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Whether you're modernizing your lending stack or launching a new offering, Buy Now, Pay Later (BNPL) can be a catalyst for growth. See how financial leaders are seizing this moment in this blog post. 

I’ve watched closely as Buy Now, Pay Later (BNPL) has shifted from a checkout convenience to a&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://www.statista.com/statistics/1111233/payment-method-usage-transaction-volume-share-worldwide/">$340B growth engine</a> reshaping the financial ecosystem. With global market value projected to grow 12.3% annually through 2030, financial services leaders have a unique opportunity to deepen loyalty, reach new segments, and accelerate revenue.<h2>Why BNPL Matters for Financial Services Leaders</h2>At its core, BNPL is simple: split a purchase into interest-free installments over a defined period. But what’s truly transformative is the behavioral shift it has catalyzed.&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://www.fool.com/money/research/buy-now-pay-later-statistics/">Recent studies show</a> that Gen Z and millennials are using BNPL more than credit cards, driven by expectations for flexibility and transparency. Among BNPL users, 66% of Gen Z and 54% of Millennials say they prefer it over traditional revolving credit.This change is not just cosmetic.&nbsp;BNPL has:<ul><li>Increased cart conversion rates for merchants</li><li>Strengthened retention across digital channels</li><li>Created new customer acquisition opportunities with reduced friction</li></ul><h2>Deliver the BNPL Experience Today’s Consumers Expect</h2>Modern BNPL solutions aren’t just payment plans. They’re personalized, data-driven credit experiences built on flexible, scalable technology. Leading financial institutions are investing in:<ul><li>Real-time credit decisioning powered by alternative data and machine learning</li><li>Cloud-native microservices architectures that accelerate feature delivery and A/B testing</li><li>API-first ecosystems that connect e-commerce platforms, CRM tools, fraud prevention systems, and payment processors</li><li>Advanced analytics for risk scoring, fraud detection, and personalized user engagement</li></ul>To compete in the BNPL space—or partner strategically with BNPL providers—financial organizations need the agility to stand up or integrate these capabilities at speed.<h2>Three Proven Paths to BNPL Value</h2>Whether you're modernizing your lending stack or launching a new offering, BNPL can be a catalyst for growth.&nbsp;Financial leaders are seizing this moment by:<ul><li>Launching in-house BNPL products that tap into proprietary customer data and loyalty programs</li><li>Partnering with fintechs to reach new demographics and accelerate speed-to-market</li><li>Embedding credit directly into omnichannel customer journeys, from mobile apps to in-store experiences</li></ul>Each path comes with its own trade-offs—but all require the same thing: execution that’s fast, compliant, and resilient.<h3>How Gorilla Logic Helps You Win with BNPL</h3>At Gorilla Logic, we help financial services companies rapidly prototype, build, and scale BNPL and embedded finance solutions. Our dedicated engineering pods,&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://gorillalogic.com/blog-and-resources?industryId=3">fintech-experienced architects</a>, and secure-by-design delivery model ensure you get to market quickly without sacrificing quality or compliance.We partner with:<ul><li>Traditional banks modernizing legacy systems</li><li>Fintech innovators scaling next-gen credit platforms</li><li>Retailers integrating embedded finance into the digital experience</li></ul>No matter your starting point, we’ll help you build—and scale—what’s next.<hr><h2>BNPL is here to stay.&nbsp;</h2>The leaders are already building. Let’s make sure you’re one of them.<a target="_blank" rel="noopener noreferrer" href="https://gorillalogic.com/contact-us">Contact Us &gt;</a>

The Buy Now, Pay Later Revolution: A Strategic Opportunity for Financial Services Leaders

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Gorilla Logic enabled real-time ride tracking and seamless ATMS integrations for a leading NEMT platform using microservices and secure cloud design.

