UC2 – Smart data collection to improve NPL data tapes management

By altilia on January 27, 2023
By altilia on January 27, 2023

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How to leverage unstructured data with AI

Introduction In today's digital landscape, businesses are drowning in data, but starving for insights. Gartner reports that 90% of new enterprise data is unstructured, growing three times faster than structured data. Yet, a 2019 Deloitte survey found only 18% of organizations effectively leverage these information. For the financial sector, transforming unstructured data laying in legal contracts into actionable insights is a complex and costly work that requires highly specialized analysts to organize data into user-friendly graphs. But is this the only available solution?  Altilia's smart Knowledge Base solution offers a powerful answer. Our platform tackles the unstructured data challenge, turning the information into a competitive advantage. Whether you're an accountant juggling diverse client information or a financial analyst reading countless contracts, Altilia's smart knowledge base could be the key to unlocking your data's true potential. Join us as we explore how Altilia's solution can help you harness the power of unstructured data, streamline processes, and drive informed decision-making in an increasingly data-driven world.   Introducing Altilia's Smart Knowledge Base Altilia's Smart Knowledge Base is our answer to the unstructured data problem. It's a powerful tool that turns messy, scattered information into useful, organized knowledge. But, what is a smart knowledge base? Think of it as an intelligent digital library. Unlike a regular database that just stores information, a smart knowledge base can understand, organize, and even use the information it contains. Therefore, the library not only stores everything you upload, but also makes connections between different pieces of information, answers your questions, and even helps you make decisions. That's what makes it "smart" – it doesn't just hold knowledge, it actively helps you use it. How is Altilia's solution different from other solutions?  Gathers All Your Data: Our system collects information from many different places. It doesn't matter if it's scanned papers, emails, or database entries - our platform brings it all together in one place. Understands Your Information: Our AI doesn't just read your data, it understands it. It can make sense of complex documents, pull out important details, and even grasp context and subtle meanings. Easy to Use: You don't need to be an AI expert to use our platform. We've made it simple. There's a search bar to find information quickly, and you can ask questions in your native language. Works Automatically: Once the setup of a workflow is completed, our system can do complex tasks on its own. It can take the new documents that have been uploaded, extract information from them, and even create detailed reports without the need to personally go through each step.  Trustworthy: We know the quality of the result is important, especially when writing a report or a legal document. That's why our system can show you how it reached its conclusions. This is crucial for businesses that need to follow strict rules. By combining these features, Altilia's Smart Knowledge Base changes how you use your data. It's not just about storing information - it's about making that information work for you. It helps you gain insights, work more efficiently, and make better decisions across your entire organization.   The Financial Analyst's Challenge Meet Sarah, a seasoned financial analyst working for a large investment firm. Sarah's job involves analyzing complex reports from rating agencies to guide investment decisions. Let's see how Altilia's Smart Knowledge Base transforms her workflow and solves her data analysis dilemma. Sarah's Typical Day Before Altilia: Information Overload: Sarah receives a comprehensive report from a major rating agency: A 200-page PDF document with text, tables, and graphs Supplementary data in spreadsheets Some reports are inside data silos, making difficult to retrieve the correct information Related news articles and press releases Time-Consuming Analysis: Sarah spends days: Manually reading through the lengthy report Copying data from PDFs into spreadsheets for analysis Cross-referencing information with past reports and news Risk of Oversight: With so much information to process: Important details might be missed It's challenging to spot trends across multiple reports Connecting related information from different sources is difficult Delayed Insights: Because the analysis takes so long, Sarah often struggles to provide timely investment recommendations to her team. Sarah's Transformed Workflow with Altilia: Centralized Information: All the information, regardless of its original format, is now in one place: The PDF report is automatically processed and its content extracted Spreadsheet data is integrated into the system Relevant news and press releases are collected and linked Automated Information Extraction: Altilia's AI does the heavy lifting: Automatically reads and understands the entire report Extracts key data points, trends, and risk assessments Organizes all information into a structured, easily searchable format Intelligent Search: Sarah can now find any piece of information in seconds: Uses natural language queries like "Show me all companies with a credit rating downgrade in the last quarter" The system understands context, finding related information even if it's not explicitly mentioned Automated Analysis: The platform generates insights automatically: Compares current ratings with historical data Identifies trends and anomalies in the agency's assessments Creates visualizations of key financial indicators Enhanced Accuracy: With AI-powered analysis, the risk of oversight is significantly reduced: The system cross-references information from different sections and sources Any unusual data points or discrepancies are flagged for human review Sarah can always double check the results proposed by the AI Agent and the resources used. Faster Insights: Sarah now spends less time on data processing and more on high-level analysis: Quickly identifies key trends and potential investment opportunities Provides more timely and comprehensive recommendations to her team The Result: With Altilia's Smart Knowledge Base, Sarah transforms from a data processor into a strategic advisor. She can analyze reports more thoroughly, provide faster insights, and add more value to her firm's investment decisions. The investment firm benefits from more timely, accurate, and insightful financial analysis, helping them make better investment choices in a fast-paced market.   What's Next for Unstructured Data? The world of data is changing fast, and unstructured data is leading the charge. So, what's coming next? Here's our insights into the future: Smarter AI: Imagine AI that can understand data like a human, but faster and without getting tired. That's where we're heading and we are working on an AI that can make sense of even the trickiest information. Speed is Key: In the future, waiting for answers will be old news. We're moving towards systems that can give you insights right away, as soon as new data comes in. Keeping Data Safe: As we use more data, keeping it safe becomes super important. Future systems will need to be like a fortress for your information, while still making it easy for you to use. Data for Everyone: You shouldn't need a PhD to understand your data. We're working towards a world where anyone can ask questions and get answers from their data, as easily as using a search engine. Contrary to what it might look like, the future of data is exciting, and a bit wild. There will be more data than ever, coming from places we can't even imagine yet. But with the right tools, like Altilia's Smart Knowledge Base, you won't just keep up – you'll be ahead of the game. Ready to step into the future of data management? Let's turn your data challenges into your biggest strengths, today and tomorrow. Book a call with our experts to explore how Altilia’s smart knowledge base might fit your business.

