Reduce routine work
in documents workflow
with artificial intelligence
APprehension RoBOT
Examples of ApRbot solutions
Understanding documents
Extracting information from primary legal and accounting documents (more than 150 types), including documents without templates (emails, reports).
Budget analysis
Automatic cost classification with budget reports.
Communicating with customers
An email bot/chatbot that responds to customer and vendor requests provides information from SAP and other systems, including the state of mutual settlements, calculation of proposals, preparation of draft contracts.
Consolidation of reports
Extracting information from non-patterned reports, including service stations, medical reports, insurance agents, and turning it into structured data.
Understanding legal agreements
Extracting the meanings of clauses and subclauses of legal agreements.
Payment control
Document audit of customer payments (checking packages of documents: accounts, acts, contracts and more than 50 types).
Industry solutions
Banks, factoring, leasing
Insurance companies
Unstructured data problem
80% of corporate data according to Google research is unstructured, i.e. the computer can not understand them, and need a person to translate them into a format suitable for automation.

- The volume of unstructured data is growing exponentially
- Manual data translation is a huge amount of time and money

What ApRbot Helps
Companies can spend less on processing document, email and speech streams and get a new revenue-boosting tool
We reduce the cost of processing documents by 50-80%
We increase the processing speed by 5-30 times
Employee efficiency
We make experts happier, freeing from the routine, while increasing their productivity by 200-400%
Risk reduction and profit growth
We reduce risks through great transparency. Helping earn more with data for quick management decisions
Solve the problem of document flow management
How it works

ApRbot first track winner
Moscow Accelerator 2020
Partners and customers
Alexander Abolmasov