FAQ for homepage

What is Frame AI?

Frame AI is the leading Streaming Generative AI Platform for enterprise companies. Frame AI helps major brands and software companies transform unstructured data and natural language customer interactions into proactive insights, working through existing systems and infrastructure. Frame AI’s platform is the premier implementation of Stream-Trigger Augmented Generation (STAG), a breakthrough architecture designed to apply Generative AI to massive volumes of streaming data. Drawing on experience analyzing billions of customer interactions for leading technology and communications platforms, Frame AI empowers marketing, CX, and product teams with tailored AI strategies.

How does Frame AI transform unstructured data into proactive insights?

Frame AI leverages Stream-Trigger Augmented Generation (STAG) architecture to analyze massive volumes of unstructured data in real-time. By integrating seamlessly with existing systems and infrastructure, our platform processes streaming data to generate actionable insights, helping marketing, CX, and product teams make informed decisions and proactively address customer needs.

What is unstructured data?

Unstructured data refers to information that doesn’t have a pre-defined data model or isn’t organized in a predefined manner. Unlike structured data, which is typically stored in databases and easily searchable by algorithms due to its organized format, unstructured data encompasses a wide range of formats including text documents, emails, social media posts, videos, images, and audio files. This type of data is inherently more complex and varied, making it more challenging to analyze and process using traditional data tools. However, it holds significant value as it often contains rich, detailed insights that can be leveraged for deeper understanding and decision-making. The Frame AI Stream-Trigger Augmented Generation (STAG) architecture uses machine learning and natural language processing to extract meaning and actionable insights from unstructured data, enabling enterprises to tap into the wealth of information contained within.

What is Stream-Trigger Augmented Generation (STAG) and how does it benefit businesses?

Stream-Trigger Augmented Generation (STAG) is Frame AI’s groundbreaking architecture that applies Generative AI to massive volumes of streaming data. STAG proactively detects and triggers actions based on predefined business objectives, enabling real-time analysis and response. Businesses can automatically identify and address customer needs, compliance issues, and other critical areas as they arise. By leveraging STAG, enterprises can transform unstructured data into actionable insights, enrich their existing systems, and enhance workflows with predictive and generative AI, ultimately driving better business outcomes and operational efficiency.

Who can benefit from using Frame AI's platform?

Frame AI’s platform is designed to benefit enterprise teams in marketing, compliance, CX, and product teams. By transforming unstructured data into actionable insights, Frame AI empowers these teams to improve the efficiency of their customer data processes, enhance customer experiences, ensure regulatory compliance, and drive strategic product development. This leads to better decision-making, increased operational efficiency, and a more proactive approach to addressing customer needs and improving overall business outcomes.

How does Frame AI tailor its platform to the needs of every business?

Frame AI tailors its platform to the needs of every business by creating customized NLP models that detect and measure the specific metrics businesses already prioritize. Our platform processes and analyzes previously dormant unstructured datasets, transforming them into actionable insights. This enables enterprises to enrich their existing systems and workflows with predictive and generative AI.

How does Frame AI ensure the safety and security of my customer data?

Frame AI adheres to the highest standards of data governance and regulatory compliance. We align with industry best practices and regulations such as GDPR, CCPA, and HIPAA, ensuring data is managed with the utmost care and fully compliant with legal requirements. All customer data handled by Frame AI is encrypted both in transit and at rest using state-of-the-art encryption protocols. We implement rigorous access control measures, ensuring only authorized personnel can access sensitive information. This minimizes the risk of unauthorized access and data breaches. Additionally, Frame AI maintains SOC 2 certification, demonstrating our commitment to security, availability, processing integrity, confidentiality, and privacy of customer data. We also support a BYOC (Bring Your Own Cloud) approach, giving customers the flexibility to host their data within their own cloud environment, further enhancing security and control.

FAQ for Marketing

How does Frame AI enhance personalization?

Frame AI’s Stream-Trigger Augmented Generation (STAG) architecture enhances personalization by detecting what matters to customers in the information they share organically and consensually in emails, chats, and calls. By analyzing unstructured data and natural language strings from these interactions in real-time, STAG identifies specific needs, preferences, and traits that might not be apparent through traditional data collection methods. This allows businesses to move beyond generic personalization and offer relevant, individualized experiences that resonate deeply with each customer.

What does Frame AI detect in unstructured data?

Frame AI detects traits and triggers in unstructured data by using advanced Natural Language Processing (NLP) and machine learning. It can detect all sorts of things that impact purchasing decisions— demographic traits like marital status, life events like an upcoming move or job change, prefernces around communication, content, and product, competitor considerations, and more. Frame AI builds bespoke models that pick up the customer signals that matter to a given business and user. Frame AI synthesizes these signals to enrich profiles and trigger workflows.

What kinds of things can Frame AI trigger in my existing tools?

