Case Study

Scaling personalized, high-touch support at CAST AI to 100+ Slack Channels with ClearFeed

With Shravan Ashok, Principal Technical Program Manager &Anthony Velasco, Technical Support Engineer at CastAI
Kevin Carroll Profile Picture

Company Goal

CAST AI uses artificial intelligence to identify which compute resources are needed for specific Kubernetes workloads and automatically selects the best combinations, configuring CPUs and memory to prevent over-provisioning.

https://cast.ai/

HeadQuarters

Miami, FL

Industry

SAAS

Summary

CAST AI, a deep-tech product for SREs and DevOps engineers, focuses on a proactive and personalized support experience. They decided to choose Slack as a support channel for their customers. 

As the number of customer slack channels grew beyond 70, it became inefficient for the team to monitor so many channels and they struggled to stay on top of support SLAs. 

With the ClearFeed Slack-native ticketing system, they have been able to reduce response times and cater to more customers with a leaner team. They also have been able to set up a repeatable process that they can scale to more customers.

Introduction

CAST AI is an innovative cost optimization and infrastructure automation platform specializing in managed Kubernetes services. Built by a team with extensive expertise in Kubernetes, CAST AI primarily serves customers who are using managed Kubernetes providers such as AKS (Azure Kubernetes Service), EKS (Amazon Elastic Kubernetes Service), and GKE (Google Kubernetes Engine).

The platform is engineered to dramatically reduce the cloud bills of its clients, generally saving them between 40 to 60 per cent. CAST AI also focuses on automation, easing the workload by taking on much of the heavy lifting that would otherwise consume their time and resources.

The primary personas that use CAST AI are Site Reliability Engineers and DevOps professionals. The onboarding journey for CAST AI’s customers is a mission-critical implementation, as it involves changes to the customer's production cluster. This requires close coordination with the CAST AI support team through an instantaneous support model that facilitates troubleshooting and coordination.

We had a quick chat with the founding technical support engineering team at CAST AI (Anthony, Curtiss, Ronak and Shravan) to get more insights.

Slack as a Channel of Support

Choosing the right communication channel was vital for providing efficient and timely customer support. CAST AI decided to choose Slack as a medium for interacting with its customers. Below are the reasons why Slack emerged as the preferred channel over traditional methods like email or ticketing systems such as Zendesk or Intercom:

  1. Founder-Led Support Philosophy: CAST AI believes in a “founder-led support” philosophy, where key personnel, including the CTO, Director of Engineering, and VP of Customer Success, actively participate in resolving support tickets.
  2. Direct Engagement with Engineers: With Slack, CAST AI can have its engineers engage directly with customers. While they don’t want engineers who are deeply involved in code development to be frequently context-switching, they do want them to be close to the customers and experience customer pain points first-hand.
  3. Collaboration in Support: Traditional support systems often limit access based on the number of agent seats purchased. This model can lead to only a select few having access to the support platform, which is counter-intuitive to CAST AI’s approach of involving multiple roles in the support process.
  4. Immediate and Personalized Responses: Slack allows for real-time communication, enabling support teams to respond to customer queries almost instantly. Email or traditional ticketing systems usually have longer response times, which can lead to frustration and dissatisfaction among customers.
  5. High touch and white glove support: While implementing CAST AI, customers generally start with a few pre-production clusters and actively monitor cost savings. Over time as the customers gain more confidence, they scale the adoption to production clusters. With Slack-based support, the CAST AI team can be on standby and can operate like an augmented team available to their customers during implementation times which accelerates adoption.
  6. Higher visibility to leadership teams of customers: With Slack, the leadership team at the client’s end also has visibility into the progress of the implementation, which helps them move projects forward significantly faster.