<figure class="table"><table><thead><tr><th style="background-color:hsl(0, 0%, 0%);width:200px;">Client</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Industry</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Solution Provided</th><th style="background-color:hsl(0, 0%, 0%);width:600px;">Technologies Used</th></tr></thead><tbody><tr><td style="vertical-align:top;">Non-emergency medical transportation broker</td><td style="vertical-align:top;">Healthcare &amp; Life Sciences</td><td style="vertical-align:top;">Platform DevOps &amp; SRE, Digital Product Development</td><td style="vertical-align:top;">AWS ECS, AWS Secrets Manager, Deno, PHP, Microservices Architecture</td></tr></tbody></table></figure><h2>The Need</h2>A leading non-emergency medical transportation (NEMT) platform aimed to expand its service ecosystem by integrating with multiple Advanced Transportation Management Systems (ATMS). The organization sought to improve operational reliability and user experience by addressing several key pain points:<ul><li>Ride Disruptions: Frequent delays, last-minute cancellations, and communication breakdowns were creating friction for riders and service partners</li><li>Lack of Real-Time Visibility: Customers needed accurate, real-time tracking to monitor ride status and manage transportation logistics more effectively</li><li>Scalability with Multiple Vendors: The platform required seamless integration with four distinct ATMS providers, each with unique requirements, while maintaining a secure and composable architecture</li></ul><h2>The Solution</h2>To enable real-time data flow and scalable interoperability across multiple vendors, Gorilla Logic implemented a microservices-based integration framework backed by secure cloud infrastructure:<ul><li>Composable Microservices Architecture: Developed and deployed new Deno and PHP microservices tailored to the client’s existing AWS ECS-based framework</li><li>Multi-Tenant Adapter System: Introduced a flexible, extensible adapter design to manage ATMS integrations:<ul><li>A generic base adapter defines the common structure for all integration flows</li><li>Custom adapters handled the unique specifications of each ATMS</li><li>The architecture supported easy scaling and future additions of new transportation systems</li></ul></li><li>Secure Credential Management: Used AWS Secrets Manager to securely store and manage sensitive credentials for each ATMS API, ensuring data protection and regulatory compliance</li></ul><h2>Results</h2>Improved Rider Experience: Real-time tracking and communication minimized delays and cancellations, providing more reliable service to patients and healthcare providers.Scalable System Integrations: The adapter-based architecture made it easy to onboard new transportation partners while maintaining system stability and reducing overhead.Hardened Security Posture: Sensitive data and API credentials were secured using best-in-class cloud-based secrets management.

Enhancing Real-Time Ride Tracking and User Experience for a Non-Emergency Medical Transportation Network

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Discover how Gorilla Logic helped a global streaming platform reduce cloud costs by $60K/month and scale personalized content delivery with AI and DevOps.

