elsAI

Problem Statement

1. Complex Property Insurance Documents: Addressing the challenge of deciphering intricate property insurance documents, which often contain dense legal language and technical terminology.
2. Efficient Data Extraction and Comparison: Streamlining the extraction, classification, and summarization of key insurance policy data to facilitate quick and accurate comparisons between contracts and offers.
3. Language Barriers: Overcoming language barriers by processing documents written in non-English languages, ensuring accessibility for users.
4. Data Privacy Compliance: Ensuring compliance with data privacy regulations, such as GDPR, by implementing encryption, access controls, and anonymization techniques to safeguard sensitive customer data.
5. User-Friendly Policy Analysis: Providing a user-friendly platform for policy analysis, enabling users to easily navigate and understand complex insurance terms and conditions.

Solution Overview

1. OptiSol worked with a startup company in building a Minimal Viable Product (MVP) for efficiently processing complex Property Insurance documents in Switzerland using Natural Language Processing (NLP) and GPT-based models.
2. The solution will extract, classify, and summarize key insurance policy data, including coverage, deductibles, exclusions, and limits, from uploaded PDF documents in the non-english languages like German, Arabic etc.
3. To protect sensitive customer data, the solution will incorporate encryption for data at rest and in transit.
4. AWS cloud hosting with robust security measures, access control, and anonymization techniques will ensure GDPR compliance.
5. In addition to document processing, the solution will offer advanced features such as comparing insurance contracts and offers, anonymizing sensitive data, and implementing a question-answering system for precise information retrieval.

Business Impact

1. Efficiency and Cost Reduction: The solution optimizes document processing, leading to significant time and cost savings for insurance companies and policyholders alike.
2. Informed Decision-Making: By offering accurate and comprehensive data extraction and comparison capabilities, the solution empowers users to make informed decisions regarding insurance policies, ultimately reducing the risk of financial losses.
3. Revenue Generation: The platform's advanced features attract users and create a new revenue channel for the business, enhancing its financial performance and growth potential.
4. Competitive Edge: By providing advanced functionalities such as document comparison, data anonymization, and question-answering systems, the solution distinguishes itself from competitors and strengthens the business's position in the insurance industry.
5. Customer Satisfaction and Retention: The user-friendly interface and comprehensive features enhance customer satisfaction, leading to increased loyalty and retention rates among users of the platform.

Problem Statement

1. Manual Data Extraction: The client faced difficulties in manually extracting company details from PDFs provided by Governmental Institutional Bodies, resulting in inefficiencies and resource constraints.
2. Non-Roman Text Encodings: Handling non-Roman text like Arabic and Pashto characters posed a major challenge, requiring specialized encodings for accurate extraction and representation.
3. Confusion of Characters: The complexities of non-Roman characters within the PDFs often caused confusion during data extraction, resulting in inaccuracies and errors in the extracted information.
4. Improper Outputs: The current extraction methods produced inaccurate outputs with non-Roman text, making it hard for the client to trust the data for critical decision-making.
5. Lack of Scalability: The client struggled to scale the data extraction process manually for a large number of PDFs using traditional methods, hindering their ability to meet the increasing demand for data processing.

Solution Overview

1. OptiSol partnered with a prominent fintech provider to implement automated data extraction solution using Generative AI space.
2. The solution efficiently identifies and extracts company names, addresses, important dates, and related details from semi-structured Arabic PDFs.
3. Preprocessing removes watermarks to improve extraction accuracy.
4. OCR technology is used to extract text from PDFs, ensuring proper handling of Roman and Arabic characters.
5. The solution intelligently tags headings, paragraphs, and indexed list items, extracting required fields with keywords and converting them into multi-paged spreadsheets.

Business Impact

1. Faster Data Processing: Overcoming non-Roman text issues and converting PDFs into tabulated data improves data processing speed.
2. Accurate Information: Increased accuracy over manual processing ensures reliable data for better decision-making.
3. Enhanced Data Accuracy: The solution's ability to handle Roman and Arabic characters accurately ensures reliable data extraction, minimizing errors and enhancing the quality of extracted information.
4. Increased Productivity: The automated data extraction process allows the client's team to focus on higher-value tasks, leading to improved productivity and resource optimization.
5. Competitive Edge: Streamlined data extraction gives the client a competitive advantage in making faster and more informed decisions than competitors relying on manual methods.

Problem Statement

1. Complexity of Legal Processes: Users often struggle with the complexity of legal procedures and terminology. Understanding legal documents, identifying key points, and navigating through intricate legal jargon can be overwhelming.
2. Cost and Time Concerns: Traditional legal services can be expensive and time-consuming. It is also a challenge to find affordable legal assistance or may need quick resolution to their legal issues without lengthy delays.
3. Access to Expertise: Access to legal expertise may be limited, especially for individuals or businesses in remote areas. Finding qualified legal professionals who specialize in specific areas of law can be challenging.
4. Confusion Over Legal Matters: Users may have doubts about the validity of legal documents, interpretations of laws, or the strength of their legal arguments. This uncertainty can lead to stress and indecision.
5. Dispute Resolution Challenges: Resolving legal disputes can be particularly daunting, involving complex negotiations, precedents, and case law. Clients may struggle to find effective solutions and may face prolonged legal battles.

