Aurea Process (formerly CX Process) from Aurea Software in Austin is a business process management offering, based on Savvion BPM.
$200,000
per year
Benchling
Score 9.8 out of 10
N/A
Benchling’s cloud platform is used by pharmaceutical and biotech companies to analyze complex datasets, streamline research workflows, design DNA using CRISPR gene-editing technology and more.
$0
per month
Pricing
Aurea Process
Benchling
Editions & Modules
License
$200,000
per year
Academic
$0
Professional
Contact Benchling for price
Enterprise
Contact Benchling for price
Offerings
Pricing Offerings
Aurea Process
Benchling
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
Aurea Process
Benchling
Features
Aurea Process
Benchling
Reporting & Analytics
Comparison of Reporting & Analytics features of Product A and Product B
Aurea Process
5.3
1 Ratings
38% below category average
Benchling
-
Ratings
Dashboards
6.01 Ratings
00 Ratings
Standard reports
6.01 Ratings
00 Ratings
Custom reports
4.01 Ratings
00 Ratings
Process Engine
Comparison of Process Engine features of Product A and Product B
Aurea Process
5.8
1 Ratings
36% below category average
Benchling
-
Ratings
Process designer
6.01 Ratings
00 Ratings
Process simulation
7.01 Ratings
00 Ratings
Business rules engine
5.01 Ratings
00 Ratings
SOA support
5.01 Ratings
00 Ratings
Process player
7.01 Ratings
00 Ratings
Model execution
5.01 Ratings
00 Ratings
Collaboration
Comparison of Collaboration features of Product A and Product B
Aurea Process
4.0
1 Ratings
70% below category average
Benchling
-
Ratings
Social collaboration tools
4.01 Ratings
00 Ratings
Content Management Capabilties
Comparison of Content Management Capabilties features of Product A and Product B
The tool has potential. Its capabilities and visual aspects could be considered rather basic but this might improve, particularly if the business intelligence/analytics aspect is leveraged. Once running well, it could allow (perhaps smaller) companies to successfully improve their customers' experiences through digitalizing customer journey - and we all know that customer loyalty goes a long way. However, whether or not the tool is comprehensive enough to deliver this for larger companies with more complex, multi- and omni-channel interactions is yet to be seen...
Benchling is especially well suited to groups or contexts where there are many users who do not have a coding background but need a seamless and structured approach to data. Benchling is particularly useful in cases where there are data flows from instruments and other devices where the data can be deposited in an automated fashion. It is likely less appropriate or useful to users who are just looking for a general data warehouse solution.
Some of the integrations can be a bit spotty so it depends on what kind of data source you are integrating
Sometimes new users are not always aware of all the various functionality that Benchling has - can do better to provide more user awareness of more complex features
Benchling was much more of a full stack solution and provide much more features that were relevant to the group. Airtable was more of a generic way to manage large amounts of data, but the complexity was still high for the types of data that would be need to be managed and there would need to be some workarounds. Overall Benchling was selected since it also had an electronic lab notebook feature which was very useful to associates in addition to its data workflows.
As our customers vary in size and maturity, the ROI ranges accordingly.
For younger, smaller businesses this is a useful tool. Digitalization of he customer journey has certainly helped save time and efforts in many cases.
For more mature market players the tool is not always comprehensive enough. Dashboard and report personalization take time and efforts, and sometimes it feels that a dedicated BI tool would be a more suitable solution.
It had a positive ROI in terms of reducing the amount of time spent on data movement and curation by associates
It had a positive ROI in terms of increasing the number of insights from structured data
It reduced the number of data entry and analysis errors by associates which led to a positive ROI in terms of efficiency and reducing time wasted by tracking down errors in data