<figure class="table"><table><thead><tr><th style="background-color:hsl(0, 0%, 0%);width:200px;">Client</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Industry</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Solution Provided</th><th style="background-color:hsl(0, 0%, 0%);width:600px;">Technologies Used</th></tr></thead><tbody><tr><td style="vertical-align:top;">Global media company</td><td style="vertical-align:top;">Telecommunication, Media, &amp; Information Services</td><td style="vertical-align:top;">AI, cloud, and automation solutions</td><td style="vertical-align:top;">AWS, Docker, ECS, Kubernetes, Terraform, Akamai, Chef, Load Testing Tools</td></tr></tbody></table></figure><h2>The Need</h2>A leading global media company aimed to enhance its streaming platform to deliver personalized, reliable, and cost-effective experiences across multiple platforms. The primary challenges included:<ul><li>AI-Driven Personalization: Implementing machine learning solutions to tailor content based on user interactions.</li><li>Integrated Applications: Seamless integration of entertainment apps with identity management systems for secure, personalized user experiences.</li><li>Continuous Availability: Upgrading infrastructure to minimize downtime and ensure uninterrupted service.</li><li>Cost Optimization: Seeking efficient alternatives for feature flagging and caching to reduce operational expenses.</li><li>Traffic Management: Developing advanced strategies to optimize content delivery for a global audience.</li></ul><h2>The Solution</h2>Gorilla Logic deployed a comprehensive strategy combining AI, cloud, and automation solutions to address the client's needs:<ul><li>AI-Powered Personalization: Leveraged machine learning algorithms to analyze user activity and deliver tailored content recommendations.</li><li>Seamless App Integration: Integrated entertainment applications with identity management solutions, enabling secure and personalized user experiences.</li><li>Infrastructure Optimization: Identified and resolved infrastructure bottlenecks, improved processes, and migrated application infrastructure from Chef to Docker on ECS.</li><li>Traffic Optimization: Recommended and implemented traffic management strategies using AWS, Terraform, Akamai, and advanced load testing tools to ensure efficient content delivery.</li></ul><h2>Results</h2>Enhanced User Engagement: AI-driven content recommendations increased user engagement and retention.Improved System Reliability: Optimized infrastructure resulted in near-zero downtime for critical applications.Operational Cost Savings: Migrating to a Kubernetes architecture reduced operational expenses by approximately $60,000 per month.Scalable Development: Enabled continuous development with an optimized global talent pipeline, enhancing scalability and efficiency.

Scaling Personalized Content Delivery and Reducing Infrastructure Costs for a Global Streaming Platform

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Discover how Gorilla Logic helped a luxury vacation rental brand expand its reach and boost revenue through a secure, scalable B2B API integration with Hopper, powered by Azure API Management and a developer-friendly portal experience.

<figure class="table"><table><thead><tr><th style="background-color:hsl(0, 0%, 0%);width:200px;">Client</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Industry</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Solution Provided</th><th style="background-color:hsl(0, 0%, 0%);width:600px;">Technologies Used</th></tr></thead><tbody><tr><td style="vertical-align:top;">Luxury travel company</td><td style="vertical-align:top;">Transportation &amp; Hospitality</td><td style="vertical-align:top;">B2B API integration, API management, developer enablement</td><td style="vertical-align:top;">Azure API Management (APIM), APIM Developer Portal, RESTful APIs: Inventory, Pricing, Booking, Cancellation</td></tr></tbody></table></figure><h2>The Need</h2>A luxury vacation rental platform sought to expand its customer reach and drive business growth by featuring its listings on Hopper, a popular travel booking app. To support this B2B integration, the company needed to:<ul><li>Expose its property inventory, pricing, booking, and cancellation APIs</li><li>Implement robust authentication and authorization to protect sensitive customer data</li><li>Ensure high availability and scalability to accommodate fluctuating booking volumes and user activity</li></ul><h2>The Solution</h2>Gorilla Logic integrated the client’s APIs with Hopper while ensuring security, performance, and scalability through Azure API Management (APIM). The solution included:<ul><li>API Integration with Azure APIM:<ul><li>Inventory Properties API: Delivered property details</li><li>Pricing API:&nbsp;Provided real-time reservation pricing</li><li>Booking API: Enabled reservations</li><li>Cancellation API:&nbsp;Handled booking cancellations</li></ul></li><li>Developer Enablement:<ul><li>Leveraged APIM’s Developer Portal to provide Hopper engineers with interactive documentation, authentication guidance, and testing tools</li></ul></li><li>Performance and Reliability:<ul><li>Monitored API usage and health in real time to ensure high availability and proactive issue resolution</li></ul></li></ul><h2>Results</h2>Expanded Reach and Revenue: The integration opened access to a broader customer base via Hopper, driving increased bookings and revenue growthSeamless B2B Integration: Enabled Hopper users to search listings, check prices, book stays, and cancel reservations with easeScalable, Secure API Infrastructure: Ensured ongoing performance, security, and uptime—even under variable traffic loadsFaster Developer Onboarding: The APIM Developer Portal reduced friction for Hopper's engineering team, accelerating the integration timeline and minimizing errors

Expanding Reach and Revenue for a Luxury Travel Brand Via Seamless B2B Integration

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Gorilla Logic helped a global automotive leader modernize its cloud development portal, reducing support tickets by 66% and accelerating development cycles.

