Amazon SageMaker vs. AppSheet vs. C3 AI Platform

It allows for one-click processes and for things to be auto checked before they are moved through the process but through the system. It also makes training easy. I am able to train users on the basic fundamentals of the tool and how it is used very easily as it is fully managed on its own which is incredible.

Incentivized

If you need to manage special assets with unique characteristics and keep data in spreadsheets, Appsheet is ideal for replacing these sheets with a system. Once you start using it, you find yourself trying to move everything into Appsheet. It is perfect for generating internal software that would otherwise never be developed due to programming costs.

Incentivized

For consultants like me, who are not interested in generic LLM's with very deployment costs and payback times, industry specific applications are essential. We are time-bound to deliver value to our clients whether it is improved productivity or revenue uplift, and for this particular reason C3 AI Platform is a particularly good choice.

• Machine Learning at scale by deploying huge amount of training data
• Accelerated data processing for faster outputs and learnings
• Kubernetes integration for containerized deployments
• Creating API endpoints for use by technical users

Incentivized

• Calculations - I have several apps that do some pretty complicated calculations, and decision making to build things like Shopping Lists for a Kanban assembly team, where the app will help a stocker determine whats low in a kanban assembly line stock box.
• Document generation and record keeping - I have an app that users digitally sign and receive PDF contracts, and the system automatically records all records from the transaction. Everything is held in files on YOUR OWN DRIVE (Google Drive) so when you're done with the project or AppSheet you DONT loose your data.
• Client/Customer Management - I follow the old school "Swimming with Sharks" model for client retention and customer engagement, and have built several small customer tracking tools for local businesses. This tool is limited ONLY by your imagine and desire to learn.

Incentivized

• It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
• Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.

Incentivized

• Once the tables / UX Views get way too many in number, it can become a little daunting to manage. This part of the UX may need something really smarter.
• Ability to Undo.
• Could provide more UI Look and Feel options. BTW, the new Graphs look great, but have some bugs, while the new INPUT() feature is a great addition too.

We are still less than 10 users and probably may continue to be so. But, this being a franchisor set up, could be of use to other users like us.

It's just great. The usability is the best thing about Appsheet. You must choose which things will really be used later. You have to be careful of not generating something too big and then it feels like something that need to be learned. This is something that resolve problems, but you had to be able to think before doing. It will not solve problems itself. You need to find the problem, think a solution, and then use appsheet to make this solution a reality

Incentivized

I’d give it 7.5/10. Its model-driven architecture is powerful for scaling enterprise AI, at pace but it definitely needs some heavy-lifting. The platform can be hard to grasp initially and the steep learning curve, makes change management very important. The framework can be a bit rigid for industry agnostic developers used to flexible, open-source tools. It is excellent for data orchestration but is not as lean as some of the low-code competitors.

AppSsheet has a support group and they show videos to help app builders. Though I have truck drivers' hours and can't join the webinars. Support groups with better assists me on a Saturday evening or a Sunday that I have time off. It's hard to watch videos driving down the highway.

I did everything on my own

Incentivized

Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.

Incentivized

The ease that AppSheet provides to the developer is limitless. Before starting with AppSheet I used other software, but they didn't give me the tools at my fingertips.
When I learned about AppSheet and everything it could do, I understood that it was what I was looking for, the ease with which everything is related within the app with a few clicks is impressive.

C3 AI Platform offers much faster deployment through pre-built, industry-specific apps, and comfortably beats the others when it comes to time to deployment and scalability. Palantir on the other hand requires heavy custom engineering. C3 AI Platform does lack the open-source flexibility of Databricks and the cloud native scale of Vertex. I would prefer C3 AI Platform for turnkey enterprise solutions, but for other use cases it can be a bit more complex vs the other three due to its "back-box" environment.

• We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
• We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
• For our use-cases, serving models is less expensive with SageMaker than bespoke servers.

Incentivized

• A good impact in general at the beginning since the free version allows great development so the investment in the implementation is of knowledge and time.
• As a consultant I have expanded my services through this platform including new low code application building services.