XOVOX

Do you need access to voice data that is locked down by platforms like NICE, Genesys, Verint, or Red Box? XOVOX has a solution. Our flagship?XTRACT?service helps organizations?retrieve valuable data from voice archives, regardless of formatting. We retrieve call catalogs and audio from any source archive, including the cloud, files, tapes, disks, and relational databases, without ever needing access to your original software. Additionally, you can decide whether we extract all of your audio data or data from a specific channel or date range. After we extract your data, we convert it to an open format like WAV, making it readily accessible across platforms or for use in your AI initiatives. XOVOX XTRACT?is the ideal solution for organizations looking to retrieve voice data across your legacy platforms or both current or historical calls from your existing platform, and gives you the flexibility you desire. Don’t lose the value in your voice data. Contact XOVOX today. https://lnkd.in/eW_HtMS4

XOVOX, the leader in voice recording extraction and migration, announces a new capability to extract audio recordings and metadata from the VPI Empower platform. With this new capability, XOVOX can help companies move their voice recording data from VPI Empower systems into a new recorder or cloud-based archive. Data can be retrieved from both live and retired systems. VPI (Voice Print International) is a platform for recording and retrieving voice calls. Empower was originally released in 2009 and is used by financial institutions and telephone contact centers for compliance and quality assurance purposes. VPI was acquired by NICE in 2016 and Empower has subsequently been announced as “EOL” (end of life). VPI Empower now joins the extensive list of EOL recorder formats that XOVOX supports, including NICE 8.9, Eyretel Mediastore, Comverse Ultra, Racal/Thales/NICE Wordnet, Dictaphone Freedom, and many others. Once extracted, XOVOX can convert the voice recordings and associated metadata into accessible formats and systems for a variety of purposes, including: 1) Import into a new recording platform or audio archive 2) Upload to cloud storage for compliance, retention, and regulation statutes, e.g. GDPR, SEC 17a-4, MiFID 3) Speech analytics and artificial intelligence – Use your voice data to train your AI so you can deliver better products and services as well as generate business insights to improve customer service and support and enhance your marketing initiatives. “XOVOX has had several clients and partners asking us to export data from legacy VPI systems. This new capability enables us to extract directly from the VPI recorder file archive, without any need for the original running system. We can even extract from a damaged or crashed system,” said Andrew Stevens, President of XOVOX. “This latest addition to our roster of 40+ known recorder formats extends our leadership in the field.” To learn more about XOVOX, please visit us https://xovox.tech or email us at [email protected].

Unlocking the Power of Voice Data: XOVOX's Conversion and Normalization Services For businesses everywhere, valuable data is hidden and locked inside voice recordings. Unlike text messages or emails, voice recordings capture the speaker’s tone, inflection, pitch, and other distinctive characteristics. These characteristics make voice recordings unique and quite useful for business insights and even biometric identification purposes. Most companies with troves of voice data are subject data to complex web of regulations like GDPR, SEC 17a-4, and MiFID. But this data is confidential, not for outside consumption. And therein lies the challenge: How do you use this data internally while simultaneously sharing it to fulfill compliance requirements AND protecting it from hackers? ? XOVOX can help companies rapidly extract and normalize their voice data - whether it exists in disparate legacy or modern IVR systems. With nearly two decades of specialized expertise, XOVOX offers comprehensive solutions tailored to help organizations navigate the intricate landscape of compliance, security, and data accessibility. Conversion to a Single Format: Unlocking the full potential of voice data begins with standardization and consolidation. XOVOX empowers organizations to overcome compatibility issues, simplify data management processes, and ensure seamless integration with modern infrastructure and analytics platforms. XOVOX's conversion service streamlines the conversion of voice recordings from disparate formats into a standardized format. Normalization for Accessibility and Compliance: XOVOX ensures that voice data is optimized for accessibility, compliance, and analysis purposes. By normalizing voice recordings, organizations can mitigate the risk of compliance violations, enhance data accuracy, and extract actionable insights with greater speed and precision. Secure Storage and Data Protection: In addition to conversion and normalization, XOVOX prioritizes the security and protection of voice data and manages all voice recording data by using demonstrable and defensible chain of custody data management techniques. Client data is protected with state-of-the-art encryption, access controls, and robust data management practices. XOVOX offers archival services that ensure voice recordings are stored in a highly secure environment, safeguarded against unauthorized access, breaches, and manipulation attempts. Conclusion As regulatory requirements become more rigorous and data usage grows, effective management and protection of voice data is more important. XOVOX delivers comprehensive solutions for organizations seeking to unlock the power of their voice recordings and navigating the complexities of compliance. By standardizing, consolidating, and securing voice data, XOVOX empowers businesses to harness the full potential of this invaluable asset for critical business activities, including compliance/regulation, infrastructure upgrades, and analytics.

Structured vs. Unstructured Data - Part I Data is either structured or unstructured. It is not monolithic. And as businesses become more data-driven and are leveraging analytics and AI, the ability to harness these two distinct types of data together is essential. “Structured data” is data that fits neatly into tables and includes discrete data types such as numbers, text strings, and dates. Common examples of structured data include sales forecasts, airline reservations, and CRM systems. Structured data is often stored in Excel files or relational databases (SQL Server, Oracle, MySQL, etc.) On the other hand, “unstructured data” doesn't fit neatly into a data table because of its size or nature. For example, audio recordings, video clips, chats, legal documents, and newspaper articles are largely freeform and unpredictable and do not fit neatly into tables. Nevertheless, analysis and searchability of unstructured data is critically important in order to detect keywords, customer sentiment, discussion topics, and many more usages. Unstructured data is often stored in a “NO-SQL” database like MongoDB, AWS DynamoDB, and Azure Cosmos DB. Going a little deeper, here are some other ways you can distinguish structured from unstructured data. Defined vs. Undefined Data Structured data is clearly defined data in a structure, while unstructured data is usually stored in its native format. It lives in rows and columns and can be mapped into predefined fields. Unlike structured data, which you can organize and access in relational databases, unstructured data does not have a predefined data model and is undefined. Qualitative vs. Quantitative Data Qualitative data is generally unstructured data. Examples include customer surveys, interviews, and social media interactions. It cannot be processed and analyzed using conventional tools and methods; more advanced analytics techniques like data mining and data stacking are necessary to unearth what the data is telling you. Quantitative data is often structured data, meaning it usually consists of hard numbers or things that can be counted, like product information in a CRM.) Methods for analysis include regression (to predict relationships between variables), classification (to estimate probability), and clustering of data (based on different attributes). Data scientists and other data analysts can use these methods to generate business insights for your organization. That's it for now. Part 2 will discuss differences in formats, data storage, and ease of analytics.