<figure class="table"><table><thead><tr><th style="background-color:hsl(0, 0%, 0%);width:200px;">Client</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Industry</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Solution Provided</th><th style="background-color:hsl(0, 0%, 0%);width:600px;">Technologies Used</th></tr></thead><tbody><tr><td style="vertical-align:top;">Global Automotive Manufacturer</td><td style="vertical-align:top;">Auto &amp; Manufacturing</td><td style="vertical-align:top;">Digital Product Development, Cloud Modernization, DevOps</td><td style="vertical-align:top;">React, GitOps, CLI, JSON</td></tr></tbody></table></figure><h2>The Need</h2>An internal development portal was causing inefficiencies due to outdated technology and needed modernization and automation support, including:<ul><li>Legacy System Challenges:&nbsp;Update legacy components and plugins using modern technologies and a Domain-Driven Design approach</li><li>Scalability Requirements:&nbsp;Accommodate the client's expanding cloud needs while maintaining a user-friendly interface for development teams</li><li>Process Optimization:&nbsp;Improve efficiency and accelerate the development process by reducing monthly support tickets</li></ul><h2>The Solution</h2>Streamlining development processes and enhancing team efficiency via:<ul><li>Plug-and-Play Customization:&nbsp;Enabled developers to use pre-built components for tailored solutions without starting from scratch, offering simple default options and advanced tools for complex configurations</li><li>Automated Workflow:&nbsp;Designed an automated workflow where engineers create a JSON file to define UI intent, submit it to a pipeline, and generate auto-coded UI stored in source control. A Command Line Interface mode was also introduced for programmatic work</li><li>Modern Technology Stack:&nbsp;Implemented modern frameworks like React and GitOps to create a more dynamic platform and improve the user experience</li></ul><h2>Results</h2>Improved Efficiency:&nbsp;Successfully automated menu generation and reduced monthly support tickets by 66%Accelerated Development:&nbsp;Empowered teams to work independently without relying on UI steps or other teams, reducing development cycles from days or weeks to a few hoursEnhanced Automation:&nbsp;Introduced automated tracking, approval, and implementation of changes using pipelines, reducing processing time from days to hours

Accelerating Development and Reducing Support Load for Global Auto Manufacturer with Cloud Component Strategy

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Gorilla Logic introduced a Slack-integrated, AI-powered knowledge assistant to unify internal knowledge access and reduce time-to-competency for a real estate tech company

