Boston based Botkeeper is the world's first and original robotic bookkeeper. The Botkeeper solution uses a combination of skilled accountants, machine learning, and AI to provide the best bookkeeping at the lowest possible cost. Instead of replacing your existing accounting software, we'll hook right up to it! Botkeeper can easily and quickly integrate with Quickbooks Online or Xero. Getting up and running is simple- 1. Data is extracted from both financial and non-financial sources.…
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Posit
Score 10.0 out of 10
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Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
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Pricing
botkeeper
Posit
Editions & Modules
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No answers on this topic
Offerings
Pricing Offerings
botkeeper
Posit
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
Our goal is to offer bookkeeping solutions that are not only best in class, but available to all companies at all stages of growth. We have our Free Package, all the way up through Custom Packages, and everything in between!
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Community Pulse
botkeeper
Posit
Features
botkeeper
Posit
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
botkeeper
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Ratings
Posit
9.2
27 Ratings
9% above category average
Connect to Multiple Data Sources
00 Ratings
8.026 Ratings
Extend Existing Data Sources
00 Ratings
9.927 Ratings
Automatic Data Format Detection
00 Ratings
9.926 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
botkeeper
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Ratings
Posit
9.0
27 Ratings
7% above category average
Visualization
00 Ratings
8.027 Ratings
Interactive Data Analysis
00 Ratings
10.024 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
botkeeper
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Ratings
Posit
9.9
26 Ratings
20% above category average
Interactive Data Cleaning and Enrichment
00 Ratings
10.024 Ratings
Data Transformations
00 Ratings
9.926 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
botkeeper
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Ratings
Posit
10.0
22 Ratings
17% above category average
Multiple Model Development Languages and Tools
00 Ratings
9.922 Ratings
Single platform for multiple model development
00 Ratings
9.922 Ratings
Self-Service Model Delivery
00 Ratings
10.019 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Well, Suited Scenarios are: Automating the data entry, analysis, bookkeeping, managing finances fairly on this basis, and pulling out burndown charts, reports, and other analytical chapters. hence it helps in understanding the business, cash flows, or issues related to that which surely end up with the ideas of revenue growth directly and indirectly as well. And the most important thing in all this is done by AI-powered tools so management of resources overhead is no more. Scenarios where it is less appropriate: When it comes to a strong comprehensive accounting then the bookkeeper fails there and we need to integrate with third-party service providers to achieve the goal. So this is the worst scenario. And for detailed resources, one needs a vast knowledge base, and that's not the case with the Botkeeper as its knowledge base appears to be limited to basic.
In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition. A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.
The support is incredibly professional and helpful, and they often go out of their way to help me when something doesn't work.
The one-click publishing from RStudio Connect is absolutely amazing, and I really like the way that it deploys your exact package versions, because otherwise, you can get in a terrible mess.
Python doesn't feel quite as native as R at the moment but I have definitely deployed stuff in R and Python that works beautifully which is really nice indeed.
Python integration is newer and still can be rough, especially with when using virtual environments.
RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.
There is no viable alternative right now. The toolset is good and the functionality is increasing with every release. It is backed by regular releases and ongoing development by the RStudio team. There is good engagement with RStudio directly when support is required. Also there's a strong and growing community of developers who provide additional support and sample code.
For someone who learns how to use the software and picks up on the "language" of R, it's very easy to use. For beginners, it can be hard and might require a course, as well as the appropriate statistical training to understand what packages to use and when
RStudio is very available and cheap to use. It needs to be updated every once in a while, but the updates tend to be quick and they do not hinder my ability to make progress. I have not experienced any RStudio outages, and I have used the application quite a bit for a variety of statistical analyses
Since R is trendy among statisticians, you can find lots of help from the data science/ stats communities. If you need help with anything related to RStudio or R, google it or search on StackOverflow, you might easily find the solution that you are looking for.
Botkeeper is quite new to accounting solutions. The tech base is quite new and cutting edge. Service support is quite fast and good. Integration support is open to another third party to enhance in all possible ways. Eliminates overhead of hiring permanent resident accountants. Great user experience and well-optimized tools.
RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful when we had R heavy code with some python threaded in. Overall we picked Rstudio for the features it provided for our data analysis needs and the ability to interface with our existing resources.
RStudio is very scalable as a product. The issue I have is that it doesn't necessarily fit in nicely with the mainly Microsoft environment that everybody else is using. Having RStudio for us means dedicated servers and recruiting staff who know how to manage the environment. This isn't a fault of the product at all, it's just part of the data science landscape that we all have to put up with. Having said that RStudio is absolutely great for running on low spec servers and there are loads of options to handle concurrency, memory use, etc.
Using it for data science in a very big and old company, the most positive impact, from my point of view, has been the ability of spreading data culture across the group. Shortening the path from data to value.
Still it's hard to quantify economic benefits, we are struggling and it's a great point of attention, since splitting out the contribution of the single aspects of a project (and getting the RStudio pie) is complicated.
What is sure is that, in the long run, RStudio is boosting productivity and making the process in which is embedded more efficient (cost reduction).
