See What Revetorque Can Actually Build
Revetorque turns complex industrial sales logic into working decision tools.
The examples below show how technical inputs, customer operating data, economic assumptions and expert logic can be structured into practical workflows for Sales and their customers.
Different industries. Different decisions. The same principle:
Model the decision first. Build the software second.
Look at the decision logic — not just the interface
A screenshot can show what a tool looks like.
It tells you much less about what the tool actually understands.
For each example, the more useful questions are:
What decision is being supported?
Which inputs matter?
How are those inputs transformed?
Which alternatives are compared?
What does the user receive at the end?
That is where the real complexity sits.
Example 01
On-Site Industrial Gas Generation Economics
Business Case + ROI/TCO
The decision
An industrial customer currently purchases gas from an external supplier.
An alternative is to invest in an on-site generation system.
At first glance, the comparison can look simple:
keep buying gas
vs
buy equipment.
But purchase price alone does not explain the decision.
The economics depend on the customer's actual operating conditions.
What goes into the model?
Depending on the application, relevant inputs can include:
- current gas consumption,
- required purity,
- delivered gas price,
- delivery and transport cost,
- operating hours,
- operating profile,
- compressor power,
- electricity price,
- proposed equipment CAPEX,
- other relevant operating assumptions.
The model uses these inputs to reconstruct the economics of the customer's current supply model and compare them with on-site production.
From technical requirements to operating economics
The logic is not simply:
Equipment price → ROI
It may look more like:
Gas requirement
Required purity and production conditions
Equipment / compressor energy requirement
Electricity consumption
On-site production cost
Comparison with external supply
Investment economics
This keeps the financial result connected to the underlying technical reality.
Compare two different supply models
External supply
The tool can model variables such as:
- purchased gas cost,
- delivery cost,
- consumption,
- recurring supply expenditure.
On-site generation
The alternative scenario can include:
- electricity,
- compressor energy,
- operating cost,
- equipment CAPEX,
- relevant maintenance or operating assumptions.
The tool then places the two scenarios inside one consistent model.
What can the user see?
Depending on the final workflow, outputs can include:
- annual operating cost,
- annual economic difference,
- OPEX per unit of gas,
- cumulative cost over time,
- payback,
- ROI,
- TCO,
- scenario comparison,
- assumptions,
- charts,
- customer-facing PDF summary.
The result is not simply:
“Your payback is X.”
The user can see what drives that result.
The model can change with the customer
If the customer changes:
- gas consumption,
- electricity price,
- operating hours,
- current supply cost,
- purity requirement,
the economics can change with them.
That is important.
The purpose is not to build a calculator that always justifies on-site generation.
It is to evaluate when on-site generation makes economic sense — and when it does not.
Who can use the output?
Sales
To structure the economic discussion around the proposed system.
Customer Champion
To understand the financial difference between alternative supply models.
Finance or Management
To review the assumptions and investment economics as part of a wider decision.
What this tool demonstrates
A single application can connect:
customer data
+
technical requirements
+
operating economics
+
CAPEX
+
ROI / TCO
+
customer-facing output
without separating the financial calculation from the engineering logic that creates it.
Discuss a Similar Business CaseExample 02
Wastewater Pumping-System Modernisation
Business Case + ROI/TCO + Scenario Decision Support
The decision
An operator needs to decide what to do with an existing pumping system.
The decision is not necessarily:
“Which new pump should we buy?”
The real choice may be between several fundamentally different strategies:
Keep the existing system
vs
replace it like-for-like
vs
invest in a more optimised system
vs
combine optimisation with monitoring or control.
Each scenario can carry different:
- CAPEX,
- energy consumption,
- maintenance requirements,
- operating performance,
- lifecycle economics.
That makes the commercial decision much broader than a product comparison.
Start with the existing system
The model can begin with the customer's current operating reality.
Relevant inputs may include:
- pump count,
- pump type,
- rated power,
- operating hours,
- flow,
- head,
- actual or measured energy consumption,
- electricity price,
- maintenance cost,
- downtime information,
- equipment condition,
- proposed investment cost.
Where actual customer data exists, it should take priority over generic assumptions.
Build several scenarios from one baseline
The tool can use the current installation as a baseline and then compare alternative investment paths.
Status Quo
Continue operating the existing system.
No immediate replacement CAPEX, but existing operating and maintenance economics remain.
Like-for-Like Replacement
Replace the equipment without materially changing the system design.
This creates one investment and operating-cost profile.
