BlackFlow

Within 2 months of implementation, we automate turnkey decision-making processes and show how to turn risk into a profitability item
BlackFlow allows any business user to customize decision making strategies of any complexity without involving developers. In the implementation process, we will not only configure the system, but also build machine learning models that will solve the tasks you need
BlackFlow key features

Implementing all types of checks

BlackFlow allows you to customize all types of checks as part of decision-making strategies (checklist, stop factors, factor algorithms, model strategies, portfolio strategies, decision-making) completely in user graphical interfaces
Costs management

BlackFlow supports mechanisms for configuring query strategies to external data sources. You can configure both parallel and consecutive queries to any data source depending on its cost and efficiency
Models Management

BlackFlow supports downloading and running models written in Python. Because model calls are made from the workflows, model risks can be monitored and evaluated
The ease of integration

The system supports standard integration mechanisms with external systems via API interfaces
License transparency

Complete independence from external software and ability to work on unix operating systems
Unlimited customization

The platform can be configured for processes of any complexity
Cases of implementation
Cases of implementation in fintech
Cases of implementation in enterprise
Cases of implementation in logistics, shipping, tracking
Pricing
Start
from $10000/year
  • 1 user
  • 1 master-system
  • up to 30000 requests per month
Standart
from $35000/year
  • up to 5 users
  • direct integration with data sources
  • up to 100000 requests per month
Pro
from $90000/year
  • up to 30 users
  • direct integration with data sources and DWH
  • up to 1 mln. requests per month
Send request
If interested please send us a request for information and we will contact you
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OUR CONTACTS
+7 952 645 85 65
b2b@datalab.fit
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