Frame AI triggers action at every end of the marketing automation spectrum, from profile enrichments to campaign engagements. A signal detected by Frame AI might result in an in-app notification, an email offer, or a future adjustment to existing marketing cadences. Frame AI works inside of existing marketing tools and CRMs, including Hubspot, Braze, Salesforce, Snowflake, and more.

How does Frame AI improve customer engagement?

Frame AI improves customer engagement by analyzing unstructured data from various customer interactions. This enables businesses to tailor their communications and offers in real time, ensuring that each interaction is highly relevant and personalized. This approach captures customer attention and fosters a stronger emotional connection, leading to increased engagement and loyalty.

How does Frame AI ensure data compliance?

Frame AI utilizes zero-party data by analyzing the information that customers willingly and proactively share during their interactions, such as preferences, intentions, and feedback expressed in emails, chats, and calls. This self-reported data provides a highly accurate and valuable insight into customer needs and desires. By leveraging advanced NLP and machine learning, Frame AI processes this zero-party data in real time, identifying specific traits and preferences that allow businesses to deliver hyper-personalized experiences.

How does Frame AI work with existing marketing tech stack and tools?

By connecting with CRM systems, email marketing platforms, and customer support software, Frame AI ingests data from various sources to provide a comprehensive view of customer interactions. It uses Natural Language Processing (NLP) and machine learning to analyze this data in real-time, uncovering valuable traits and triggers. This integration allows businesses to leverage their current tools while gaining deeper insights and automating personalized content and offers, resulting in more effective and cohesive marketing strategies.

How do you measure impact?

We participate in your existing ROI measurements, integrating seamlessly with the metrics on which you already report. By enhancing the data you collect with deeper insights and more granular analysis, Frame AI amplifies the value of your current KPIs without requiring you to adopt new measurement frameworks. This approach ensures that you can easily track the impact of our solutions within your established performance indicators, demonstrating clear value and effectiveness in a familiar context.

FAQ for Compliance

How does Frame AI support compliance and integrate with my compliance management system?

Frame AI integrates seamlessly with your compliance management system (CMS) to enhance your compliance capabilities and manage a variety of regulations, including Know Your Customer (KYC), Anti-Money Laundering (AML), the Bank Secrecy Act (BSA), Dodd-Frank, and Unfair, Deceptive, or Abusive Acts or Practices (UDAAP). By leveraging advanced natural language processing (NLP) and machine learning, Frame AI detects customer complaints and makes complaint trends visible, allowing you to address them proactively. This independent monitoring capability ensures better script adherence and complaint management, helping you avoid potential compliance issues and maintain regulatory compliance effectively.

How does Frame AI ensure the safety and security of my customer data?

Frame AI’s BYOC (Bring Your Own Cloud) architecture works by seamlessly integrating with our customers’ preferred cloud service providers, ensuring that all data processing and storage remain within the customer’s own secure cloud environment. This approach maintains data security and compliance by keeping sensitive information within the customer’s control, protected by end-to-end encryption and secure access controls. Additionally, Frame AI adheres to SOC 2 and HIPAA standards, ensuring the highest levels of data protection and regulatory compliance. The flexible deployment options allow businesses to configure and customize the integration based on their specific needs, leveraging their existing cloud infrastructure while benefiting from Frame AI’s advanced data analysis and compliance capabilities.

How does Frame AI assist in regulatory reporting?

Frame AI assists in regulatory reporting by automatically generating detailed reports that align with CFPB standards based on the analysis of customer interactions and data analysis. The platform compiles and structures the necessary information to meet various regulatory requirements, ensuring accuracy and compliance with agency guidelines. This automation reduces the administrative burden and ensures that all relevant compliance data is captured and documented, providing a streamlined and efficient process for regulatory compliance.

How does Frame AI support compliance training?

Frame AI supports internal compliance training by providing insights into common compliance issues and areas where employees might need additional guidance. By analyzing interactions and identifying recurring compliance-related themes, the platform highlights areas for improvement and informs training programs. This data-driven approach helps businesses tailor their training efforts to address specific compliance challenges and enhance overall awareness and adherence to regulatory standards.

How does Frame AI ensure seamless integration with existing compliance systems?

Frame AI ensures seamless integration with existing compliance systems by offering flexible API connections and compatibility with significant compliance and regulatory tools–allowing businesses to incorporate Frame AI’s advanced data analysis and compliance monitoring capabilities into their current workflows without disrupting existing processes. By enhancing the functionality of existing systems, Frame AI helps businesses maintain robust compliance monitoring and reporting while leveraging their current infrastructure.

FAQ for Support/CX

How does Frame AI help with prioritization and resourcing for CX leaders?

Frame AI helps CX leaders prioritize and allocate resources effectively by using Dynamic Cost Attribution to quantify the cost of every issue. By analyzing unstructured data from customer interactions in real-time, Frame AI identifies urgent issues and high-cost areas, enabling leaders to make informed decisions on where to focus their teams’ efforts. This approach ensures that resources are directed to the most impactful areas, optimizing efficiency, reducing resolution time, and minimizing agent effort.

How does Frame AI help reduce escalations?

