With an ever-increasing portion of our transactions and interactions being carried out over the internet, verifying documents in real-time and securely has become increasingly essential. Agentic AI provides an advanced solution for automated document verification using AI technologies such as OCR and LLMs for seamless processing. This blog discusses how Akira AI’s Agentic AI automates document checks, identifies fraud detection, and ways companies can double down on tightening security and efficiency without compromising compliance.
AI agents are computer programs that are designed to carry out tasks independently by making decisions based on their environment, input, and some set objectives. Unlike conventional automation systems that strictly follow predefined instructions, AI agents can think, adapt, and act on their own. They are configured to evaluate their surroundings, learn from past experiences, and make decisions to accomplish specific goals.
AI agents can vary from basic programs performing single tasks to sophisticated systems managing complex processes. They excel in unpredictable environments and utilize their learning capabilities to navigate the internet, interact with applications, process enormous amounts of data, and engage in transactions along with refining their methods on the feedback.
AI Document Verification Agents will revolutionize this process through the automation of Key Activities that hold importance in the line of identity verification and checks against fraud and compliance. The synchronized processing of documents will inevitably make sure the tasks are always done in the right way and as quickly as possible. Where the Fraud Detection Agents are looking at tampering and manipulations, it is at the clearing; the KYC Agents go on to clear identities concerning their genuine status; further, the ability of the firm to scale its document verification processes keeps increasing.
Although those traditional ways of documenting were helpful with respect to some fronts, yet big limitations have been felt in today's digital environment. Some major challenges regarding these approaches are :
1.Time-Consuming Procedure: Manual document verification involves humans going through documents and verifying data against the available records. This is generally a time-consuming process for any form or volume of data. Industries, specifically banking and real estate, could indeed take KYC processes from days to weeks in some selected use cases.
2.High Rate of Errors: Human verification of documents is highly prone to errors. The information can be overlooked, numbers misread, or the interpretation inappropriate. Such mistakes are magnified with repetition and lead to scenarios where a document can either be wrongly approved or rejected.
3.Challenges to Fraud Detection: Document verification makes fraud detection problematic, with advanced forgery usually passing human reviewers. Minor changes in software can never be found to complicate identity theft. Traditional means of analysis and cross-checking have not provided effective automation.
4.Compliance Complexity: Industries have to obey laws and regulations such as GDPR, AML, and KYC. The manual human reviewer needs human verification, so companies are thus exposed to missing out on relevant regulatory details and failing compliance, which will lead to fines and reputation damage.
Addressing the challenges via Agentic AI
AI Document Verification Agents are going to revolutionize this process through the automation of critical activities that hold importance in the line of identity verification and checks against fraud and compliance. The synchronized processing of documents will inevitably make sure the tasks are always done in the right way and as quickly as possible. Fraud detection agents are looking at tampering and manipulation.KYC Agents have clear identities concerning their genuine status, which enhances the ability of the firm to scale its document verification processes.
Akira AI’s multi-agent workflow revolutionizes the document verification process by automating every aspect of the cycle. The system is composed of an agentic workflow with several specialized AI agents, each designed to handle a specific task within the process.
1.Application Submission: The entire process initiates when the user applies for document verification. The user is supposed to upload all the required documents.
2.Document Upload: The system will carefully verify whether or not all documents have been uploaded. If any one of them has not been, then the system shall prompt the said user to upload the document immediately.
3.IDP - Intelligent Document Processing: Through OCR-enabled IDP, key information from various document types is automatically extracted and validated. It detects any discrepancies in the document and verifies authenticity of the data.
4.Verification Steps
a)Forgery Detection: The system checks for signs of forgery by comparing the document against known authentic and counterfeit documents. It looks for changes, and inconsistencies in text or image quality, and checks the validity of electronic signatures.
b)KYC (Know Your Customer): The system verifies the extracted data against external databases to confirm the applicant’s identity.
c)Compliance Check: The system ensures that the document verification process meets all regulatory and compliance requirements.
5.Document Verification Report: Once all the processing and verification processes are well executed, an output for a detailed Document Verification Report is generated. It includes all the results obtained from the verification process.
Our composite AI framework utilizes the components from traditional Machine learning to advance Multi-agent systems:
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Layer |
Component |
Stack |
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Multiagent Layer |
Agents |
For agent development, we have been using advanced agent frameworks like langchain, langraph, and Autogen to build SOTA agents. |
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RAG (Retrieval Augmented Generation) |
Langchain, llama index frameworks, and knowledge Graphs utilized for building RAG pipelines for compliance |
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Traditional ML (Machine Learning) |
IDP - OCR, |
Integrated Document Processing (IDP) with Optical Character Recognition (OCR) |
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Predictive Models |
Traditional Machine Learning models were trained for document verification purposes. |
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Backend |
Backend pipelines |
Built using industry best practices to develop secure and scalable APIs. |
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Frontend |
User Interface |
Developed using industry best practices to ensure a secure and user-friendly interface.