<figure class="table"><table><thead><tr><th style="background-color:hsl(0, 0%, 0%);width:200px;">Client</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Industry</th><th style="background-color:hsl(0, 0%, 0%);width:200px;">Solution Provided</th><th style="background-color:hsl(0, 0%, 0%);width:600px;">Technologies Used</th></tr></thead><tbody><tr><td style="vertical-align:top;">Real estate and property management technology company</td><td style="vertical-align:top;">Residential Property Management</td><td style="vertical-align:top;">Data &amp; AI</td><td style="vertical-align:top;">LangGraph, Pinecone, and Claude</td></tr></tbody></table></figure><h2>The Need</h2>A U.S.-based property management and technology company needed to eliminate inefficiencies in how employees accessed internal information to enable faster onboarding, ensure consistent execution, and support scalable operations.<ul><li>Scattered Knowledge Repositories: Vital information—contracts, policies, training docs—was spread across Slack and disorganized Google Drive folders</li><li>Inefficient Information Retrieval: Employees spent excessive time searching or asking for answers, leading to delays, duplicate work, and inconsistent guidance</li><li>Scaling Limitations: Disjointed access to reliable knowledge made it hard to onboard new hires, standardize execution, or maintain up-to-date practices across teams</li></ul><h2>The Solution</h2>Gorilla Logic introduced a Slack-integrated, AI-powered knowledge assistant to unify internal knowledge access and reduce time-to-competency.<ul><li>Integrated Knowledge Assistant:&nbsp;Deployed a custom AI agent, “Mo,” embedded directly into Slack and internal tools to surface accurate, plain-language answers instantly</li><li>Contextual Knowledge Surfacing:&nbsp;Connected the assistant to Google Drive, Slack, and a new CMS to deliver timely, relevant content wherever employees work</li><li>Behind-the-Scenes Intelligence:&nbsp;Leveraged LangGraph, Pinecone, and Claude to power the experience, ensuring high performance while keeping user interactions intuitive</li></ul><h2>Results</h2>Instant Knowledge Access:&nbsp;Employees now receive instant, accurate answers without delay, eliminating bottlenecks and guessworkFaster Onboarding and Execution:&nbsp;Dramatically reduced new hire onboarding time and ensured consistent procedural execution across officesBoosted Productivity and Experience:&nbsp;Internal AI tooling streamlined workflows, reduced frustration, and empowered employees with reliable self-service supportSmarter AI Investment:&nbsp;Tailored use of generative AI maximized value by applying it to both internal knowledge retrieval and external language tasks

Streamlining Operations and Accelerating Onboarding for a Real Estate Tech Company With AI-Powered Knowledge Assistant

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How to implement a comprehensive FinOps strategy to gain visibility into cloud spending patterns and optimize resource allocation
How to create cross-functional teams that align engineering, finance, and operations to drive cloud cost efficiency
Ways to deploy automated monitoring tools to track resource utilization and identify optimization opportunities
How to establish clear governance frameworks with defined metrics and KPIs to measure cloud ROI

How Engineering Leaders Can Use FinOps to Improve Cloud ROI

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This blog post is part of an independent series called Connecting with AI, authored by Felipe Mantilla, an AI engineering expert at Gorilla Logic. The series' goal is to make the world of AI more accessible, support those who want to learn more about the field, and establish foundations on the most interesting advancements in AI.