Growing Challenges

As CAST AI grew and increased its reliance on Slack as a primary communication platform, several issues and challenges emerged. Here's a summary of the key challenges they faced while scaling their support operations on Slack:

  1. Missing messages: Initially, CAST AI found that using Slack for support led to quick issue resolution. However, as the number of channels increased beyond 70 channels, the team began missing replying to customer messages in time.
  2. Multiple Slack Workspaces: CAST AI uses two different Slack workspaces for their support efforts. Switching contexts between these two workspaces and finding the relevant channel for a particular conversation became overwhelming for the team.
  3. Lack of a Streamlined Support Process: With the expansion in channels and workspaces, the team lacked a unified view or a 'single pane of glass' from where they could manage all their customer issues and ensure everything is solved.
  4. Lack of Ticketing System Features: As the company grew, there was a clear need for features like SLA management, ownership and handover of specific customer issues and detailed reporting to manage and plan capacity better.
"More metrics, more info is always appreciated"

The ClearFeed Advantage

CAST AI evaluated many different products like Atlassian’s Halp, Zendesk’s Native Slack Integration and ClearFeed’s Slack Native Ticketing System. In the end, they decided to go ahead with ClearFeed because they wanted a tool that is very low friction for customers to use and is slack-native as their support and engineering teams are very collaborative.

Following are some of the features that have helped CAST AI:

  1. Centralized Triage Channel: Before ClearFeed, with over 70 channels, there was chaos in keeping track of which messages came in first, prioritizing them, and sometimes even losing track of messages. With the ClearFeed triage channel on Slack, all customer requests across channels are centralized in one place.
  2. Effective Prioritization of Customer Tickets: Before ClearFeed, the support teams were not clear about which tickets to prioritize before and were following the most recent messages on Slack. With ClearFeed, the support team has clear visibility into which issues have come in first and from which customers. This helps them prioritize better.
  3. Effective Handover with ClearFeed’s “Assignees”: CAST AI’s support team covers 4 different time zones. This needs effective handover of tickets between support engineers whenever the support shifts change. With ClearFeed, they are able to review the triage channel for all open issues and hand over ownership across support engineers with ClearFeed’s “Assignee” feature.
  4. Pricing Structure: Unlike traditional support tools that base the pricing on the number of agent seats, ClearFeed’s model is based on the number of customers that need to be supported. Support teams can easily loop in engineers and they can also directly resolve customer queries.

ClearFeed’s Impact & Partnership

CAST AI's partnership with ClearFeed has improved its support processes, making them more efficient and effective in managing customer conversations. The CAST AI team shared insights into how ClearFeed has been an invaluable partner in improving CAST AI's support services.

  • Increased Confidence to Scale Support on Slack: As CAST AI continued to grow, it went from 70 channels to 100s of channels in a matter of a few months. Without ClearFeed, managing this growth would have been chaotic. Curtiss and Ronak emphasized the confidence that ClearFeed instills in the team:

    "The first and foremost thing is that with ClearFeed we feel confident about adding more channels to Slack. Because we now have a process in place that we can rinse and repeat."
  • Decreased Escalations: Anthony highlighted how ClearFeed has reduced the noise on Slack, making it easier for the team to focus on resolving issues. He explains:

    "Feedback from our CTO and VP of Customer Success is unanimous that we see less noise due to escalations. There are fewer messages being missed, leading to lesser heartaches and fewer sleepless nights."
  • Effective First Level of Support: Shravan mentioned how since incorporating ClearFeed, the support team has streamlined and managed over 50% of the incoming conversations on Slack. He said:

    "Almost more than 50% of the incoming conversations on Slack have been streamlined and managed by the support team. So something that was exposed completely to our teammates on the engineering side now gets abstracted and handled by this first layer of support engineering."
  • ClearFeed’s Support & Feature Delivery: ClearFeed’s prompt customer support and agile feature delivery have been highly appreciated by CAST AI. The ClearFeed team has been extremely responsive, mirroring the same level of support that CAST AI aims to provide to their own customers.
"More metrics, more info is always appreciated"

Automated Answering Capability

One feature that CAST AI is interested in is integrating automated answering systems with a repository of past responses provided by the support engineering team, as well as using official documentation. ClearFeed has enabled this feature in the beta phase with the CAST AI team and they are actively trying out the feature. Here are quick comments from Shravan:

“It’s interesting to have a combination of a previous set of canned responses by the support engineering team for customer requests, and use the official Kubernetes documentation as input to the large language model to form a hybrid approach and be able to help our customers with automatic responses.”

Wishlist

Shravan Ashok shared the top two features that are on CAST AI's wishlist.

  1. Microsoft Teams Integration
  2. Measuring Customer Delight: Another aspect that CAST AI is keen on is a way to measure customer sentiment, specifically customer delight.

Our team is working hard to deliver these features and we look forward to working with the CastAI team to roll them out in the near future.

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