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Infrastructure layer |
Infrastructure |
Utilizes best-in-class infrastructure options, including on-premises, cloud-based, and hybrid solutions
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1. Master Orchestrator Agent
The central command unit that directs respectively, the overall automation of the credit analysis process. It is responsible for delegating the tasks to other agents so that at every stage in the process each step is free of any errors.
It relies on an LLM for higher-order decision-making. The knowledge graph captures the analysis data, rules, and relationships related to this domain and integrates the results into the Master Orchestrator Agent.
2. Forgery Detection Agent
The tracing of actual fraud or tampering in such documents is totally dependent on the agent. For example, a typical agent would use machine learning models that may have been trained with large datasets comprising real and forged documents to trace tampering by finding some inconsistencies in alteration or text or image quality or the metadata of the document. The agent shall validate the signature of the document as for a valid electronic signature and verify it against a public key of the issuer.
3. KYC Agent
The KYC agent checks if the person sending in documents is indeed himself. Extracted data is cross-referenced on existing information, either through databases or APIs, to confirm the fact that the information is applied to a real, existing person.
The interaction point includes any other external systems or databases, like government databases and financial institutions, through which the agent of KYC verifies an applicant.
4. Compliance Agent
The agent ensures that the verification process is being conducted under important regulatory and legal requirements. It views data against a set of pre-defined rules and guidelines to verify that the data conform to some legal compliance standards. The agent adopts a rule-based approach—the base may include legal regulations in conjunction with company policies and industrial standards. It makes sure that any such steps taken up during the verification are done in respect to such rules.
5. Final Processing
Once all the processes and verification are completed well, it generates a detailed output concerning the Document Verification Report, displaying all the results that have been gotten out of the verification process that took place.
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Aspect |
Traditional AI Document verification |
Akira AI Agentic document verification solution |
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Verification Speed |
Often slower due to reliance on manual processes and limited automation. Large volumes of documents create bottlenecks that delay decision-making |
This employs a very robust Multiagent system and Composite AI framework, which aids in rapid, automated processing that considerably reduces verification times, hence eliminating bottlenecks. |
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Accuracy |
Not accurate because of algorithms and inconsistency of human involvement. |
This can be greatly improved with better OCR and AI advanced algorithms. It involves a set of several specialized agents to provide precise and efficient verification results. |
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Forgery Detection |
Limited to handle sophisticated forgery and fraud techniques. |
Employs advanced forgery detection algorithms and computer vision tools that identify and prevent sophisticated fraud attempts |
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Compliance and Security |
Compliance management is usually complex, often involving manual updating of changes in regulation. Security cannot always be strong. |
Imposes strict adherence to regulatory standards through the automation of compliance checks. Security is also advanced. |
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Real-Time Decision-Making |
The processing may take a little time, and manual handling may delay the decision-making process |
It helps organizations take quick action based on proper and current information with immediate verification results for real-time decision-making. |
1.Precision: AI agents are applied in advanced analysis of a variety of documents to a greater degree of precision; hence, it reduces human errors and ensures that the outcomes arrived at in verification are those which are trusted.
2.Real-time decision-making: It is made possible as verification results fall at your fingertips to make timely and better decisions for individuals and institutions alike with more precise, the latest information.
3.Expedited verification: Automation of document verification greatly reduces the processing time and avoids delays. This enhancement thus enables smooth processing, and volumes can be managed with ease.
4.Advanced forgery detection: It makes use of sophisticated algorithms, thus specifically designed to bring out any form of forgery and fraud. This is technology that protects one from any form of document tampering and concurrently ensures the authenticity of the said documents.
5.Seamless workflows: Since the system can be integrated with the existing systems, it allows a continuous smooth process which results in enhanced operational efficiency and effectiveness from top to grass root.
6.Better compliance: Strict observance of the laid-down regulatory standards greatly boosts security measures for the data. This would ensure that all aspects related to document management meet all the legal requirements and the demands of the specific industry.
The integration of Akira AI's document verification solution runs with the power of the Multiagent system, a Composite AI framework for unchallenged efficiency, and incredible accuracy. By deploying advanced OCR, intelligent agents, and state-of-the-art technologies for faster processing, such a revolution in the direction of real-time document verification will make the level of compliance quite high. Accordingly, this makes the process of verification of documents easy and reliable.