The Silicon Review
Over the last twenty years, technology has come a long way. However, amidst the fast-paced world of DevOps and ever-evolving software releases, customer support – the tech stack's unloved cousin – has been lagging behind. Customer expectations have never been higher, but there's a missing link in the chain.
When new software is released, the company – rather than customers – should be the ones to flag faults. Support should be kept up-to-date with product changes and equipped with the technical skills required to be able to solve customers' problems on the front line.
IrisAgent's proactive AI-powered customer support and product intelligence capabilities move companies beyond 'shoulds.' Your customers' support experience doesn't have to be tarnished by product-related delays, outages, and performance issues. IrisAgent platform proves it.
We interviewed Palak Dalal Bhatia, Founder of IrisAgent, who explained to us the importance of combining breakthrough technology with deep expertise in customer support to deliver sheer quality for its customers. Read on for the excerpts from the interview.
Q. What makes IrisAgent unique?
With our AI-powered auto-responder capabilities, we take simple, repetitive tickets off your support team’s plate to enable them to focus on more complex issues. However, we’re more than just a chatbot. Unlike other players in this space, we take a 360-degree view of customer support operations by using product and user context to gain meaningful insight into the ‘why’ behind tickets associated with bugs, performance issues, and outages. With this knowledge, we help companies create support workflows, recommend operational improvements, and flag potential issues before customers discover them.
Our results speak for themselves. For example, when a leading enterprise SaaS company implemented IrisAgent across support operations, they gained powerful visibility into problem areas and bottlenecks, enabling them to take action that saw their CSAT score increase and ticket MTTR decrease respectively.
Q. What does innovation mean to IrisAgent?
Customer expectations have never been higher, but there’s a missing link in the chain. Support teams are often reactive to customers’ needs because they’re unaware of customer-impacting product issues, bugs, and launches.
IrisAgent proves that innovation doesn’t have to be synonymous with disruption by providing support teams with the most profound understanding of trending issues affecting (or may affect) customers.
In today's fast-paced world of DevOps and ever-evolving release cycles, “failure” – outages, performance issues, and bugs – is inevitable. However, delays, engineering escalations, and poor customer experience are not.
At heart, IrisAgent’s mission is simple: make customer support better for everyone. Our platform brings people together by providing customer support and product and engineering teams visibility into bottlenecks and problem areas.
Q. How important is the role of AI to what you deliver?
IrisAgent is a proactive customer support platform that resolves customer tickets and issues efficiently and effectively using Machine Learning (ML), Natural Language Processing (NLP), and Artificial Intelligence (AI). The goal is to help customer support teams save companies time and money. IrisAgent speeds up the time to resolution for customer support cases caused by outages, bugs, and performance issues.
IrisAgent not only detects early product issues but also uses Machine Learning to find the root cause of product issues. Support agents can get an overview of recent and ongoing incidents that are caused by a particular incident. They can quickly identify the root cause and, with the help of IrisAgent’s workflow automation capabilities, provide customers with the next steps and routes to resolution. By integrating with monitoring tools like Jira, PagerDuty, and several others, IrisAgent goes into the ‘why’ behind tickets associated with bugs, performance issues, and outages to create support workflows and recommend operational improvements.
Applying Machine Learning in customer support improves the support experience for support agents and customers alike. Since customer support can contain many unstructured and unlinked data, Machine Learning structures and links them to relevant data. By linking and structuring data, support agents can easily connect incoming tickets to similar tickets and trace them to the root cause.
Q. How do your solutions work on customer happiness?
IrisAgent is proactive because we enable companies to get on top of product and customer issues in real-time, preventing costly engineering escalations. We’re boosting support agent productivity by empowering teams to triage, pre-empt and resolve tickets associated with outages, bugs, and performance issues at a lightning-fast speed.
We help resolve complex tickets faster with product context:
We integrate with your CRM to tell you when a customer is up for renewal and provide you with insight into their adoption journey to help you to tailor your conversations and empathize more deeply with their experience.
Q. How was your experience working through the pandemic? Could you tell us about it?
The company was founded during the pandemic, so we have been remote-first and geographically distributed from the day one. We didn’t have legacy processes that needed to be changed to adapt to the new normal and that has helped us scale faster and leverage resources from round the world. We are a diverse and distributed team consisting of experienced product and engineering leaders. We are backed by seasoned VCs and advisors who have led customer experience at leading software companies.
Q. What does the road ahead look like for IrisAgent? Do you have anything new coming up?
The future is bright for IrisAgent. Today, our root cause discovery feature immediately identifies why a ticket has been created and provides support agents with routes to resolution, but ultimately we’re looking to fix problems before they start.
Beyond ticket deflection for incidents and user outages, which we’ll be rolling out this month, the next 18 months will see us double down on our analytics capabilities to take our Customer Health solution – and incident detection abilities – to the next level.