Frame AI Reviews

Frame AI has been best at giving us alerts when clients have need help that needs to be escalated to higher intervention

Sometimes there are false negatives but the longer we have worked with it, the less we have seen

This has been very helpful in letting us know when a client is unhappy and we need to step in to figure out how we can better serve our client.

We have been working with Frame AI for more than a year now, and we really appreciate their collaboration, professionalism, thorough follow-ups and support. So far, we have calibrated their product for 3 main use cases: Cost to Serve, Escalation Risk and Predicted CSAT, and are very satisfied with the product, which we use on a daily basis.

Being a very configurable environment, the initial lift requires some time and collaboration with employees to assess the amount of time spent on different tasks. Fortunately, Frame AI CSM was of great help and guidance throughout this process.

Since their product allows us to bring data points into other systems such as Salesforce CRM, we were able to build custom alerts in our system of choice to proactively review Support cases based on the above use cases. It also allows us to provide additional visibility to Support agents directly on their cases, allowing them to adjust their customer interactions quickly if needed.

There are two things that I like most about Frame.ai:

1. The power and flexibility of the tool. I'm continuously impressed with the ability of the tool to adapt to our numerous needs as a business. They always seem to be ready to jump into a new challenge no matter what we throw at them.

2. The people at Frame.ai are exceptional partners. They've been supporting us for years and have been huge advocates and allies during this time. We've come to them with many different use cases and they haven't shyed away from any challenge yet.

The tool can be difficult to configure and interpret without help. Thankfully, this hasn't been much of an issue for us as the Frame team has always been willing to assist.

Showcases opportunities for us to improve from a Support perspective in unlimited ways. Highly customizeable and the account team is fantastic as well.

The UI could be more intuitive and helpful.

Helping us understand where the pain is and how we can adjust our systems and processes to better target self-service.

One of the most useful features I find is the ability to auto-tag phrases as this removes a huge amount of manual effort to figure out what customers are asking and why. Such as customer escalation requests, when a customer requests an escalation, our leadership is notified right away via a Slack itegration.

I dislike some of the user interface customization and interactivity, it's a little confusing at times. However, the frame team has always been more than willing to help guide us along whenever we get stuck

The main problem Frame AI solves is the manual effort of reading each and every case to establish a trend or to find that needle in the haystack. Finding out how many customers experienced log4j issues for example, or how often are customers getting stuck performing a particular task. Typically the keyword search combined with some custom tags gets you the information you need - quickly.

The flexibility of the product and the types of insights we can search for is astounding! Alongside their exceptionally engaged success team, it's like having our own in-house data team who is available just for us.

The product itself is still finding its feet. It's frequently difficult to easily read or find the things we're looking for, and it's clear they are still figuring some things out in terms of a precise market fit, and what they want to be delivering.

Frame is helping us find and articulate narratives, pains, and patterns that we could only speak to anecdotally before.

I demoed Frame against a number of other AI / NLP-driven feedback tagging tools, and none came close to what Frame can detect and accurately analyze in a detailed feedback submission.

Setting up Frame to correctly work with your feedback (assuming any level of complexity) will take time, though the customer success + onboarding team is fantastic. The scores dashboard and visuals aren't exactly the easiest to navigate or look at. Loading times can be significant depending on your user traffic.

Tagging and acting on product feedback across a number of feedback channels, at scale. Benchmarking and baselining complex areas / features within our product and ensuring we act on those causing the most user friction.

Frame.ai not only provides us with what we request, they go above and beyond and treat us as a priority. George, Robbie and team are wonderful to partner with.

Based on the function I am currently utilizing Frame for I currently see no downside.

The quickness Frame is able to provide me with data has been extremely beneficial. Frame.

For us, the alternative to Frame would be a ticketing system (Zendesk, etc). We want the features of the ticketing system such as escalation and reporting, but we don't want to lose the personal feeling of support. Frame's ability to offer escalation and reporting while remaining completely out of the customer experience and only be present in our support engineer view was the selling point for us.

As a technical product, error messages pasted into Slack often trigger the NLP "negative" filters.

We were handling support requests in Slack, and starting to get overwhelmed and worried that we'd drop issues and lose valuable insights. The normal path is to move away from Slack and into Zendesk or other ticketing systems. Our team didn't want to lose the close contact and responsiveness that we had with Slack, but needed to get some of the reporting and escalation policies that a ticketing system had.

Frame.ai allows us to become much more proactive when solving member issues. They provide us the tools to uncover issues even before our members are aware of them.

We are still very early in our relationship with Frame and so far I do not have any negative issues.

We are proactively uncovering member issues and better understanding member sentiment across multiple engagement types. Frame.