KlearStack
Automated Invoice Processing using Machine Learning
Make your process automation friendly, by converting semi-structured data into structured data!
We use artificial intelligence to capture the invoice details WITHOUT template driven or rules-based setup. Using deep learning and neural networks and mimicking the attention to detail of a human eye, our solution extracts information from the unlimited number of invoices in a structured way! It thus significantly increases the efficiency of your invoice processing.
End to end AP Invoice Processing using AI and RPA, that provides >100% productivity improvement in < 15 days, with 0 capital expenditure
Key Features:
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Speeds up the processing time compared to average human user.
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No templates required, unlike currently used OCR tools.
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Accurate, anywhere, anytime: Artificial Intelligence empowers us to extract data from the invoice with high accuracy and precision.
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Compatible with multiple languages: English (UK, US) and German.
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90%+ accuracy from Day 1, with continuous improvement.
Tandem Digital Team
Digital Recruiter
With Mavenick’s expertise in RPA and AI, an “integrated back office-front office” came to birth.
End to end automated recruitment solution that reduces the manual effort by 10x, reduces the recruitment time by 8x, increases the quality of shortlisted profiles and reduces the recruitment cost by 2x
Key Features:
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Do not miss assessing even a single applicant
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5x faster turn-around time despite 100% coverage
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End to end recruitment automation. No human intervention necessary after Job Description is created. All the subsequent steps are automated, until the first face to face interview takes place
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Job posting to job portals
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Applicants evaluation against JD using Machine Learning and Natural Language Processing
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Resume sourcing using multiple public websites
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100% resume scanning and scoring against Job Description using NLP/ML
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Administering online test for hard skills assessment
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Screening interview using Conversation Bots
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Scheduling interviews for final shortlisted candidates