Impulse creates digital workforce to perform repetitive and mundane work so that our enterprise customers utilize human cognitive power in solving higher order problems.
Enterprise Automation Problems
How Does Impulse Solve Enterprise Automation Problems
Cluster Based Deployment
Supported Cloud Platforms
A Unified Platform For End-to-End Enterprise Process Automation With AI
- Large scale ETL to ingest and transform data. documents, images, and videos from a wide range of sources.
- Machine Learning and AI: Automate machine learning, computer vision, NLP, and AI models using pre-built algorithms without writing code.
- Automation: Create data processing flow and intelligent automation tasks using UI based drag-and-drop tools.
- Visualization: Integrated MvInsight displays automation outcomes in the form of dashboards, graphs and charts.
- Validation and Verification (VNV): Using customizable UI to perform VNV to maintain quality and integrity of the automation tasks.
- Feedback and continuous learning: Configure for incremental model training for improved automation accuracy.
How Is Impulse Different From Other RPA Software
- Most RPA companies use third party libraries and components to perform specialized automation tasks. For example:
- Some RPA companies use ABBYY OCR
- Some RPA companies use cloud based APIs, such as Google Vision API
- They depend on third party companies for ETL work
- They partner with other data science platform to do AI/ML
- Our advantage is that Momentum with Impulse are self-contained, suite of tools and technology with no third party licensing needed to develop complex enterprise automation.
- On-prem deployment for sensitive data, without requiring Internet connectivity, prevents data from getting out of the enterprise firewall.
- No third party dependency makes us price competitive as well.
Select Examples of Process Automation By Impulse
- A large bank with 850 branches across different geographies automated key banking processes by using Momentum and Impulse. Impulse automated data extraction from both printed and handwritten documents and performed automatic banking transactions, thereby, reducing operating cost by 40%.
- A large real estate technology company automated data extraction and normalization tasks that involved reading a large number of structured and unstructured documents used in the lending process.
- A financial services company automated data extraction and normalization from bank statements.
- A large bank automated Know-Your-Customer (KYC) by automatically reading contents from various types of identity documents, such as driver license, passport, and tax documents.