Optimised System
Model a more efficient solution with different:
- energy consumption,
- operating conditions,
- maintenance assumptions,
- investment cost.
Optimised System + Monitoring / Control
Add another investment layer and evaluate whether the incremental economics justify the additional functionality.
The tool can therefore answer not only:
“Is the new system better?”
but also:
“Which level of investment makes sense under these conditions?”
Separate hard economics from assumptions that require more caution
Not every value driver has the same evidential quality.
Energy consumption and documented maintenance expenditure may provide relatively direct financial inputs.
Downtime can be different.
The operational risk may be important, but converting it into a financial saving requires credible customer-specific data.
A structured model can therefore separate:
Hard financial case
For example:
- energy,
- maintenance,
- lifecycle cost.
from:
Operational or risk-based value
For example:
- downtime exposure,
- monitoring,
- operational visibility,
- other less directly monetised benefits.
This avoids forcing every benefit into an artificially precise ROI figure.
What can the tool calculate?
Depending on the use case:
- annual energy cost,
- maintenance economics,
- hard annual savings,
- simple payback,
- 5-year TCO,
- 7-year TCO,
- 10-year TCO,
- scenario-to-scenario difference,
- incremental upgrade economics,
- cumulative cost.
The financial model can sit alongside the technical assumptions that created it.
Different users may need different outputs
One calculation does not necessarily mean one screen for everyone.
Sales / Sales Engineering
May need:
- customer inputs,
- technical assumptions,
- scenario comparison,
- decision guidance.
Customer / Management
May need:
- concise investment comparison,
- CAPEX,
- annual economics,
- payback,
- TCO,
- key assumptions.
Engineering
May need:
- technical inputs,
- calculation basis,
- assumptions requiring validation,
- unresolved information.
CRM
May need:
- structured opportunity summary,
- selected scenario,
- relevant outputs.
One underlying decision model can support several different downstream outputs.
What this tool demonstrates
A decision tool can move beyond a single calculator and combine:
current-state assessment
technical inputs
multiple investment scenarios
operating economics
ROI / TCO
different outputs for different users
It can help structure a system-modernisation decision rather than merely calculate the payback of one predefined proposal.
Discuss a Similar Modernisation Use CaseDifferent industries. The same decision principles.
Industrial gas generation and wastewater pumping are very different applications.
The tools are different too.
But the underlying principles remain consistent.
Start with the decision
What does the seller or customer actually need to decide?
Use customer-specific data where it matters
Do not hide important variation behind generic averages.
Connect technical performance to economics
The financial output should follow the operational logic.
Keep assumptions visible
Users should be able to understand what drives the result.
Compare realistic alternatives
Including the Status Quo where it matters.
Allow the model to produce an inconvenient answer
The seller's preferred option should not automatically win.
Build the output around the next decision
A useful output should help someone do something next.
Real tools rarely stay inside one category
The labels on the Revetorque Solutions pages describe the primary job of the tool.
They are not product boxes.
A real application may combine several jobs.
For example:
Guided discovery
technical qualification
customer-specific inputs
ROI / TCO
scenario comparison
Business Case output
That can combine elements of:
- Guided Selling,
- ROI & TCO Tools,
- Business Case Tools.
The category comes second.
The decision comes first.
Explore SolutionsYour tool does not need to look like either example
The two examples above start with very different products and customer decisions.
Your use case may involve:
- energy,
- maintenance,
- productivity,
- consumables,
- uptime,
- lifecycle cost,
- technical qualification,
- application selection,
- replacement strategy,
- another repeatable technical-commercial decision.
The important question is not:
“Do you already have a tool exactly like ours?”
It is:
“Can the underlying decision be modelled clearly enough to become a useful tool?”
From working tool to live validation
A working application is only the beginning.
The next step is to put the tool in the hands of actual users and see what happens on real sales opportunities.
That is how the Revetorque Pilot is structured:
Build the working tool
Put it in the hands of selected Champions
Use it on real opportunities
Review the evidence
Decide whether and how broadly to continue
Have a similar decision buried in a spreadsheet, workflow or expert methodology?
Bring us:
- the commercial problem,
- technical inputs,
- existing calculation or methodology,
- alternatives being compared,
- assumptions,
- and the output Sales or the customer needs.
It does not need to match either example.
We first understand the decision.
Then we determine what kind of tool should be built around it.
Discuss a Similar Use Case
Tell us what your team currently calculates, compares or explains manually.
Discuss a Similar Use Case