How to automate internal processes like risk assessments

How to automate internal processes like risk assessments

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The problem

Qualified employees should solve qualified problems and not waste a huge portion of their capacity with pre-qualification of respective problems.

A company that starts seriously with digital transformation will face the challenge that there will “pop-up” a lot of projects. In this case described here, due to strategic goals like implementing AI and Big Data Analysis, there was high demand to pre-qualify projects e.g. regarding risk assessment. So, the customer needed to transform their legal process and find a cost-effective solution, that is scalable on demand to pre-qualify new projects.

The solution

Necessary pre-qualification is optimized by a Conversational AI guiding the employee through the process

The solution provider used the existing questions and evaluation logic structure to create a Conversational AI survey and evaluation chatbot that is now used to pre-qualify projects e.g. regarding risk assessment. The chatbot collects all the data in a conversational manner and reacts to the user input. The chatbot is capable of analyzing the data and providing a unique response/evaluation. For this solution there was no coding necessary and all necessary features were out of the box ready.

As a result, productivity gains of qualified employees in this process by a factor of 10.


Stumbling blocks

Evaluation logic is set up as a second instance technically. From user perspective it is one chatbot. In order to scale change management content and logic wise as well as new built-outs, we created the system in a very modular and variable driven approach.

What had the customer tried before?

  • The customer conducted a qualified market and provider scouting
  •  Tried establishing the process without chatbot, however, faced limitations on the implementation and flexibility of the system

Additional challenges at the customer

  • Cost pressure
  • Digital transformation awareness
  • New technological possibilities
  • No DevOps resources for own implementation

What criteria were important to him?

  • Technological feasibility
  • Scalability in terms of costs to enable business case
  • Scalability in terms of language reach to act global
  • Educational support from vendor to understand further possibilities



  • Enabled automatic assessment of intended Data Analysis projects without necessary clearance by consulting legal team
  • Changes in content and logic can now be done 10x faster due to modularization and massive use of variables
  • End-to-end automation
  • No need to wait for legal professionals to continue with the implementation of the use

The project schedule

  • use cases description with questions (content) and content/sub-question/evaluation logic by customer
  • create MVP by supplier
  • test and provide feedback on UX by customer
  • re-work and add more content by supplier
  • re-test by customer
  • add evaluation logic by supplier
  • final test by customer
  • push to production by supplier

Project maturity level

Used company-wide

Project duration

8 weeks

Project cost


Involved employees
(Operating phase, FTE)


Running costs
(per month, digits)


Involved employees
(Project phase, FTE)



The project schedule

  • create MVP to demo the flow and UX
  • tune functionalities
  • enhance content/question scope
  • modularize approach to better cope with future changes
  • build evaluation logic as system
  • integrate into customer’s intranet

Technical Specs

  • in productive internal global use
  • NLP and chatbot technology proprietary to Passage AI enabled by a user friendly platform and console
  • hosting required

Where is the data stored?

  • customer data is located in customer´s databases and systems
  • solution is compliant to National and European data protection laws


Adam Friedmann

"If a customer lacks the content and evaluation logic or APIs to their systems , then we are not the perfect match, but if it comes to executing based on a solid logical structure of a survey to free employees’ productivity , we're number one."

Adam Friedmann

The information may of course vary in individual cases. Please contact the provider for an assessment of your project.