Pecan is an automated AI-based predictive analytics platform that simplifies and speeds the process of building and deploying predictive models in various customer-related and operational use-cases, such as LTV, churn, NBO, risk, and segmentation. Pecan does not require any data preparation, engineering, or prepossessing - it connects directly toraw data, and uses neural networks to automate the entire predictive process. With Pecan, organizations can obtain and deploy AI models in days, without…
$950
per month
RapidMiner
Score8.9 out of 10
N/A
RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer. RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.
$7,500
Per User Per Month
Pricing
Pecan.ai
RapidMiner
Editions & Modules
Starter
$950
per month
Business
1,750
per month
Pay as you go
Pay as you go
per month
Let's talk
Custom
Professional
$7,500.00
Per User Per Month
Enterprise
$15,000.00
Per User Per Month
AI Hub
$54,000.00
Per User Per Month
Offerings
Pricing Offerings
Pecan.ai
RapidMiner
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Features
Pecan.ai
RapidMiner
Platform Connectivity
Comparison of Platform Connectivity features of Pecan.ai and RapidMiner
Feature
Pecan.ai
-
Ratings
RapidMiner
9.5
2 Ratings
13% above category average
Connect to Multiple Data Sources
00 Ratings
10.02 Ratings
Extend Existing Data Sources
00 Ratings
10.02 Ratings
Automatic Data Format Detection
00 Ratings
9.02 Ratings
MDM Integration
00 Ratings
9.01 Ratings
Data Exploration
Comparison of Data Exploration features of Pecan.ai and RapidMiner
Feature
Pecan.ai
-
Ratings
RapidMiner
9.0
2 Ratings
6% above category average
Visualization
00 Ratings
9.02 Ratings
Interactive Data Analysis
00 Ratings
9.02 Ratings
Data Preparation
Comparison of Data Preparation features of Pecan.ai and RapidMiner
Feature
Pecan.ai
-
Ratings
RapidMiner
8.8
2 Ratings
7% above category average
Interactive Data Cleaning and Enrichment
00 Ratings
9.02 Ratings
Data Transformations
00 Ratings
7.02 Ratings
Data Encryption
00 Ratings
9.02 Ratings
Built-in Processors
00 Ratings
10.02 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Pecan.ai and RapidMiner
Feature
Pecan.ai
-
Ratings
RapidMiner
9.0
2 Ratings
7% above category average
Multiple Model Development Languages and Tools
00 Ratings
9.02 Ratings
Automated Machine Learning
00 Ratings
9.02 Ratings
Single platform for multiple model development
00 Ratings
9.02 Ratings
Self-Service Model Delivery
00 Ratings
9.02 Ratings
Model Deployment
Comparison of Model Deployment features of Pecan.ai and RapidMiner
Pecan is something that few know and that I feel can represent a great utility for an entire company, to focus and prioritize all its products and services in favor of the right path, avoiding making mistakes and jumping directly to the solution of future problems before they happen. Pecan will allow you to always be one step ahead and improve your trading system quickly.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
RapidMiner is really fantastic to perform fast ETL processes and work on your data as you want, no matter what is the source. You will really save a lot of time when you learn how to use it. You can create mining analysis with several algorithms, and thanks to add-ons, you can apply a lot of techniques. It will not replace a business intelligence dashboard but it allows to create great datamarts for your BI tools. One negative thing is that It's no easy to share your outputs.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
One of the main important characteristics is its ease of use and the intuitive nature of the platform. It is possible to carry out analyzes quickly and efficiently without requiring user experience. This positive point really gives us what we need for our work: optimization and automation.
The creation of reports and statistics allows us to fully visualize the analysis carried out, in order to develop our work and carry out the pertinent actions.
Segmentation allows us to prioritize potential customers, more focused marketing campaigns, highlight our services with what our public is really interested in.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I am very impressed at how easily you can work within RapidMiner without much data analytics training. Plus with the help of the crowd, you can see what steps others have taken with their data analytics projects.
Text mining was simple and clean. We used this for our call transcription problem where we didn't have the resources to listen to each call. We needed to qualify each call based on some key phrases.
Our direct mail program was large and not very targeted. Using RapidMiner, we were able to isolate a predictive level we felt comfortable with and decided not to send to anyone below that level. We saved quite a bit of money.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I hope RapidMiner would be the first data science platform that allows data scientists to change the behaviour of a machine learning algorithm that already exists in the repository. For example, I want to be able to change the way a genetic algorithm mutates.
Automatic programming: One day, I hope RapidMiner can automatically generate codes in any 4th generation programming language based on the developed model.
More tutorials/samples needed: Why doesn't RapidMiner becomes the next 'UC Irvine Machine Learning Repository'? Provide real examples and real cases for users to study and understand the best practices in modelling. RapidMiner already has some datasets for a tutorial. Besides the existing samples, I hope RapidMiner can provide more sample data and examples.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I particularly believe that CrossEngage has some features that Pecan does not offer, such as A/B Testing, however, we were looking for a good predictor and analyst and the truth is that Pecan does its job very well.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We tried different data tools and we figured we give RapidMinder Studio a shot as one of our employees had experience with it, and when compared to some of the other tools that we used it was the best fit among the test group that we used. Overall it was a little more fluid and user-friendly.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Thanks to the patters that RapidMiner has detected, we have been able to follow clues in the right direction, both for the Protein Interaction Network Analysis and for the Epilepsy Research
Students and participants of the machine learning workshops have learned about this technology and about the tool
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info