Train AI with accounting data

ACCT
Efficiently train data models using accounting data

1. Authentication and connection

Your users authorize your application to access their accounting platform by going through an authorization flow using Merge Link.

2. Data retrevial from accounting platform

Utilize Merge's API endpoints, such as GET /balance-sheets, GET /cash-flow-statements and GET /invoices, to retrieve comprehensive accounting data.

3. Data pre-processing

  • Clean the data by removing duplicates in your customer data, handling missing values, and filtering out irrelevant fields.
  • Transform data into a format suitable for AI training, possibly involving normalization, encoding, or feature engineering.

4. Model training

Validate the model's performance using the testing set. Compute relevant metrics to gauge the model's effectiveness.

5. Feedback loop

Continuously monitor accounting data for updates, changes, and new information. Implement a feedback loop for model retraining and improvement to adapt.

6. Surface accounting insights

Build a UI to provide your customers with valuable insights generated by the AI models, such as forecasts on cash flow, recommendations for cost optimization, or identification of potential financial risks.

Get started in automatically pulling accounting data to train AI with Merge

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Key models & fields
type
number
accounting_period
company
status
total_amount
tracking_categories
line_items
income
cost_of_sales
gross_profit
operating_expenses
net_operating_income
non_operating_expenses
net_income
cash_at_beginning_of_period
cash_at_end_of_period
operating_activities
inveting_activities
financing_activities
assets
liabilites
equity
Typical sync frequency
Highest
Industries
Artificial Intelligence (AI) Software
Revenue Intelligence
Financial Planning and Analysis (FP&A)