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Exploring Capabilities of OpenAI’s ChatGPT Code Interpreter

Imagine having a personal data scientist at your fingertips, capable of interpreting raw data, creating intricate visuals, and even handling video editing. Sounds like a dream? Well, OpenAI has turned this dream into reality with the introduction of their Code Interpreter for ChatGPT.

What is ChatGPT’s Code Interpreter?

The Code Interpreter is a groundbreaking plugin developed by OpenAI. The primary objective of this feature is to amplify the abilities of ChatGPT, moving it beyond its initial role as a text-generating AI.

By enabling the Code Interpreter, users have the opportunity to transform ChatGPT into an adaptable tool capable of running Python code, processing data, and much more. The chatbot can even edit videos and images, bringing a sense of versatility that has been largely absent in the realm of chatbots.

But how does the Code Interpreter work? Let’s delve deeper.

Unpacking the Code Interpreter: How does it work?

At its core, the Code Interpreter transforms ChatGPT into an instantly accessible data scientist. The plugin empowers the chatbot to run code, create charts, analyze data, perform mathematical operations, and edit files.

When a user inputs any unformatted data, for example from a PDF, ChatGPT can analyze it and create well-structured output. Be it generating data in table layouts or restructuring the format and running models, the Code Interpreter aids ChatGPT in providing the best possible outcomes.

Further enhancing its capabilities, the Code Interpreter can efficiently convert data from wide to long formats and vice versa, a feature that saves users substantial time and effort.

This plugin’s usefulness extends beyond typical data handling. It opens up a world of creativity, like the instance where a user uploaded a CSV file of every lighthouse location in the US and ChatGPT created a GIF map with twinkling lights atop each location.

(Code Interpreter can help you do data analysis in seconds!)

Given this wide array of applications, the Code Interpreter brings a significant advantage to ChatGPT Plus subscribers. But how can one access and make the most of this new feature?

How to Use ChatGPT’s Code Interpreter?

For gaining access to the Code Interpreter, one must be a ChatGPT Plus subscriber. Here are the steps to navigate the process:

  1. Log in to ChatGPT on the OpenAI website.
  2. Select Settings.
  3. In the bottom-left of the window, next to your login name, select the three-dot menu.
  4. Select the Beta features menu and toggle on Plug-ins. To enable internet access for ChatGPT, toggle on Web browsing. A Chrome extension can also be used for the same.
  5. Close the menu and find the small drop-down menu under the language model selector. Select it.
  6. Select Plugin Store.
  7. Select All plug-ins.
  8. Find Code Interpreter in the list and select Install.

What Can ChatGPT’s Code Interpreter Do?

From performing intricate data analysis to converting file formats, the Code Interpreter pushes the boundary of what ChatGPT can accomplish. A few examples of its potential uses include:

  • Data Analysis: The Code Interpreter can delve into raw data, analyze it, and provide a comprehensive understanding of it. For instance, a Twitter user analyzed a 300-hour Spotify playlist of his favorite songs using ChatGPT. The chatbot not only provided visualization but also helped with data retrieval and explained how to use Spotify API.

(You can ask it to summarize a huge data set, get insights from it, and make changes as well)

  • File Conversion: With the Code Interpreter, ChatGPT can transform data from one format to another effortlessly. A user uploaded a GIF and asked ChatGPT to convert it into an MP4 with Zoom.
  • File Handling: The Code Interpreter comes equipped with extraordinary file-handling capabilities. It can upload and download files, extract colors from an image to create palette.png, and automatically compress large images to manage memory shortage issues.

Code Interpreter: Industry Use Cases

The introduction of Code Interpreter can herald a new era of tech innovation. In industries like retail, for example, companies can leverage ChatGPT to analyze customer behavior data, improving their marketing strategies and customer service. Similarly, in healthcare, researchers could use it to sift through vast amounts of medical data to derive useful patterns and insights.

In the realm of education, the Code Interpreter could be used to create interactive learning tools, helping students grasp complex concepts easily. This could lead to a more inclusive and adaptive learning environment. Tech companies can leverage the same to accelerate building products, gain efficiencies, etc. Companies like Mantra Labs have already started exploring such possibilities and experimenting with them to create tools and solutions that cater to industrial needs.

In media and entertainment, from analyzing viewer preferences to helping with video editing and creating customized content, the possibilities are vast.

