About
Avanzai helps accelerate your financial data analysis by letting you use natural language to output production-ready Python code. Avanzai speeds up financial data analysis for both beginners and experts using plain English. Plot times series data, equity index members, and even stock performance data using natural prompts. Skip the boring parts of financial analysis by leveraging AI to generate code with relevant Python packages already installed. Further edit the code if you wish, once you're ready copy and paste the code into your local environment and get straight to business. Leverage commonly used Python packages for quant analysis such as Pandas, Numpy, etc using plain English. Take financial analysis to the next level, quickly pull fundamental data and calculate the performance of nearly all US stocks. Enhance your investment decisions with accurate and up-to-date information. Avanzai empowers you to write the same Python code that quants use to analyze complex financial data.
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About
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.
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About
The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
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About
Year-to-year comparisons can highlight trends and point up the need for action. Trend ratio analysis works best with VentureLine's five-year accounting ratios married with a common size analysis. With time period to time period in financial analysis, good or poor performance becomes obvious. VentureLine provides cross-sectional financial analysis tools, comparing industry financial ratios to any company or comparing two companies in similar lines of business. Highly recommended by expert analysts is the most effective form of cross-sectional financial analysis: comparing a company's financial ratios and common size percentages to industry ratios and percentages in which the company competes. One way to visually zero in on potential problems and missteps taking place within a business is to prepare and study common size financial statements. Common size financial statements get rid of the dollars and cents, reflecting account balances as percentages only.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Financial professionals and companies seeking an AI copilot for analyzing financial data and output production-ready Python code
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Audience
Component Library solution for DevOps teams
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Audience
Developers interested in a beautiful but advanced programming language
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Audience
Companies searching for a financial analysis solution to manage and improve their operations
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationAvanzai
United States
avanz.ai/
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Company InformationNumPy
numpy.org
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Company InformationPython
Founded: 1991
www.python.org
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Company InformationVentureLine
www.ventureline.com
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Categories |
Categories |
Categories |
Categories |
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Financial Reporting Features
"What If" Scenarios
Audit Trail
Balance Sheet
Cash Management
Consolidation / Roll-Up
Forecasting
General Ledger
Income Statements
Multi-Company
Multi-Department / Project
Profit / Loss Statement
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Integrations
Buffer Editor
Claude Opus 4.5
Figstack
GAMS
GPT-4.1
Granica
IPLocate
Intel Tiber AI Studio
MatchKraft
Mistral OCR
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Integrations
Buffer Editor
Claude Opus 4.5
Figstack
GAMS
GPT-4.1
Granica
IPLocate
Intel Tiber AI Studio
MatchKraft
Mistral OCR
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Integrations
Buffer Editor
Claude Opus 4.5
Figstack
GAMS
GPT-4.1
Granica
IPLocate
Intel Tiber AI Studio
MatchKraft
Mistral OCR
|
Integrations
Buffer Editor
Claude Opus 4.5
Figstack
GAMS
GPT-4.1
Granica
IPLocate
Intel Tiber AI Studio
MatchKraft
Mistral OCR
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