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Data Manager Online: AI-Powered Solutions for Unstructured Data

Data Manager Online: AI-Powered Solutions for Unstructured Data

Harnessing the power of unstructured information means taking full advantage of up to 80% of a company's digital assets. Data Manager Online, a leading Italian technology publication, recently featured Altilia in an article exploring innovative solutions for dealing with unstructured data.  In the article "Unstructured Data? Altilia has the solution", Massimo Ruffolo, CEO and Founder of Altilia, gives a glimpse into a future where advanced AI doesn't just process documents - it turns them into actionable insights, transforming the way companies across industries manage, interpret and use their most valuable resource: information. Key Insights from the Article 80% of business data is unstructured: Unstructured data makes up the vast majority of an organization's information assets and is growing exponentially, and managing this vast amount of information is a significant challenge facing every modern organization. AI transforms documents into actionable insights: Altilia's technology, including Generative AI, enables more sophisticated data control and automated document creation through 'active insights', turning raw and unstructured information into valuable knowledge that can be shared across the organization. Built to adapt to the needs of any industry: Customized AI assistants are designed to adapt to the unique needs of specific industries - from banking to pharmaceuticals - the platform addresses each domain-specific knowledge and process-specific requirements to ensure optimal performance. Humans and AI: Altilia's reinforcement learning approach allows humans to review the actions of AI assistants and provide feedback to train them for future processes. This continuous learning enables the AI system to improve its performance over time. One Platform to Rule Them All: The single solution approach simplifies the management of unstructured data for organizations, eliminating the need for multiple tools and streamlining operations.   As the digital landscape evolves, Altilia promotes an ethical and responsible approach to AI adoption, contributing to the future of work by embracing technological revolutions in Italy. Click here to read the full article (in Italian).

