Appian vs. Azure AI Document Intelligence vs. Ephesoft Transact

Appian works great for automating manual processes and integrating multiple systems through its toolset. It gives great flexibility for establishing rules for approvals, routings, escalations, and the like. Because of the low code toolset, it's very easy to deploy and make changes as needed as processes evolve and as the organization learns to utilize the system better. Minimal maintenance is required to support the applications build on the platform. Some of the automated testing integration with tools like Jenkins is limited so that may be an issue for some.

Incentivized

Azure AI Document Intelligence is mainly used in document data filling. If the template is the same, only the inside data content will be different. There, we use a text-based OCR process to fill the data in the same template with different, accurate data means the manual work will be reduced and time saved. And used in an image and text combined bot if the user query through text from the knowledge based document it brings the output which is used in information technology and services.

Incentivized

• Allows at a glance workflow documentation which assists in the need we have for information readiation.
• Drag and drop interface for workflow development greatly speeds our apps time to market.
• Using the advanced features of Appian, we are able to create working sites in a fraction of the time it would take to do so using "traditional" development.

Incentivized

• From the Image the OCR technology use to store embedding properly
• From the images the OCR technology automatically capturing text is brilliant
• Also for creating Azure AI Document Intelligence endpoint and keys it is very easy to do

Incentivized

• Search issues when type ahead and database search are used in the same field.
• Buttons implementation where user is require[d] to click on the button description - if clicks on the button outside that text - button will not work.
• Problems with using certain off-the-shelf performance tools like WebLoad or Neoload. That is because of different dynamic variables being used internally in Appian - which these tools are unable to correlate. We are still investigating using other tools like Jmeter to overcome dynamic correlation problem for performance testing.

Incentivized

• Azure AI Document Intelligence should have used to store image based embedding for multiple languages
• Images storing part is a different area in our case and only for a few images that part can be increased
• Cost is high which should be reduced so more users will come and more technology through this will come

Incentivized

We recently renewed our license with Appian. We are convinced that its flexibility, relative ease of use, the support they provide, there mobile advancements and their general willingness and desire to see us succeed all contributed to our reason to renew our agreement with Appian

Appian is a low code environment, because of this, a very good visual interface is required. Appian is providing a feature-rich dashboard [that] we can use for building the dashboards and other interfaces. Appian also provides patches and releases to enhance these features. A developer can start off development just by going through a basic course from the Appian learning community.

Incentivized

Azure AI Document Intelligence mainly meets our business requirements. Actually, what we need is image and text-based multimodal, and we store data in pgvector PostgreSQL vector embedding those data. For that, we need text and image combined embedding, which we can get from Azure AI Document Intelligence. Which is working good for us and improved accuracy not 100% but 70% accuracy we are getting at least through Azure AI Document Intelligence.

Incentivized

Appian is one of the leading low code business automation platforms that support RPA, decision rules, case management, workflow automation, and machine learning all in a single bundle. But it is also harder to implement and replace the traditional business process.

Incentivized

As analyst I participated in a developer boot camp. At times it was hard to keep up but most of the time it made sense. Trainer took the time to explain and slowed pace down to answer questions etc.

Incentivized

Very boring; hard to get through quickly, but rather effective in demonstrating the use of the platform.

Incentivized

It was really seamless. SaaS in the true definition of the word. We logged on and started using the product. Very easy.

Incentivized

Appian has enormously transformed and keeps on updating the product every quarter to meet the latest needs of the world with new innovations & technologies being integrated within the platform. What gives more pleasure than a product that keeps on continuous[ly] improv[ing]?

Incentivized

Azure AI Search, we used to bring image and text relevant to the user query, but it did not work properly, and the accuracy was very poor compared to Azure AI Document Intelligence. Azure Blob Storage we used to store images and bring in frontend there also accuracy low, so we went for embedding through Azure AI Document Intelligence. Azure AI Content Safety for text content, but it is very costly, so we went for Azure AI Document Intelligence.

Incentivized

• I believe it has negatively impacted our release dates. There may have been a misunderstanding as to the learning curve, even though it is "low code."
• The look and feel of the applications created using Appian have uniformity and it's easier to have "reuse" between applications.
• There is less developer control when it comes to features. I think this mainly has to do with the amount of plugins available. I would think there should be many more available plugins. But again, our use case is probably different than most others.

Incentivized

• Significant reduction in manual processing cost by 40-60%
• Improved data accuracy and reduce work
• Scalability is good without cost increase

Incentivized