<span style="color:rgb(31,29,29);font-family:&quot;Open Sans&quot;, ui-sans-serif, system-ui, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;;">This blog post is part of an independent series called Connecting with AI, authored by <a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/in/felipe-mantilla-167850163/"><span style="color:rgb(31,29,29);font-family:&quot;Open Sans&quot;, ui-sans-serif, system-ui, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;;">Felipe Mantilla</a><span style="color:rgb(31,29,29);font-family:&quot;Open Sans&quot;, ui-sans-serif, system-ui, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;;">, an AI engineering expert at Gorilla Logic. The series' goal is to make the world of AI more accessible, support those who want to learn more about the field, and establish foundations on the most interesting advancements in AI. You can find the original version of this post in Spanish on his <a target="_blank" rel="noopener noreferrer" href="https://medium.com/@felipemantillagomez/conecta-con-ai-4e7d002ae9cf">Medium blog</a><span style="color:rgb(31,29,29);font-family:&quot;Open Sans&quot;, ui-sans-serif, system-ui, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Symbol&quot;, &quot;Noto Color Emoji&quot;;">.&nbsp;In recent months, AI has found its way into virtually every space. The term “agents” is buzzing everywhere, and companies are quick to integrate features that make API calls to LLM providers, branding themselves as “AI-friendly.” But what exactly are these agents? How do they work? And more importantly—how can you build one using TypeScript?While AI is most commonly associated with Python, JavaScript remains one of the most widely used languages globally, especially for web development. Many companies already have codebases and engineering teams fluent in JavaScript, making TypeScript a valid and accessible option for integrating agents. Even though enterprise support exists, community adoption is still catching up. Still, it’s worth knowing how to do it.<h2>Getting Started with OpenAI in TypeScript</h2>Since ChatGPT and OpenAI are household names at this point, here's what you’ll need to use OpenAI’s API with TypeScript:<ol><li>Create a TypeScript-compatible project</li><li>Install the <code>openai</code> package via npm</li><li>Get an OpenAI token</li><li>Start experimenting with the API</li></ol><h3>Creating a TypeScript-Compatible Project</h3>There are multiple ways to set up a TypeScript project. Recently, Node.js announced native support for TypeScript in version 23. If you want more details on that, check out <a target="_blank" rel="noopener noreferrer" href="https://www.totaltypescript.com/typescript-is-coming-to-node-23">this article</a>.Another approach is to create a project from scratch, adding the dependencies and configurations manually. I put together a step-by-step guide for this process—<a target="_blank" rel="noopener noreferrer" href="https://medium.com/@felipemantillagomez/construyendo-algo-capitulo-1-configurando-nodejs-express-typescript-ca3334ddd408">check it out here</a>.For this guide, though, we’ll use a boilerplate available on GitHub. <a target="_blank" rel="noopener noreferrer" href="https://github.com/jsynowiec/node-typescript-boilerplate">You can find it here</a>. It already comes with built-in features like watchers, testing, and a build process.To use the boilerplate, follow these steps:<img class="image_resized" style="width:73.06%;" src="https://content.gorillalogic.com/strapi/open_AI_38a2beab79.gif" alt="openAI.gif">Clone it from the repo.Then run:<code>npm i &amp;&amp; npm run build &amp;&amp; npm run start</code>And that’s it—you’re ready to start developing your project using TypeScript.<h3>Installing the <code>openai</code> Package from npm</h3><a target="_blank" rel="noopener noreferrer" href="https://www.npmjs.com/package/openai">Head here</a> to check out OpenAI’s JavaScript documentation. To install the package, run the following command:<code>npm i openai</code>I made two additional tweaks:Added a <code>dev</code> script with file watchers:<code>"dev": "tsc -w -p tsconfig.json &amp; node --watch build/src/main.js",&nbsp;</code>And cleaned up <code>main.ts</code> and the associated test files.Now OpenAI is officially part of our project’s dependencies:<img class="image_resized" style="width:52.46%;" src="https://content.gorillalogic.com/strapi/typescript1_994d486a96.jpg" alt="typescript1.jpg"><h3>Get Your OpenAI Token</h3>Here’s the tricky bit—OpenAI is a paid service. You’ll need a paid account to get an access token. (But don’t worry, if you don’t have one yet, keep reading—we’ll also explore open-source models you can use without an OpenAI subscription.)Create a new OpenAI account or log into an existing one.<img class="image_resized" style="width:76.83%;" src="https://content.gorillalogic.com/strapi/typescript2_911f70289d.jpg" alt="typescript2.jpg">Then grab your token, which will look something like this:<img class="image_resized" style="width:66.9%;" src="https://content.gorillalogic.com/strapi/typescript3_12b79d04ce.jpg" alt="typescript3.jpg">Once you’ve got your token, be sure to add some credits to your account. Otherwise, your API calls will fail.