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Unlock the Future of Business with SequelString AI-Driven Framework

Elevate Efficiency, Drive Innovation, and Transform Your Operational Landscape with Our Advanced AI and Machine Learning Technologies.

AI Templateless Document Extraction Powered by SequelString.

At the pace that suits you, from insight to invention

Uncover

Systematically identify opportunities to enhance performance through ongoing exploration.

Automate

Streamline your work with an automated system that functions flawlessly, fundamentally changing how you get things done.

Execute

Implement and oversee automation driven by AI throughout your organization.

SequelString AI

Govern Smarter. Operate Leaner. Impact Greener.

Optimizing digital transformation for People, Planet, and Performance.

Innovative Brands That Trust Us

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AI (Artificial Intelligence) Vs IA (Intelligent Automation)

An Integrated Automation Platform

is driving Intelligent Automation while leveraging Artificial Intelligence.

Component of Hyper Automation

Impact of Hyperautomation in Business

85%

Reduction

In Human-Agent Requirement

90%

Increase

In Customer Engagement 24X7

Advanced

Automated Lead Verification & Qualification

300%

Advance

In Unified Customer Digital Experience

Intelligent Document Processing

IDP combines computer vision and Al technologies to convert analog data into a digital and usable format.

IDP technology extracts and organizes data from diverse formats and sources, enabling automation of document-centric procedures. IDP uses AI, NLP, ML, CV, and OCR to capture, categorize, and process the most difficult-to-automate data.

Doc Sources

Internal

External

Input Types

Structured

Semi Structured

Unstructured

Formats

Unformatted data

Physical documents

Output

Benefits of IDP

Faster Data Processing

Enhanced Accuracy

Reduced Processing Cost

Improved Process Efficiency

Higher Straight Through Processing

Enterprise-Grade Automation

Applications of IDP

Digitizing Paper Documents:

Scan paper-based documents and convert them into machine-readable file formats

Avoiding Manual Data Entry:

Eliminate manual data entry into data systems by combining IDP solutions with RPA and BPM

Capturing Right Information:

Intelligent data extraction pulls the right data you want from various document formats

Our Products

PRY

PRY driven by AI and Natural Language Processing (NLP) to process and analyze large amounts of data for tasks such as data extraction, transformation, loading, cleaning, and enrichment.

VaOM

The cutting-edge realm of VaOM, where Vendor and Order Management transcend traditional boundaries, ushering in a groundbreaking era of efficiency, transparency, and excellence.

Expense

EXPENSE transforms expense management with its intuitive, template-free interface and smart data extraction, providing clear insights into your spending patterns for superior financial control.

Reduced Cost

Compliance with Legal & Regulatory Requirements

Reduced Carbon Foot Print

Security & Scalability

Reducing the Chances of Fraud

Advanced Governance

Better Record Keeping

Productivity & Operational Efficiency

Reduced Workload

Increased Quality & Data Analysis

Speed & Accuracy

Will our Data be Safe?

Yes, your data is 100% safe & secure and only your chosen people from your own organization have access to your data. Apart from this, your data is in an encrypted format when it is stored in databases as well as during transit between the server and your machine. Multiple security audits and reviews have been done to make sure of this.

Can RPA help Finance and Accounting? Yes!

Automation can empower finance and accounting business units to be more efficient, streamline high-touch processes, and boost employee satisfaction.

End-to-end process automation can save up to 60% processing time and cost, all while integrating multiple legacy systems and applications, reducing the need for manual labor and ensuring maximum data security and compliance across all operations.

Additionally, hyperautomation can accelerate complex processes within the department.

What can be automated? A lot!

There are key areas of opportunity for automation inside finance and accounting. From customer onboarding and invoicing, to cash application, to logistics management to invoice processing, to payments processing.

Nearly any process can benefit from automation inside finance and accounting. In the next page, you will discover process heatmaps that highlight where automation has the biggest potential across the business unit.

Interesting Facts

Facts about Hyper Automation

Hyper automation refers to the use of advanced technologies such as AI, ML, and RPA to automate business processes and tasks, resulting in cost savings, increased efficiency and productivity.
Gartner predicts that hyper automation will be a significant trend in the near future, with 20% of businesses using it to automate processes by 2020 and 40% of DPA efforts supported by it by 2021.
Gartner advises organizations to implement hyper automation in a controlled manner and to consider the potential impact on the workforce, as there is a concern about job displacement and the need for proper monitoring and validation of the automated processes.

