Overview
Once, financial institutions could rely on location to drive loyalty. Now, growing digital access means people are not limited to local providers, leaving businesses in a race for primacy. Acquiring and retaining customers with so many comparable options requires banks to know what their customers need, when they need it.
How? The typical financial institution spends significant resources communicating with customers across a growing number of channels, each managed through distinct tools and teams. The unstructured data collected from these interactions can constitute up to 80% of total enterprise data, holding critical insights about customer opportunities, operational costs, and compliance risks. Yet this data remains untapped, siloed within individual teams and transactions.
Our breakthrough Stream-Trigger Augmented Generation (STAG) architecture applies advanced AI to unlock the hidden value of this data in real-time. By identifying, labeling and scoring key moments and trends and vital information that impact teams across the enterprise, Frame AI orchestrates contextualized customer intelligence in existing tools and processes to maximize the ROI of your data investments.
For Marketing, Frame AI enriches customer profiles with traits and banking lifecycle events detected in customer conversations to target high-value cross-sell and upsell opportunities, allowing financial institutions to tailor their existing automated campaigns to real-time, individual needs, optimizing conversion and increasing lifetime value.
For CX and Support, Frame AI continuously monitors customer interactions, detecting churn risks, cross-sell opportunities, and CSAT trends. With automated quality assurance and real-time alerts, it helps prioritize critical issues, reduce customer effort and escalations, and improve agent efficiency.
For Compliance, Frame AI ensures regulatory adherence with real-time monitoring and adaptive risk management. Automated documentation and anomaly detection help financial institutions stay ahead of audits and compliance breaches, reducing legal exposure.
Frame AI delivers a feature-rich, customizable platform that amplifies existing tools and processes. Our custom NLP models turn unstructured data into actionable triggers, scaling the impact of your enterprise data without the need for new infrastructure.
For custom pricing, contract terms, or additional features, contact sales@frame.ai .
Highlights
- Leverage custom NLP models to monitor customer communication against functional objectives to power real-time interventions and automation
- Enable every team to stay ahead of risks and opportunities with actionable, contextualized customer intelligence in the tools they already use
- Automate documentation and quality assurance to reduce manual effort and ensure consistent, scalable processes across the enterprise
Details
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Pricing
Dimension | Description | Cost/12 months |
|---|---|---|
Frame AI | Enterprise platform fee | $150,000.00 |
The following dimensions are not included in the contract terms, which will be charged based on your usage.
Dimension | Description | Cost/unit |
|---|---|---|
frame_usage | Usage Overage (beyond included) | $0.01 |
frame_solutions | Custom Solutions (as contracted) | $1.00 |
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All fees are non-refundable and non-cancellable except as required by law.
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Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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An Enterprise Support Package is included for all Frame AI Customers
Please reach out to sales@frame.ai with any questions or for options on contract or pricing terms.
support@frame.ai
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Helpful AI System for Alerts
Frame AI System
Data-Driven Insights and Proactive Escalation Intervention
- Informing stakeholders regarding account sentiment outliers
- Guiding strategic product decisions using cost and sentiment data on key features
- Keeping escalation ratios at an industry low .56%while holding Support team to high CSAT standards
With the data Frame provides, we're able to proactively start and drive discussions with our PDE teams that lead to a deeper understanding of true customer sentiment and pain points regarding our most adopted features. With Frame's Predictive CSAT and Pre-Escalation scores, we're able to identify customer escalations before they happen and get the appropriate resources in the room quicker to resolve high level items of concern for our clients.
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Proactive Services Insights Powered by AI
In terms of Cost to Serve, their highly customizable product factors allowed us to start looking into outliers quickly; cases that cost us more time and money to support than the average can now quickly trigger a collaboration discussion with other teams such as R&D, including actual data points from Frame AI to add weight to the conversation. Relying on the signals they detect is much more reliable than estimates from the Support agents themselves in the end. Within a year, this approach allowed us to lower our cost to serve by 24% (so far!)
Escalation Risk alerts combined with other minor adjustments allowed us to reduce escalation requests by almost 50%. Proactively reviewing cases with experts and helping Support agents proactively also has a positive impact on the overall customer satisfaction, which went up by 4.2% in the last year.
Predictive CSAT is based on signals collected on ALL Support cases received, versus the 15% of formal transactional survey responses we receive from customers. Both scores are aligned within 1% difference, which means we can trust the value predicted by Frame AI and be more confident in showing up this value to leadership as it is based on much larger scale than actual surveys.
They are introducing Case Summary capabilities through AI, which we trialing at the moment and are very satisfied with the results, which also include coaching tips for the agents based on the case interactions. Once again, those data points are made available to us, so we can reuse them in our Reporting, automations, continuous improvement initiatives and transparently display it to Support agents as well.