Software Alternatives, Accelerators & Startups

NumPy VS Theysaid

Compare NumPy VS Theysaid and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Theysaid logo Theysaid

Conversational AI surveys, interviews, user tests, polls
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Theysaid TheySaid
    TheySaid //
    2025-09-08

TheySaid - The everything app for feedback, powered by AI and voice to gather, analyze, and act on feedback. Conduct interviews, user tests, surveys, polls, and funnel results into a single dashboard or your database via integrations.

Popular use cases include onboarding, customer + employee experience, lost sales deals, product research, and more!

Theysaid

$ Details
Free Trial $49.0 / Monthly ("Essential" "1 seat license" "1 Active AI project")
Startup details
Country
United States
State
Utah
City
Lehi
Founder(s)
Chris Hicken, Lihong Hicken, Amy Long, Arnab K
Employees
20 - 49

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.

Theysaid features and specs

  • AI Surveys
    Conversational AI surveys that dig deeper to uncover the why behind every answer.
  • AI Interviews
    AI conducts adaptive interviews, asking smarter questions and adjusting in real time to uncover deeper insights.
  • 2-way voice
    Users speak to AI and complete their form with voice while AI reads questions aloud.
  • Usability Testing
    Ask users to do tasks, visit websites or prototypes, and get voice and video recordings.
  • AI Sidebar
    AI tells you what you've learned recently, suggests new projects, and answers questions.
  • AI Forms
    Now forms are beautiful with an optional AI assist mode to help users quickly fill out forms.
  • Conditional Logic
    Simple, intuitive branching logic still allows AI to ask follow-up questions.
  • Panel Recruiting
    Recruit feedback participants from our panel integrations, or bring your own panel.
  • Teach AI
    Give AI context about your company, pricing, and product by uploading any document.
  • Integrations
    Full-featured connectors with HubSpot, Salesforce, Slack, and more.
  • Free survey creator
    On the website, you can create or brainstorm your next project and then add it to your account.
  • Import surveys
    Import surveys from your ancient survey tools like Qualtrics, SurveyMonkey, or Typeform.
  • Templates
    The best templates for popular feedback types are available with one click.

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.

Analysis of Theysaid

Overall verdict

  • TheySaid (theysaid.io) is a solid AI-powered survey and feedback platform that uses conversational, interactive surveys to gather deeper customer insights than traditional static forms, making it a good choice for teams focused on customer experience and product feedback.

Why this product is good

  • Uses AI-driven conversational surveys that feel more like a dialogue, encouraging higher response rates and richer qualitative feedback
  • Automatically follows up on responses to dig deeper into customer sentiment without manual effort
  • Provides AI-generated summaries and actionable insights, saving teams time in analyzing feedback
  • Easy to set up and deploy surveys across multiple touchpoints such as websites, emails, and products
  • Helps uncover the 'why' behind customer opinions rather than just collecting surface-level ratings

Recommended for

  • Product teams seeking qualitative user feedback to guide roadmap decisions
  • Customer success and experience teams measuring satisfaction and reducing churn
  • SaaS companies wanting to gather in-app feedback conversationally
  • Marketing teams looking for deeper audience insights beyond standard surveys
  • Small to mid-sized businesses that want AI-assisted feedback analysis without heavy manual work

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

Theysaid videos

TheySaid 3.0 Review โ€“ AI Customer Feedback Analysis & Voice-of-Customer Platform (2025)

More videos:

  • Review - Customer Survey Tool product review | Theysaid AI

Category Popularity

0-100% (relative to NumPy and Theysaid)
Data Science And Machine Learning
Customer Feedback
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Surveys
0 0%
100% 100

Questions & Answers

As answered by people managing NumPy and Theysaid.

What makes your product unique?

Theysaid's answer:

Most surveys are dull and only scratch the surface. TheySaid turns surveys into conversations, asking real-time follow-ups, revealing the why behind every answer. This gives revenue leaders sharper visibility into customer needs, fueling faster, more confident business decisions that drive growth.

Why should a person choose your product over its competitors?

Theysaid's answer:

Most survey tools stop at collecting answers, giving leaders surface-level data thatโ€™s hard to act on. TheySaid turns feedback into real conversations with smart follow-ups, capturing the why behind customer behavior. This means revenue leaders donโ€™t just get data, they get clear action items: what to improve, where to double down, and how to reduce churn. And with insights delivered 10x faster, they can act quickly to capture growth opportunities and make confident business decisions.

How would you describe the primary audience of your product?

Theysaid's answer:

TheySaid is built for B2B leaders who rely on customer insights to drive growth. Our primary audience includes Customer Success teams, Revenue leaders, Product managers, and Marketing executives at SaaS and subscription-based businesses. They use TheySaid to uncover authentic customer sentiment, strengthen retention, and identify expansion opportunities.

What's the story behind your product?

Theysaid's answer:

Surveys were dead. Customers ignored them, response rates tanked, and leaders were left making decisions on scraps of data. Lihong Hicken and Chris Hicken saw the gap and built TheySaid, the first AI-powered conversational survey that actually listens. With AI interviews, live polls, and user testing alongside surveys, TheySaid captures the why behind every answer and instantly translates insights into clear action items. For revenue leaders, that means faster decisions, smarter growth moves, and insights delivered 10x quicker than any traditional tool.

Which are the primary technologies used for building your product?

Theysaid's answer:

TheySaid leverages advanced AI (natural language processing, machine learning, and generative AI), cloud infrastructure, and secure integrations with popular CRM and HR systems to deliver fast, scalable, and reliable insights.

User comments

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Reviews

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

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

Theysaid Reviews

We have no reviews of Theysaid yet.
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Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 122 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.

NumPy mentions (122)

View more

Theysaid mentions (0)

We have not tracked any mentions of Theysaid yet. Tracking of Theysaid recommendations started around Aug 2024.

What are some alternatives?

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

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

Survicate - Collect feedback on your website and find out more about your visitors.

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

Dovetail - Mobile Cloud-Based Dental Software

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

Sprig - Delivering locally-sourced, seasonal, sustainable lunches and dinners.