Engagement & pricing

Our Engagement and Pricing Models

Coherence Systems works with teams that need to understand dynamic physical and digital systems from noisy, changing data. Because each environment has different data access, integration depth, security needs, and deployment constraints, we scope work before quoting ongoing agreements.

Most engagements begin with a focused initial phase, then move into an annual service agreement when continued software access, monitoring, support, refinement, or deployment assistance is needed.

See how we work

One engagement model

How engagements usually work

The same four steps run under every entry point, from a first conversation to broader deployment.

  1. 01

    Scope the system

    We clarify the system, data streams, goals, constraints, and success criteria.

  2. 02

    Build the first evidence workflow

    We define views, windows, channels, comparison rules, benchmarks, and reviewable outputs.

  3. 03

    Review results

    We evaluate whether the workflow produces useful evidence for your system.

  4. 04

    Continue or expand

    Move into an annual service agreement for ongoing access, support, monitoring, refinement, and broader deployment.

Five entry points, one model

Choose your starting point

Every engagement runs on the same model. These are five ways in, based on where your team is today. Pilot Software Deployment is the most common place to start.

Start here · flagship

Pilot Software Deployment

For teams that want to evaluate Coherence Atlas against real or simulated data.

What it covers

A scoped pilot that stands up a working review workflow using real or simulated data. It covers declared views, comparison rules, benchmark setup, review records, and a final readout against agreed success criteria, so your team can evaluate fit in context.

Initial scope

  • Pilot scoping and success criteria
  • Real or simulated data setup
  • Declared views, windows, and channels
  • Benchmark and review workflow
  • Monitoring outputs
  • Reviewable evidence records
  • Final pilot readout

Ongoing path

  • Continued software access
  • Monitoring and support
  • Refinement
  • Pilot expansion

Data Science Services

For teams that need a clearer read on existing data before building a monitoring workflow.

What it covers

Applied data science for teams working with many changing data streams. It covers data review, feature design, model evaluation, drift analysis, and documented reporting for a clearer, reviewable read before committing to a larger deployment.

Initial scope

  • Data review and problem scoping
  • Feature design
  • Model evaluation
  • System, data and signal analysis
  • Documented workflow
  • Reviewable findings report
  • Next step recommendations

Ongoing path

  • Recurring analysis
  • Model review
  • Workflow refinement
  • Advisory support

Custom Signal Systems

For teams with many streams, sensors, logs, or telemetry sources that need a tailored workflow.

What it covers

Bespoke signal pipelines for teams working across multiple streams, sensors, logs, or telemetry sources. It covers alignment, windowing, comparison logic, persistence review, drift review, and integration planning shaped around your own systems and vocabulary.

Initial scope

  • Multi stream pipeline design
  • Channel alignment
  • Windowing logic
  • Custom comparison rules
  • System state review
  • Review records
  • Integration planning

Ongoing path

  • Ongoing operation
  • Refinement and monitoring
  • Expanded integrations
  • Persistence, drift, and transition review

Managed MLOps Support

For teams already running models or monitoring pipelines that need clearer operating context and review records.

What it covers

Operational support can cover model and signal monitoring, drift and degradation review, issue triage, and reporting, with operating context retained for later review.

Initial scope

  • Model and signal monitoring
  • Drift and degradation review
  • Documented review records
  • Operating context
  • Monitoring reports
  • Issue review

Ongoing path

  • Continuous monitoring support
  • Change review
  • Operating context
  • Recurring recommendations

Cloud Architecture Design

For teams planning infrastructure for signal processing, storage, and reviewable records.

What it covers

Architecture design for monitoring workflows that span local systems, cloud infrastructure, storage, and reviewable records. Best for teams that need a clear technical plan before building or scaling their own pipeline.

Initial scope

  • Edge to cloud architecture design
  • Data flow mapping
  • Batch and real time workflow planning
  • Storage and review-history design
  • Separation of compute and review layers
  • Scale planning
  • Implementation roadmap

Ongoing path

  • Architecture review
  • Implementation support
  • Deployment planning
  • Scaling support

Pricing

How pricing is determined

Pricing is quoted after discovery. Cost depends on data access, number of systems, integration depth, security requirements, support needs, deployment scope, timeline, and whether the work involves research analysis, pilot deployment, ongoing monitoring, or broader infrastructure support.

Initial phases are scoped and limited. Ongoing software access, monitoring, support, refinement, implementation help, and annual service agreements are quoted separately.

Academic & research

Academic and research pricing

Academic, nonprofit, and research collaboration pricing is available by request. Research engagements are scoped around study goals, data access, publication needs, support requirements, privacy constraints, and institutional review requirements.

What you get

What customers receive

  • A clear scope
  • Documented assumptions
  • Reviewable outputs
  • Documented workflows
  • A record of what was evaluated

The goal is to make system behavior easier to understand, explain, and build on.

Next step

Start a scoped conversation

Tell us about your system, data environment, and the kind of evidence or monitoring workflow you need.

Email directly