Solution Overview

1. OptiSol collaborated with a startup to develop an AI-driven conflict resolution application, empowering users to utilize OpenAI for resolving legal inquiries effectively.
2. This AI-powered solution is accessible via a digital mobile application, offering users convenient access to its functionalities.
3. Through interactive sessions within the app, users can submit questions regarding their uploaded documents and receive precise and insightful responses.
4. Secure storage of legal documents in a database ensures accessibility for future reference and compliance audits.
5. The application caters to a broad user base, catering to the needs of both legal professionals and individuals seeking clarity on intricate legal matters.

Business Impact

1. Enhanced Legal Document Handling: Utilizing LLM Models streamlines the process, enhancing efficiency in understanding and categorizing legal documents.
2. Accelerated Time-to-Market: AI-driven document analysis reduces delays, expediting the delivery of legal guidance.
3. Prompt and Accurate Decision-Making: Adoption of AI ensures timely and precise results, facilitating quicker resolutions in legal matters.
4. Efficient Resource Allocation: Automation minimizes manual verification efforts, optimizing resource utilization and enabling focus on strategic tasks.
5. Strategic Market Positioning: Integration of advanced AI methodologies establishes the client as a frontrunner in the industry, providing a competitive edge.

Problem Statement

1. Manual & Time-Consuming Order Management: The client faced the arduous task of manually processing and managing orders and inventory through phone conversations, leading to inefficiencies and potential errors.
2. Language Barrier and Translation Challenges: Dealing with multilingual conversations created a language barrier, making accurate translation essential for effective communication and order processing.
3. Lack of Real-Time Visibility: Without an automated system in place, the client lacked real-time visibility into order status and inventory levels, hindering decision-making and responsiveness to changing demands.
4. Integration Challenges with ERP & Digital Platform: The absence of seamless integration with the existing ERP system and digital platform resulted in data silos and disjointed processes, causing delays and inaccuracies.
5. Dependency on Call Transcriptions: Relying on manual transcriptions of phone conversations introduced the risk of errors, misinterpretations, and data inconsistencies, leading to potential order fulfillment issues.

Solution Overview

1. OptiSol partnered with a leading paint manufacturer to automate their order & inventory management system, which previously relied on phone conversations between retailers and distributors.
2. Using OpenAI's Whisper, we effectively converted spoken Hindi conversations into accurate Hindi text, and then translated it into English with exceptional precision.
3. Our expertise in training and fine-tuning OpenAI's generative models enabled effective extraction of critical order-related details from noisy call transcripts.
4. The extracted details included product names, types, quantities, delivery dates, and quoted prices, providing valuable insights for streamlined order and inventory management.
5. Leveraging the extracted data in Json format, we seamlessly integrated it into the client's ERP system, ensuring a smooth and automated order and inventory management process.

Business Impact

1. Overcoming Low Digital Platform Adoption: The solution effectively tackled the challenge of low digital platform adoption, enabling the client to transition smoothly while continuing existing operations.
2. Improved Efficiency through Automation: By automating the tasks of telephone operators and manual transcribers, the client achieved enhanced efficiency in their order and inventory management processes.
3. Nationwide Adoption in Multiple Languages: The solution's implementation in multiple Indian languages facilitated widespread usage across the country, ensuring accessibility and inclusivity.
4. Enhanced Efficiency: The automated order and inventory management system streamlines the process, reducing manual efforts and increasing overall efficiency.
5. Improved Accuracy: By converting spoken conversations into accurate text and extracting critical details, the solution minimizes errors and improves data accuracy.

Problem Statement

Time-Consuming Process: Manually verifying government documents was a slow and laborious task, that caused delays in decision-making and processing.

Difficulty with Volume: When the volume of government documents was more, manual verification became more challenging and less efficient.

Risk of Missing Key Information: Critical clauses, obligations, and requirements may be overlooked during manual verification, posing compliance risks for the contractors.

Limited Scalability: The current process lacks scalability, making it difficult for the client to handle a larger number of government documents and expand their operations.

Increased Error Potential: Human errors in the manual verification process can lead to inaccuracies, potentially resulting in compliance issues and contractual disputes.

Solution Overview

We have worked with a leading startup in implementing a GPT based solution that parses documents, extracts content section by section, and organizes it based on clause numbers and other attributes.

Rulesets are created by identifying essential domain-specific keywords from sample documents.

Cosine similarity is used to match potential words to the ruleset, expanding the keyword list.

The system then extracts relevant paragraphs, sections, and sub-sections containing the identified keywords.

An API is built for easy access and continuous improvement of the model based on testing results.

Business Impact

Faster Contract Review: The GPT-based solution speeds up the contract review process, enabling quicker responses to opportunities.

