AINetProfit® Manual
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Introduction
We decided to create an EASY-TO-USE accounting application takes full advantage of what AI and Neural Networks can do for any business large or small.
Modern Web-Based Companies
Don't Use Accounts Payable or Receivable
Companies selling products on platforms like Amazon or their own websites do NOT need traditional Accounts Payable (AP) or Accounts Receivable (AR) . Here's why:
✅ Why Traditional AP/AR Aren't Needed
1. They Don't Sell on Credit (No AR Needed)
- Traditional AR tracks invoices where customers pay later (e.g., Net 30 terms).
- Web businesses get paid instantly via credit cards, PayPal, Amazon, etc.
- There's no need to manage invoices or collections — sales are immediate.
2. They Don't Receive Invoices from Suppliers (No AP Needed)
- Many expenses are prepaid: ads, manufacturing, shipping, etc.
- No vendor bills to track — just record the payment as an expense.
✅ What These Companies Need Instead
Instead of AP/AR, modern businesses need tools to track and PREDICT advertising performance and sales attribution which we will be adding over time in the development of this application .
Table Name | Description |
---|---|
Predictions | Calculate which ads to buy and the maximum to spend on each ad to achieve a net profit on each buy by calculating the probabily of turning a net profit on each potential ad buy BEFORE you buy that ad! |
AdSources | Tracks ad campaigns by source (e.g., Google, Amazon, Facebook) |
AdExpenses | How much was spent on each ad or campaign |
SalesAttribution | Sales generated by each ad or campaign |
Payouts | When Amazon, Stripe, etc. paid the business and how much |
ROIPerAd | Calculated metrics like gross profit and return on ad spend (ROAS) |
⚙️ Summary
For modern e-commerce sellers, cash-based accounting and ad performance tracking are far more useful and what our accounting app is focused on, namely, helping YOU to make more PROFIT.
This app is for modern e-commerce sellers who need reports to file their taxes which we included and features to help market their products.
Why SaaS Is Very Bad for Consumers
We Sell AINetProfit® with A One-Time Flat Fee
Our one-time flat fee allows users to own their copy, providing greater control, cost savings, and alleviating risks and problems associated with the SaaS model. READ THIS: Forbes Article
SaaS (Software as a Service) is way of delivering software over the internet where users are forced to pay a subscription fee to access the software, instead of buying and owning the software. The software runs on the provider's servers and is accessed through a web browser.
In our opinion, SaaS presents serious drawbacks for consumers:
- Recurring Costs: SaaS models often involve ongoing subscription fees which means that consumers NEVER STOP PAYING for the use of the software.
- Data Privacy Concerns: Storing data on external servers in the cloud managed by third-party providers can raise issues regarding data security and privacy, especially if the provider experiences breaches or mishandles data. NEVER PUT YOUR FINANCIAL DATA ON THE CLOUD !!!
- Dependence on Internet Connectivity: Accessing SaaS applications requires a stable internet connection. Service disruptions or limited connectivity can hinder access to essential tools and data.
- Limited Control and Customization: Consumers may have restricted ability to modify or customize SaaS applications to fit their specific needs, as they do not own the software.
- Vendor Lock-In: Migrating from one SaaS provider to another can be challenging due to data portability issues and compatibility concerns, potentially limiting consumer choices.
Custom Categories
AINetProfit® gives you total control over how your finances are categorized—with support for both predefined and fully custom IRS categories that reflect the real-world structure of your business. Whether you're a sole proprietor, LLC, or corporation, you can tailor your categories to match exactly how you operate.