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Altilia - The state of AI adoption in businesses: Trends and insights

The state of AI adoption in businesses: Trends and Insights

Introduction: With an explosive annual growth rate of 37.3% (Grand View Research), AI is reshaping the way industries operate and innovate. From global tech giants to highly regulated sectors, businesses are racing to exploit AI's potential. But this AI race isn't just about releasing the most technologically advanced solution; it's a dance between innovation and responsibility. This article takes you on a journey into the AI-driven business world, exploring how companies are moving from AI experiments to deployments, the rise of open-source models, and the push for customized AI solutions. We'll uncover why the most regulated industries are becoming AI pioneers and how businesses are addressing consumer concerns while pushing the boundaries of what's possible. The Point of View of Consumers: Let’s start from the pain points: how consumers see AI. While the adoption of AI solutions from businesses accelerates, consumers approach the integration of AI in business with a mix of curiosity and caution. While many appreciate the enhanced personalization and efficiency that AI can bring, concerns about data privacy, job displacement, and misinformation persist.  Interestingly, a survey made by forbes points out that 65% of consumers say they'll still trust businesses that use AI, indicating a general acceptance of this technology.  Despite AI's potential, many people are concerned about the technology. To build trust and maintain good relationships with customers, companies using AI must openly address these concerns. Successful AI development and adoption requires carefully balancing innovation with ethical considerations.   The AI Use Cases Driving Adoption: As artificial intelligence rapidly transitions from buzzword to business assets, organizations are strategically identifying the most impactful areas for AI integration. The landscape of AI implementation is diverse, reflecting the technology's adaptability to various industry challenges and operational needs. While the potential applications of AI are vast, certain use cases are emerging as clear frontrunners in the race for digital transformation. A recent IBM study sheds light on the AI priorities of today's businesses, revealing a focus on enhancing operational efficiency, bolstering security, and augmenting decision-making processes. Let's explore the top 5 AI applications: Automation of IT processes (33% of surveyed companies) Security and threat detection (26% of surveyed companies) AI monitoring or governance (25% of surveyed companies) Business analytics or intelligence (24% of surveyed companies) Automating processing, understanding, and flow of documents (24% of surveyed companies)   The Shift from Experimentation to Production: The State of Data + AI report made by Databricks reveals a significant shift from AI experimentation to production. Remarkably, there's been an 11x increase in AI models deployed into production compared to last year. Organizations have become 3x times more efficient at deploying models, indicating a maturing AI landscape. This increased efficiency is largely due to the emergence of data intelligence platforms, which provide a unified environment for the entire AI lifecycle – from data preparation to model deployment and monitoring.   The NLP Revolution: Natural Language Processing (NLP) has emerged as a transformative force in AI applications, revolutionizing how machines understand and interact with human language. At its core, NLP is the technology that allows AI systems to read, decipher, understand, and make sense of human languages in a valuable way. Its popularity relies on its wide-ranging applications across industries and its ability to bridge the gap between human communication and computer understanding. The State of Data + AI report reveals that NLP is not just growing—it's dominating. With 50% of specialized Python libraries used in AI applications associated with NLP, it has become the most utilized and fastest-growing machine learning application. This surge in adoption is driven by NLP's versatility and its potential to solve complex, language-related challenges. In healthcare, NLP is accelerating clinical research by analyzing vast amounts of medical literature and patient records, leading to faster drug discovery and more personalized treatment plans.  Financial institutions are leveraging NLP for sentiment analysis of market reports, automated trading based on news, and enhanced customer service through sophisticated chatbots.  Retailers are using NLP to analyze customer reviews, improve product recommendations, and create more intuitive voice shopping experiences. The power of NLP lies in its ability to make sense of unstructured data—like emails, social media posts, customer feedback, and recorded conversations—which constitutes up to 80% of enterprise data. By turning this unstructured information into structured, actionable insights, NLP is enabling businesses to tap into previously underutilized data sources, leading to better decision-making and more personalized customer experiences. Moreover, advancements in NLP, particularly with the rise of transformer models like BERT and GPT, have dramatically improved machines' ability to understand context and nuance in language. This has opened up new possibilities for more natural human-computer interactions, from more accurate machine translation to AI-powered content creation and, as NLP continues to evolve, its integration with other AI technologies like computer vision and sentiment analysis is creating even more powerful tools for businesses.    