Looking at the Potential

Looking back at some already accomplished tasks, it’s clear that the Code Interpreter could streamline many processes. For instance, consider the task of converting large volumes of data from one format to another. In the past, this required dedicated software or skilled personnel. Now, this could be accomplished with a simple command to the ChatGPT Code Interpreter.

Another example is the analysis of large data sets. Take the Twitter user who analyzed his extensive Spotify playlist. Without the Code Interpreter, this task would have been arduous, requiring manual sorting through hundreds of songs and extracting relevant data. The Code Interpreter simplified this process, performing it in a matter of seconds.

In conclusion, the introduction of ChatGPT’s Code Interpreter represents a significant leap in AI development, one that holds immense potential. As we continue to refine and expand this tool, the Code Interpreter could transform industries, change our approaches to problem-solving, and redefine the boundaries of what AI can achieve.

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NPS in Insurance Claims: What Insurance Leaders Are Doing Differently

Claims are the moment of truth. Are you turning them into moments of loyalty?

In insurance, your app interface might win you downloads. Your pricing might drive conversions.
But it’s the claims experience that decides whether a customer stays—or leaves for good.

According to a survey by NPS Prism, promoters are 2.3 times more likely to renew their insurance policies than passives or detractors—highlighting the strong link between customer advocacy and retention.

NPS in insurance industry is a strong predictor of customer retention. Many insurers are now prioritizing NPS to improve their claims experience.

So, what are today’s high-NPS insurers doing differently? Spoiler: it’s not just about faster payouts.

We’ve worked with claims teams that had best-in-class automation—but still had low NPS. Why? Because the process felt like a black box.
Customers didn’t know where their claim stood. They weren’t sure what to do next. And when money was at stake, silence created anxiety and dissatisfaction.

Great customer experience (CX) in claims isn’t just about speed—it’s about giving customers a sense of control through clear communication and clarity.

The Traditional Claims Journey

  • Forms → Uploads → Phone calls → Waiting
  • No real-time updates
  • No guidance after claim initiation
  • Paper documents and email ping-pong

The result? Frustrated customers and overwhelmed call centers.

The CX Gap: It’s Not Just Speed—It’s Transparency

Customers don’t always expect instant decisions. What they want:

  • To know what’s happening with their claim
  • To understand what’s expected of them
  • To feel heard and supported during the process

How NPS Leaders Are Winning Loyalty with CX-Driven Claims and High NPS

Image Source: NPS Prism

1. Real-Time Status Updates

Transparency to the customer via mobile app, email, or WhatsApp—keeping them in the loop with clear milestones. 

2. Proactive Nudges

Auto-reminders, such as “upload your medical bill” or “submit police report,” help close matters much faster and avoid back-and-forth.

3. AI-Powered Document Uploads

Single-click scans with OCR + AI pull data instantly—no typing, no errors.

4. In-the-Moment Feedback Loops

Simple post-resolution surveys collect sentiment and alert on issues in real time.

For e.g., Lemonade uses emotional AI to detect customer sentiment during the claims process, enabling empathetic responses that boost satisfaction and trust.

Smart Nudges from Real-Time Journey Tracking

For a leading insurance firm, we mapped the entire in-app user journey—from buying or renewing a policy to initiating a claim or checking discounts. This helped identify exactly where users dropped off. Based on real-time activity, we triggered personalized notifications and offers—driving better engagement and claim completion rates.

Tech Enablement

  • Claims Orchestration Layer: Incorporates legacy systems, third-party tools, and front-end apps for a unified experience.
  • AI & ML Models: For document validation, fraud detection, and claim routing, sentiment analysis is used. Businesses utilizing emotional AI report a 25% increase in customer satisfaction and a 30% decrease in complaints, resulting in more personalized and empathetic interactions.
  • Self-Service Portals: Customers can check their status, update documents, and track payouts—all without making a phone call.

Business Impact

What do insurers gain from investing in CX?

A faster claim is good. But a fair, clear, and human one wins loyalty.

And companies that consistently track and act on CX metrics are better positioned to retain customers and build long-term loyalty.

At Mantra Labs, we help insurers build end-to-end, tech-enabled claims journeys that delight customers and drive operational efficiency.
From intelligent document processing to AI-led nudges, we design for empathy at scale.

Want a faster and more transparent claims experience?

Let’s design it together.
Talk to our insurance transformation team today.

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