Software Alternatives, Accelerators & Startups

Juro VS NumPy

Compare Juro VS NumPy and see what are their differences

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Juro logo Juro

Juro is a contract automation platform that enables your team to create, execute and monitor routine contracts at scale without ever leaving the browser.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Juro Landing page
    Landing page //
    2023-08-26

Juro is a contract automation platform that empowers your team to create, execute and monitor routine contracts at scale without ever leaving the browser. We work with rapidly-scaling businesses like Deliveroo, Babylon Health and SecretEscapes to streamline contract workflow and gain better insight into contract data. Juro is backed by Union Square Ventures, Point Nine Capital, Seedcamp and founders of TransferWise, Gumtree and Indeed.

  • NumPy Landing page
    Landing page //
    2023-05-13

Juro

Website
juro.com
$ Details
freemium $450.0 / Monthly (Includes 500 contracts and minimum 5 users)
Platforms
Chrome OS Windows iOS Android
Release Date
2016 December

Juro features and specs

  • User-friendly Interface
    Juro offers a highly intuitive and easy-to-navigate interface, making it simple for users to manage contracts without extensive training.
  • Automated Workflows
    Juro's automated workflows streamline the contract lifecycle, reducing manual tasks and minimizing errors, leading to faster contract processing times.
  • Real-time Collaboration
    The platform supports real-time collaboration, allowing multiple stakeholders to work on and review contracts simultaneously, improving efficiency and communication.
  • Integrations
    Juro integrates seamlessly with various third-party applications like Salesforce, HubSpot, and Slack, enhancing its functionality and providing a unified work environment.
  • Customizable Templates
    Users can create and save customizable contract templates, ensuring consistency and compliance while saving time on drafting repetitive documents.
  • Secure Storage
    Contracts are stored securely in Juro, with encryption and other security measures in place to protect sensitive information.

Possible disadvantages of Juro

  • Limited Customization
    While Juro offers customizable templates, some users may find the level of customization for workflows and user interfaces limited compared to other platforms.
  • Pricing
    The pricing model of Juro might be on the higher side for small businesses or startups, making it less accessible for organizations with limited budgets.
  • Learning Curve
    Despite its user-friendly interface, some users may still experience a learning curve, especially if they are migrating from another contract management system.
  • Feature Limitations
    Certain advanced features, such as complex reporting and analytics, might not be as robust as those offered by other high-end contract management solutions.
  • Dependence on Internet
    Since Juro is a cloud-based solution, users are dependent on a stable internet connection to access and manage contracts, which can be a limitation in areas with poor connectivity.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Analysis of Juro

Overall verdict

  • Yes, Juro is generally considered a good platform for contract management.

Why this product is good

  • Juro offers an intuitive interface and robust features that streamline the contract lifecycle. Users appreciate its ability to automate contract creation, negotiation, and approvals, saving time and reducing errors. The platform also provides seamless integrations with other tools, enhancing workflow efficiency.

Recommended for

  • Small to medium-sized businesses looking to streamline their contract processes
  • Legal teams that want to automate routine tasks and focus on strategic work
  • Teams who need a collaborative environment for drafting and negotiating contracts

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Juro videos

Juro | Contract collaboration your whole team will love.

More videos:

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NumPy videos

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Juro and NumPy)
Contract Management
100 100%
0% 0
Data Science And Machine Learning
Document Automation
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Juro and NumPy

Juro Reviews

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NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 119 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Juro mentions (0)

We have not tracked any mentions of Juro yet. Tracking of Juro recommendations started around Mar 2021.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 5 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing Juro and NumPy, you can also consider the following products

CobbleStone Software - Managing contracts just got easier with CobbleStone!

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

IronClad - Ironclad is an automated assistant that manages legal paperwork for your company.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Conga Contracts - Conga Contracts is management solution designed to accelerate and simplify contract negotiations in Salesforce.

OpenCV - OpenCV is the world's biggest computer vision library