Frame AI helps reduce escalations by detecting potential issues early and triggering actions based on predicted escalation risk. Utilizing advanced natural language processing (NLP) and machine learning, Frame AI identifies signals of dissatisfaction or frustration in customer interactions. By alerting support teams to these signals, Frame AI enables proactive intervention, addressing problems before they escalate and ensuring quicker resolution, which reduces agent effort and enhances the overall customer experience.

How does Frame AI improve CSAT scores?

Frame AI improves Customer Satisfaction (CSAT) scores by using signals from customer data to predict and enhance interactions. By analyzing customer communications in real-time, Frame AI identifies specific needs, preferences, and potential issues, allowing support teams to tailor their responses and solutions. This personalized and proactive approach leads to higher satisfaction, as customers feel understood and valued, directly boosting CSAT scores. Additionally, by reducing resolution time and agent effort, Frame AI ensures that customers receive timely and efficient support.

How does Frame AI make Support/CX teams more proactive?

Frame AI makes Support/CX teams more proactive by continuously monitoring customer interactions and detecting emerging trends and issues. By leveraging real-time data analysis, Frame AI triggers actions based on predicted CSAT scores, escalation risk, churn risk, and more. This proactive stance enables teams to address potential problems before they become significant, reducing the likelihood of escalations, minimizing resolution time, and enhancing overall customer experience while lowering agent workload.

What can Frame AI detect in unstructured data?

Frame AI detects various signals in unstructured data, including customer sentiment, pain points, emerging trends, and compliance issues. It identifies demographic traits, life events, preferences, and competitor mentions, among other things. Frame AI synthesizes these signals to trigger actions based on predicted outcomes such as CSAT scores, escalation risk, churn risk, and cross-sell opportunities, providing valuable insights that enrich customer profiles, inform strategic decision-making, and streamline support processes to reduce resolution time and agent effort.

How does Frame AI improve agent effort?

Frame AI improves agent effort by providing actionable insights derived from customer interactions. By analyzing real-time data, Frame AI identifies critical signals and triggers actions that streamline the support process. This reduces the time and effort required to identify and address issues, allowing agents to focus on delivering high-quality service. Consequently, agents can work more efficiently and effectively, increasing job satisfaction, faster resolution times, and better customer outcomes.

FAQ for Product

How does Frame AI help product leaders prioritize development and resource allocation?

By analyzing unstructured data in real-time, Frame AI uncovers critical insights and trends that highlight the most impactful areas for improvement. This quantification allows product leaders to make data-driven decisions, ensuring that resources are allocated to high-priority enhancements and optimizations. By focusing on issues that have the most significant cost implications, Frame AI enables product teams to maximize efficiency, streamline development processes, and deliver features and fixes that drive the most value for customers.

What types of unstructured data does Frame AI analyze to improve product quality and user experience?

Frame AI analyzes support tickets, calls, and emails which provide detailed information on recurring issues and common pain points, helping to identify critical bugs or features that require attention. By synthesizing these data sources, Frame AI identifies key trends and areas for improvement, enabling product teams to make informed decisions that enhance overall product quality and user experience.

How can Frame AI trigger actions based on product feedback and customer sentiment?

Frame AI can trigger actions based on key indicators like predicted CSAT scores, escalation risk, and churn risk. For instance, if the analysis detects a recurring issue with a feature, Frame AI can trigger an alert to the product team to prioritize a bug fix. Similarly, if customer sentiment indicates high satisfaction with a new feature, this feedback can prompt further development or enhancements. By providing real-time insights and alerts, Frame AI ensures that product teams can take targeted actions, such as implementing feature updates, addressing critical bugs, or refining user experience, ultimately leading to a more responsive and customer-focused product development process.

How does Frame AI integrate with existing product management tools?

Frame AI integrates seamlessly with existing product management tools such as Jira, Trello, and Asana. This integration process involves securely linking Frame AI’s advanced analytics capabilities with the product management system, allowing real-time data flow between the two. Frame AI enriches the data within these systems by analyzing unstructured customer interactions, such as support tickets, calls, and emails, and extracting valuable insights related to customer sentiment, recurring issues, and feature requests. These insights are then automatically fed into the product management tools, enhancing the existing data with deeper, context-rich information. This seamless integration enables product teams to have a more holistic view of customer feedback and pain points, leading to more informed decision-making and prioritization of development efforts.

How does Frame AI measure impact and ROI?

Frame AI measures impact and ROI by integrating seamlessly with your existing metrics and performance indicators, eliminating the need for new measurement frameworks. By enhancing your current data with deeper insights and more granular analysis, Frame AI quantifies the cost and benefit of each issue and action through solutions like Dynamic Cost Attribution. This allows businesses to track improvements in key areas such as CSAT scores, escalation reduction, and resource allocation efficiency. By participating in existing ROI measurements, Frame AI ensures that you can clearly see the value added by its advanced analytics and proactive insights, demonstrating tangible improvements in operational performance and customer satisfaction.

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