Every taxable category in AINetProfit® can be linked directly to an official IRS tax line using our exclusive Tax Line Mapping system. This allows you to generate tax-ready reports instantly, giving your accountant clean, organized data mapped to Schedule C and other forms. It's an incredible time-saver that reduces audit risk and improves year-end tax accuracy.
Our default category library includes dozens of intelligently curated IRS-compliant options to get you started fast— all pre-mapped to real tax return lines. And unlike other software, you're not stuck with our definitions. You can edit, expand, or create entirely new categories that reflect your unique workflows and assign them to the correct tax lines with a few clicks.
This isn't just customization. It's compliance made simple. With AINetProfit®, your categories are more than just labels—they're deeply integrated with your AI engine, rules system, and financial reports to help you stay organized and audit-ready.
Why User-Defined Categories Matter
Every business is unique—and so are its expenses. That's why AINetProfit® empowers users to create their own custom categories in addition to our pre-defined set. Whether you run a design studio or sell niche products online, you can tailor your categories to match how your business actually operates.
These categories are more than labels—they drive the way your financial reports are generated, summarized, and filed. By letting users define their own
CategoryType
and GroupType
, the system can adapt to virtually any accounting structure, while still ensuring your data remains
organized and compliant.
IRS Tax Reporting Integration
For categories that are tax-related, we've gone one step further. Each category can be mapped to a specific line on IRS tax forms using the
TaxLineMapping
field. This allows your categorized totals to be automatically aligned with the correct fields on forms such as
Schedule C, 1120, or 1065, streamlining the process of tax preparation.
For example, a category labeled "Office Supplies" might be mapped to Schedule C, Line 18
. When reports are generated, AINetProfit®
calculates totals per category and displays them in the correct order, making it simple to copy the values—or export them—directly into your tax software or forms.
With our category system, you get the perfect blend of flexibility and compliance. Every category you define helps drive
smarter automation, clearer reporting, and faster tax filing. It's not just accounting—it's accounting with foresight.
And yes, the IRS would be impressed.
Pro Feature: Combine custom categories with our Category Rules Engine to auto-assign them based on transaction patterns.
ML.NET and Bayesian optimization fill in the gaps, while your custom structure stays intact—ensuring total flexibility without sacrificing automation.
Databases - Where We Store YOUR Data
AINetProfit® uses the lightweight yet powerful SQLite database engine to securely store all your financial data directly on your own computer. We believe your accounting information should remain private and in your control — not uploaded to the cloud or stored on someone else’s servers.
SQLite is a trusted, high-performance database engine used by major tech companies around the world, including Apple, Google, and Microsoft. It’s fast, reliable, and fully embedded, which means there’s no need to install or manage any external database systems — everything works seamlessly out of the box.
Note: AINetProfit® supports optional file encryption, automatic versioned backups, and full offline performance , so your data is always secure, recoverable, and accessible — even without an internet connection.
Our AI Trained Models
AINetProfit® leverages the power of Microsoft’s cutting-edge ML.NET framework to build and train advanced neural networks directly within the application. This allows our AI engine to continuously learn from real-world accounting patterns, optimizing decisions and enhancing accuracy over time — all without requiring an internet connection.
How Our AI-Powered Categorization Works
The system uses an AI-trained model that was built using historical transaction data. First, the training data is read from a file using
CategoryRulesLoader
, which loads known examples of descriptions, transaction types, and the correct categories.
This data feeds into a machine learning model that learns how to recognize patterns and make predictions.
Once trained, the AI model is loaded by CategoryPredictor
, which takes a new transaction description and type,
and returns the most likely category. The CategoryPredictionModel
plays a key role in converting input data into usable
predictions by referencing the trained patterns. It effectively mimics the way a human might recognize familiar keywords in descriptions to decide
how to classify each transaction. The result is a smart categorization tool that simplifies bookkeeping
by reducing the need for manual entry.
We use real Bayesian Optimization through Microsoft's official ML.NET AutoML
engine, which applies
sequential model-based optimization (SMBO) to intelligently explore and fine-tune hyperparameters such as learning rate,
tree depth, and feature encoding strategies. By combining this with our custom-built
Business Rules Engine, AINetProfit® intelligently balances predictive modeling with deterministic logic,
ensuring reliable performance and actionable insights you can trust. The result? A smarter accounting platform that gets better every time you use it.
Rules Engines
AINetProfit® leverages the power of Microsoft’s cutting-edge ML.NET framework to build and train advanced neural networks directly within the application. This allows our AI engine to continuously learn from real-world accounting patterns, optimizing decisions and enhancing accuracy over time — all without requiring an internet connection.
How Our AI and Rules Engine Work Together
ML.NET requires a certain amount of quality training data to deliver accurate results. However, in the early stages—when imported transactions are limited— AINetProfit® compensates using a built-in Category Rules Engine embedded directly within the trained model logic. This hybrid design ensures reliable categorization even with sparse data, allowing users to benefit from intelligent automation right from the start.
Our Rules Engine acts as a set of intelligent overrides based on known transaction patterns, keywords, and user-defined logic. And uniquely, we allow users to contribute their own rule definitions—but only within the Category Rules Engine. This ensures accuracy is preserved while enabling powerful customization where it matters most.
By combining AI-driven predictions with user-contributed heuristics, the system delivers the best of both worlds: the adaptability of machine learning with the transparency and precision of deterministic logic.
Behind the scenes, our architecture uses Microsoft’s AutoML
and Bayesian Optimization
to continuously enhance model performance
while referencing your personalized rules when training data is insufficient. This fusion of structured logic and probabilistic intelligence
is what sets AINetProfit® apart—a system built to grow with you, adapt to your workflows, and deliver actionable insights you can count on.
Why We Only Support American Banks
While there isn't a widespread consensus advocating that companies should exclusively use American banks, several practical and regulatory factors often lead businesses operating in the U.S. to prefer domestic banking institutions.
Regulatory and Operational Considerations
For companies conducting business in the United States—especially those involved in processing U.S. payroll, managing taxes, or seeking federal programs—having a U.S.-based bank account is often essential. The U.S. Department of Commerce notes that nearly all U.S. payroll providers require a U.S. bank account to process payroll. Additionally, certain federal programs mandate that a company maintain a U.S. bank account for a specified period to be eligible for assistance. [Source: trade.gov]
Accounting and Compliance Benefits
Utilizing American banks can simplify accounting processes, ensure compliance with U.S. financial regulations, and facilitate smoother interactions with domestic financial systems. This is particularly relevant for businesses that rely on U.S. accounting standards and need to align with local financial practices.
Our Conclusion
While there's no explicit directive for companies to use only American banks, the combination of regulatory requirements, operational efficiencies, and compliance considerations often make U.S. banks the practical choice for businesses operating within the United States.
Why We Don't Use Double Entry Bookkeeping
In today's rapidly evolving financial landscape, the traditional double-entry bookkeeping system is increasingly viewed as outdated. Modern accounting software automates transaction recording and real-time financial analysis, rendering the manual, dual-entry process redundant and useless. The double-entry system's complexity demands specialized training and is time-consuming, making it impractical for small businesses with limited resources and of NO value for larger companies. Moreover, its rigid structure can hinder adaptability in dynamic markets. Some critics argue that the persistence of double-entry bookkeeping ONLY benefits accountants and NOT businesses, where it perpetuates a reliance on professional services for tasks that could be simplified through technology. This perspective implies that the system's continued use may serve the interests of the accounting profession over those of business efficiency.
🔥 Our Custom Reports
We built our own Modern Reports Engine without using any unnecessary components like RDLC, Crystal Reports, Telerik, or DevExpress. Our reports are elegant, lightweight, and total control is in the user's hands.