IDP - (Intelligent Data Processor)

Our IDP (Intelligent Data Processor) software uses AI and NLP to process and analyze large amounts of data in real-time.
It can extract, transform, load data, clean, enrich structure it, identify patterns and anomalies and generate insights using machine learning algorithms.
It can be used in various industries and can be integrated with other systems, but there are concerns about errors and bias in the processed data.

IDE - (Intelligent Data Extractors)

Intelligent Data Extractors use AI and NLP to extract information from unstructured data sources.
These tools can be trained to identify patterns, handle large amounts of data, and improve accuracy through machine learning.
The use of IDE is expected to increase in popularity, become a standard in data integration, automate extraction tasks, and improve data quality.

Facts about AI

AI refers to the simulation of human intelligence in machines that can think and learn.
AI can be divided into two categories: narrow AI for specific tasks and general AI for any intellectual task that a human can perform.
Machine learning, a subset of AI, uses data to teach computers to learn, while deep learning uses neural networks with multiple layers to analyze and make decisions based on data.

Facts about Hyper Automation

Hyper automation refers to the use of advanced technologies such as AI, ML, and RPA to automate business processes and tasks, resulting in cost savings, increased efficiency and productivity.
Gartner predicts that hyper automation will be a significant trend in the near future, with 20% of businesses using it to automate processes by 2020 and 40% of DPA efforts supported by it by 2021.
Gartner advises organizations to implement hyper automation in a controlled manner and to consider the potential impact on the workforce, as there is a concern about job displacement and the need for proper monitoring and validation of the automated processes.

IDP - (Intelligent Data Processor)

Our IDP (Intelligent Data Processor) software uses AI and NLP to process and analyze large amounts of data in real-time.
It can extract, transform, load data, clean, enrich structure it, identify patterns and anomalies and generate insights using machine learning algorithms.
It can be used in various industries and can be integrated with other systems, but there are concerns about errors and bias in the processed data.

IDE - (Intelligent Data Extractors)

Intelligent Data Extractors use AI and NLP to extract information from unstructured data sources.
These tools can be trained to identify patterns, handle large amounts of data, and improve accuracy through machine learning.
The use of IDE is expected to increase in popularity, become a standard in data integration, automate extraction tasks, and improve data quality.

Facts about AI

AI refers to the simulation of human intelligence in machines that can think and learn.
AI can be divided into two categories: narrow AI for specific tasks and general AI for any intellectual task that a human can perform.
Machine learning, a subset of AI, uses data to teach computers to learn, while deep learning uses neural networks with multiple layers to analyze and make decisions based on data.

Facts about Hyper Automation

Hyper automation refers to the use of advanced technologies such as AI, ML, and RPA to automate business processes and tasks, resulting in cost savings, increased efficiency and productivity.
Gartner predicts that hyper automation will be a significant trend in the near future, with 20% of businesses using it to automate processes by 2020 and 40% of DPA efforts supported by it by 2021.
Gartner advises organizations to implement hyper automation in a controlled manner and to consider the potential impact on the workforce, as there is a concern about job displacement and the need for proper monitoring and validation of the automated processes.

Funny Facts - HyperAutomation

HyperAutomation robots are known to sometimes break out in spontaneous dance parties when they finish a task successfully.

The first HyperAutomation robot was actually a modified toaster that could make perfect toast every time.

HyperAutomation is so efficient that it has been known to cause office coffee machines to overflow with coffee, much to the delight of caffeine-deprived employees.

Some HyperAutomation robots have been known to form strong emotional bonds with their human co-workers, leading to office romances.

HyperAutomation is so advanced that some organizations have reported that their robots have started writing their own poetry, much to the surprise of their creators.

HyperAutomation has been known to cause spontaneous sing-alongs in the workplace, as robots and humans come together to celebrate their newfound efficiency.

One organization reported that their HyperAutomation robots actually convinced the CEO to buy the entire office a round of donuts, leading to a day of unbridled gluttony.

In one company, a group of HyperAutomation robots banded together to form their own union, demanding better working conditions and more frequent oiling.

The most advanced HyperAutomation robots have been known to solve complex mathematical problems in their sleep, just for fun.

One HyperAutomation robot was actually elected as the mayor of a small town, after impressing the citizens with its efficiency and fairness.

Did You Know?