOS, Android.
  • You also want diagnostics as a service.

Choose Seeq if

  • You need query in place.
  • You work on Web, Cloud, On-premise, Windows, Linux.
  • You also want capsules.

Questions people ask

Is Augury or Seeq better?
Neither clearly leads. Augury starts at On request and Seeq at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Augury or Seeq?
Augury starts at On request and Seeq at On request.
Does Augury or Seeq run on more platforms?
Augury runs on Web, iOS, Android. Seeq runs on Web, Cloud, On-premise, Windows, Linux.
What is Augury best used for?
Augury is most often used for a food plant with 200 similar motors and pumps and no vibration analyst on staff, a multi-site manufacturer that needs one reliability picture across plants without standardising their maintenance teams, an operator whose capex budget will not approve sensor hardware but whose opex budget will approve a service, a site trying to move from calendar-based motor overhauls to condition-based intervals with defensible evidence. Of those, a food plant with 200 similar motors and pumps and no vibration analyst on staff and a multi-site manufacturer that needs one reliability picture across plants without standardising their maintenance teams are not what Seeq is typically brought in for.
What can Augury do that Seeq cannot?
Augury covers Halo sensors, Diagnostics as a Service, Named fault diagnosis, Process Health. Seeq covers Query in place, Capsules, Asset trees, Seeq Data Lab.

Answered from the vendors’ own pages

Augury: Do I buy the sensors?

No. Sensors, gateways, connectivity and installation are included in the per-machine annual fee.

Seeq: Does Seeq store my data?

No. It queries connected historians and databases in place. Removing Seeq leaves your data exactly where it was.

Augury: Is there a per-user licence?

No. The web application allows unlimited users; the meter is monitored machines.

Seeq: Who owns Seeq?

It is an independent private company in Seattle, most recently funded by a 2024 growth round led by Sixth Street. It has not been taken over by a private equity buyer.

Augury: Who does the diagnosis?

Machine-learning models flag issues and Augury vibration analysts review them before a finding is released to you.

Seeq: How is it licensed?

Per named user, with some historian connectors charged separately. Nothing is published; every number comes from a quote.

Augury: What happens if we cancel?

The sensors are part of the service and monitoring stops; you do not retain a usable standalone system.

Seeq: Do I need a data scientist?

No, and that is the point. Workbench is aimed at process engineers. Data Lab exists for the minority who want Python.

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