- ✅ Interactive sorting, filtering, pagination
- ✅ Instant Excel, CSV, PDF, Print exports
- ✅ Fully stylable with CSS + Bootstrap
- ✅ 100% local, secure, and lightning fast
- ✅ Can easily add charts, drilldowns, tabs, anything web-based
- ✅ Add column visibility toggles with:
buttons: ['colvis']
- ✅ Add footer totals
- ✅ Add multi-level group headers
- ✅ Add custom filters by category, payee, amount
- ✅ Embed Chart.js or Google Charts to visualize totals
💡 We've Included The Standard Accounting Reports:
-
✅ Expense by Category
-
✅ Income by Category
-
✅ Profit and Loss Statement
-
✅ Uncategorized Transactions
-
✅ Tax Summary
-
✅ Etc.
💡 A Few Charts We're Adding Powered by AI:
-
📈 Expense Forecast Chart
Time series forecasting usingForecastingBySsa
.
Chart.js: Line chart showing actual vs predicted future expenses per category.
Table Input: Transactions (Date, Amount, Category)
// Forecast next 6 months of expenses var forecast = model.Predict(transactions);
-
📊 Spending Pattern Clusters
Use K-Means clustering to group similar spending behaviors (e.g. heavy weekend spenders, recurring bill payers).
Chart.js: Radar or Bubble chart showing cluster centers.
Table Input: Transactions grouped by day, time, category, etc. -
💰 Anomaly Detection in Transactions
Use anomaly detection withRandomizedPca
orIidSpikeDetector
.
Chart.js: Highlight anomalous spikes/dips in spending.
Table Input: Date, Amount, Category. -
📉 Credit Risk or Cash Flow Classification
Binary classification model predicting “low cash risk” vs “high cash risk” in upcoming weeks based on account balances + upcoming bills.
Chart.js: Gauge or pie chart showing current risk state.
Table Input: Accounts, Transactions, DueDates. -
🧠 Smart Recommendations (AI-powered Insights)
Custom model to suggest:- Items that might trigger an IRS Audit
- Categories being overused
- Potential subscriptions to cancel
- Vendors with increasing prices
-
📊 Net Profit Prediction
Regression model to predict monthly profit based on past trends.
Chart.js: Dual-axis line chart for predicted vs actual net profit over time.
Input: P&L reports aggregated by month. -
🔁 Recurring Transaction Identification
Sequence analysis or classification to detect transactions that repeat monthly.
Chart.js: Timeline chart showing recurring expenses.
Input Table: Transactions with date/amount/payee.
What Is A Company?
The first screen you will see after our cool-looking splash screens is the "Company" screen below where you create your taxable entities. Each Company has it's own, unique database.

A company, from a tax perspective, is a distinct taxable entity recognized
by the government. It can take the form of a formal business structure like a
corporation (Inc. or Corp), a limited liability company (LLC),
a "doing business as" (DBA), or even an individual operating as a sole proprietor.
Regardless of form, any entity that earns income and engages in commerce is subject
to taxation. Like individuals, these entities must report income, deduct expenses,
and pay taxes according to federal, state, and local tax laws. The key point is that
the IRS treats all income-generating entities—whether businesses or individuals—as
taxable entities.
This is where our AI Neural Network really helps to make importing financial statements easy.

Using AI to map IRS tax categories to imported financial data helps automate one of the most tedious and error-prone tasks in accounting. By analyzing descriptions, amounts, and transaction patterns, AI can accurately assign the correct IRS categories such as "Office Expenses," "Advertising," or "Meals & Entertainment"—saving time, reducing manual errors, and ensuring compliance with tax reporting requirements.
Transactions Screen
This is where our AI Neural Network really helps to manage your tranactions.


The Transactions Screen uses AI to automatically match IRS tax categories to your imported financial data. By analyzing transaction descriptions, amounts, and patterns, the system intelligently classifies expenses into categories like “Advertising,” “Office Expenses,” or “Meals & Entertainment.” This dramatically reduces manual effort, eliminates common errors, and helps ensure accurate, compliant tax reporting.