<img class="image_resized" style="width:66.62%;" src="https://content.gorillalogic.com/strapi/typescript4_82e89d7990.jpg" alt="typescript4.jpg">To keep things secure, create a <code>.env</code> file in your project and paste your token there.<img class="image_resized" style="width:58.88%;" src="https://content.gorillalogic.com/strapi/typescript5_b42014dd55.jpg" alt="typescript5.jpg">And just like that, you're ready to bring your ideas to life!<h2>Playing with the API</h2>To use your <code>.env</code> file, you’ll need to slightly tweak the <code>scripts</code> section in <code>package.json</code>:<img class="image_resized" style="width:80.77%;" src="https://content.gorillalogic.com/strapi/Screenshot_2025_04_07_at_10_00_28_AM_6ed838e6f7.png" alt="Screenshot 2025-04-07 at 10.00.28 AM.png">Install <code>dotenv</code> to handle environment variables:<code>npm i dotenv</code>Now update your <code>main.ts</code> and confirm that your environment variables are accessible from your code.<img class="image_resized" style="width:64.53%;" src="https://content.gorillalogic.com/strapi/typescript6_a3808f3444.jpg" alt="typescript6.jpg"><img class="image_resized" style="width:64.32%;" src="https://content.gorillalogic.com/strapi/typescrip7_34136806e2.jpg" alt="typescrip7.jpg"><h2>Let’s Code!</h2>We'll copy and paste the available code in npm OpenAI, making some minor adjustments.&nbsp;<img class="image_resized" style="width:67.09%;" src="https://content.gorillalogic.com/strapi/Screenshot_2025_04_07_at_10_02_20_AM_e880eb4c1b.png" alt="Screenshot 2025-04-07 at 10.02.20 AM.png">If you run this code without purchasing OpenAI credits, you’ll probably see an error response like this:<img class="image_resized" style="width:80.85%;" src="https://content.gorillalogic.com/strapi/typescript8_61756e8be7.jpg" alt="typescript8.jpg">If you have added credits, you should see a proper response like:<img class="image_resized" style="width:79.28%;" src="https://content.gorillalogic.com/strapi/typescript9_ddaad33845.jpg" alt="typescript9.jpg"><h3>Understanding the API Response</h3>With that, we're ready. To finalize this first section, we'll analyze the available properties in the answer. In this example, we’re using the Chat Completions API.&nbsp;<img class="image_resized" style="width:74.06%;" src="https://content.gorillalogic.com/strapi/typescript10_231d6ed577.jpg" alt="typescript10.jpg">Analyzing the response, it's clear that we should access choices[0].message.content. The rest of the response includes useful metadata, like:<ul><li>Number of tokens used (input + output)</li><li>Why the model stopped generating (e.g., max tokens, stop sequence)</li><li>Message role (e.g., user, assistant)</li><li>Additional metadata about the interaction</li></ul>This structure gives you a detailed view into the exchange and how the model interpreted your prompt.<h3>A Quick Note on Tokens</h3>What’s a token? It’s a chunk of text (usually a word or part of one) that the model uses to interpret language statistically. If you're curious about how text is broken into tokens, try OpenAI’s <a target="_blank" rel="noopener noreferrer" href="https://platform.openai.com/tokenizer">Tokenizer tool</a>.<img class="image_resized" style="width:40.05%;" src="https://content.gorillalogic.com/strapi/typescript11_f25a83b0dc.jpg" alt="typescript11.jpg">OpenAI pricing is based on the number of tokens processed. Longer prompts and responses = higher costs.You can check pricing details depending on which model you use:<a target="_blank" rel="noopener noreferrer" href="https://openai.com/api/pricing/">https://openai.com/api/pricing/</a><a target="_blank" rel="noopener noreferrer" href="https://platform.openai.com/settings/organization/limits">https://platform.openai.com/settings/organization/limits</a><h2>Keep Exploring</h2>The sky's the limit with OpenAI—try different use cases like audio, image, and complex text processing. Be bold. Experiment. Tinker around and push the boundaries of what’s possible.<h2>What’s Next?</h2>I’ll be posting more entries diving deeper into advanced and exciting topics. Stay tuned—you won’t want to miss them.

Connecting with AI: Building AI Agents with TypeScript

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So what do Gorillas actually do all day? Glad you asked! Our blog highlights our Gorillas and the cool projects they’re working on. We also delve into the latest trends and technologies in web, mobile, and enterprise application development. Finally, we toss in a few stories about what we do for fun. We hope you’ll join the conversation!

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Resource Hub

Explore our Resource Hub for expert insights on digital product development

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