Better Compliance and Risk Management: AI-driven key clause extraction ensures critical obligations are identified, reducing compliance risks and legal disputes.

Efficient Operations: The automated analysis allows the startup to handle more contracts efficiently, leading to cost savings and improved operations.

Informed Decision-Making: GPT provides valuable insights, empowering better strategic planning and decision-making.

Cost Savings and Resource Optimization: By automating certain tasks through GPT, the startup can reduce operational costs and optimize resource allocation.

Problem Statement

Unstructured Proposal Documents: Managing a large number of unstructured PDF proposals posed challenges in efficiently storing, searching, and extracting relevant information.

Complex Proposal Formats: Handling diverse proposal formats including text, tables, images, and graphics required consistent and effective processing methods.

Lengthy Proposals: Dealing with proposals spanning hundreds of pages hindered productivity and made it time-consuming to extract content for new proposals.

Inefficient Document Retrieval: Difficulty in quickly and accurately retrieving specific information from numerous proposals slowed down the proposal creation process and affected overall efficiency.

Content Repetition: Manual repetition of similar content in each proposal resulted in redundant efforts, increased error possibilities, and limited focus on higher-value tasks.

Solution Overview

We have worked with a Leading Construction service provider in developing a GPT based Proposal creation model that combines the capabilities of Adobe Extract API, image captioning, elastic search & and GPT-3 models.

We seamlessly integrated the Adobe Extract API into the system to fetch text, images, tables, and graphics from each PDF proposal, ensuring accurate extraction of relevant content elements.

Improved image searchability through the implementation of image captioning models, enabling proposal managers to efficiently retrieve and utilize visual content.

Elastic search implementation streamlined document management, enabling quick retrieval of relevant information from proposals.

Our custom trained GPT-3 text generation model enabled real-time generation of construction-related content, significantly expediting the proposal writing process with tailored content suggestions for proposal managers.

Business Impact

Efficient Document Search: The solution enables easy searching through a vast corpus of unstructured documents, saving time and effort for proposal managers.

Accelerated Proposal Writing: With the ability to generate tailored content in real time, the solution significantly increases the rate of overall proposal creation process, improving efficiency and enabling faster response times.

Enhanced Creativity and Quality: By providing creative prompts from generative models, the solution inspires proposal managers with new ideas, promotes creativity, and enhances the overall quality of the proposals generated.

Improved Proposal Consistency: The automated proposal generation process ensures consistency in content across various proposals leading to a professional and cohesive representation of the company's capabilities, enhancing brand image and credibility.

Competitive Advantage: The solution equips the client with a competitive edge, positioning them as a responsive and innovative company in the construction industry, enhancing their chances of winning contracts and securing new business opportunities.

Problem Statement

Limited Control over Source Selection: The client struggled with the inability to generate content exclusively from their desired sources, leading to a lack of control over the quality and relevance of the content produced.

Ineffectiveness of Fine-Tuning LLMs Fine-tuning language models for specific tasks has been common, but it's not as effective in preserving source-specific context and quality when generating content from a particular source.

Maintaining Source Authenticity: Ensuring content generated by advanced language models reflects the style, tone, and authenticity of a specific source is a challenging task to address.

Lack of Customization and Personalization Options: The client found it challenging to tailor the generated content to their specific requirements, resulting in a lack of customization and personalization options.

Difficulties in Scaling Content Generation: As the client aimed to generate a large volume of content, they encountered challenges in scaling their content generation efforts efficiently while maintaining quality and source specificity.

 

Solution Overview

OptiSol partnered with a leading Middle Eastern e-commerce service provider to create a Generative AI-based solution for customized blog content creation.

By implementing robust vector databases, we established a foundation for efficient retrieval and referencing of relevant content from the client's repository, supporting the content generation system.

Through the integration of embeddings into our language model, we enable intelligent content selection and seamless incorporation of the most relevant information from the repository based on user queries.

By adeptly extracting and consolidating information from the chosen content, our solution provides the seamless creation of comprehensive and captivating long-form blog posts, elevating the depth and richness of the generated content.

While we currently leverage advanced models like GPT-4, we anticipate the future adoption of self-hosted open source language models.

Business Impact

Enhanced Control over Content Sources: By leveraging the system's ability to utilize content embeddings from the client's specific repository, the client gains greater control over the sources of their blog content. They can ensure the content aligns with their desired standards, resulting in increased credibility and relevance.

Efficient Utilization of Local Data: The client can leverage local data without the need to retrain the entire system. This saves time and resources, allowing them to generate customized content using their existing knowledge base and expertise.

Transcending ``Black Box`` Training Data Limitations: Our system enables the client to transcend the limitations of training data by leveraging their curated and trusted content sources, delivering a more targeted and tailored experience to their audience.

Increased Content Quality and Relevance: By extracting and consolidating information from the client's repository, our solution enhances content quality and relevance, resulting in improved engagement, increased reader satisfaction, and a stronger online presence.

Competitive Advantage and Business Growth: With a content generation system that delivers customized, high-quality blog content, the client gains a competitive edge.