Open-source LLMs: The adoption of open-source Large Language Models (LLMs) is rapidly gaining momentum in the business world. According to the State of Data + AI report, 76% of companies using LLMs are choosing open-source options, often alongside proprietary models. This shift is driven by several key factors: Customization and Control: Open-source LLMs allow businesses to fine-tune models to their specific needs and industry requirements. Cost-effectiveness: These models offer a more affordable solution, especially for smaller businesses or those new to AI. Transparency and Trust: The ability to inspect the code builds trust, crucial for regulated industries. Rapid Innovation: Open-source communities drive fast-paced improvements and new features. Flexibility in Deployment: On-premises or private cloud deployment options offer greater control over data and compliance. The report also reveals a preference for smaller models, with 77% of users choosing LLMs with 13 billion parameters or fewer (GPT4 has 1.76 trillion parameters). This indicates a focus on balancing performance with cost and latency. Highly regulated industries are the unexpected AI Pioneers: Contrary to expectations, highly regulated industries such as Financial Services and Healthcare are at the forefront of AI adoption. Financial Services leads in GPU usage, with an 88% growth over six months, indicating a strong commitment to LLM applications. Meanwhile, Healthcare & Life Sciences are among the top adopters of foundation model APIs, leveraging AI for everything from drug discovery to patient care optimization. The reasons are of course mixed: Data Advantage and Necessity: These industries possess vast amounts of valuable data and face complex challenges that AI is well-suited to address. Risk Management and Compliance: AI offers powerful tools for enhancing risk assessment, fraud detection, and streamlining compliance processes, which are critical in regulated environments. Competitive Pressure and Customer Expectations: The potential for AI to provide a competitive edge and meet increasing demands for personalized, efficient services is driving adoption. Resources and Impact Potential: These industries often have the financial capacity to invest in AI, and the potential impact of AI in these sectors (e.g., improved financial advice, more accurate medical diagnoses) is significant. What is “RAG” and why businesses are using it: Let’s start from the definition: Retrieval augmented generation (RAG) is a GenAI application pattern that finds data and documents relevant to a question or task and provides them as context for the LLM to give more accurate responses. Businesses are increasingly focused on personalizing an AI to their specific needs. RAG’s techniques allow businesses to create AI systems that truly understand and operate within their specific contexts, driving innovation and competitive advantage across various industries.This is evidenced by the staggering 377% year-over-year growth in vector database usage, which is crucial for RAG applications (Databricks, 2024). This surge in adoption is driven by several benefits: Enhanced Accuracy: RAG allows businesses to augment LLMs with their own proprietary data, leading to more accurate and contextually relevant outputs. Reduced Hallucinations: By grounding LLM responses in verified information, RAG significantly reduces the risk of AI hallucinations, increasing reliability. Real-time Knowledge Integration: RAG enables the integration of up-to-date information without the need for constant model retraining, keeping AI responses always updated. Cost-Efficiency: Compared to fine-tuning large models, RAG offers a more cost-effective way to customize AI outputs for specific business domains. Improved Compliance: For regulated industries, RAG provides better control over the information sources used by AI, aiding in compliance efforts. Scalability: As businesses grow, RAG can easily incorporate new data sources, allowing AI systems to evolve with the company. Preservation of Proprietary Knowledge: RAG allows companies to leverage their own data assets without exposing this information during model training. To know more about how Altilia is leading the development and implementation of personalized RAG solutions, read this article.   Conclusion: The experimentation of AI in businesses is well underway, with applications spanning from improved efficiency to enhanced customer experiences. While challenges remain, particularly around consumer trust and ethical considerations, the potential benefits of AI are tangible. As we move forward, it's crucial for businesses to embrace AI innovation responsibly. By addressing consumer concerns, prioritizing transparency, and leveraging AI's capabilities ethically, companies can harness the transformative power of AI to drive growth and create value in the AI-driven economy of the future.

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