The market value of the product.
We will want to conduct a SWOT (strengths, weaknesses, opportunities,
and threats) analysis as part of the business plan.
However, the concept here is to use descriptive, predictive, and
prescriptive analytics to describe the likelihood of possible simulated
outcomes. The software will then recommend a certain course of action, within a
specific confidence interval (i.e., the probability of success as a
percentage).
The input of system parameters will be done in an automated way or
by means of a questionnaire, which could be generated dynamically (e.g. this
can be done using a large language model). For MVP, simulations and analyses
can be performed initially through existing generative AI applications. These
will be gradually replaced by proprietary components later.
The revenue model of the product.
A low-cost generic version will be available to the general
public. The generic version will cost around 100 US dollars and will be
accessible to anyone.
Custom versions will be designed for specific commercial and
professional uses. Subscriptions to custom versions will be priced for
businesses of various sizes, from hundreds to thousands of dollars, depending
on the complexity of the processes being simulated.
Subscriptions are usually annual and are updated automatically.
However, a one-time purchase should also be an option, as not everyone needs or
wants upgrades.
The competition
There are currently no real direct competitors for this product.
There are very expensive risk management systems available to corporations for
specialized needs, such as finance and banking. However, there is nothing on
the market that is as flexible or reasonably priced as this product.
Therefore, Simulation Magic should create a new global niche
market, as there is no equivalent. This is possible because the original system
architect has the breadth of knowledge and experience to greatly simplify an
otherwise complex set of interactions.
Thus, what seems complex for a specialized team can be simplified
by a person with diverse knowledge in engineering, software development,
finance, etc.
Flexibility of use
The flexibility of the system allows it to be used for virtually
any process that has a certain input and output (e.g., manufacturing, finance,
chemical processes, diagnostics, etc.). In addition, the data entry itself can
be automated, making the system independent of any manual intervention.
System components will be deployed as microservices, hosted in
virtual containers (e.g., Docker). Instances of the various microservices will
be automatically created/destroyed as needed, using an integrated container
management system, such as Kubernetes.
DevOps specialists will need to regularly configure and adjust
this container management program.