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Traditional role‑plays and classroom trainings often struggle to feel realistic, repeatable, and scalable. The AI Conversation Coach app was created to solve that by giving employees a safe space to practice high‑stakes conversations with AI personas that respond dynamically, just like real customers or team members. Users log in through the mobile app or web app, select a scenario (for example, handling objections on a sales call or managing a difficult performance conversation), and then engage in a simulated dialogue with an AI counterpart. The AI adjusts its responses based on what the learner says, creating a natural flow instead of scripted Q&A. On the technology side, our team built Flutter apps for Android and iOS, backed by Node.js/Express APIs and a MySQL database, all deployed on AWS and integrated with a web front end built with HTML5, CSS3, Bootstrap, JavaScript, jQuery, and EJS. This stack supports real‑time chat, scenario configuration, role‑based access, reporting, and scalable AI usage through token‑based limits. The admin panel allows training managers to design their own conversation scenarios, define AI personas, assign modules to user groups, and review performance data, turning the app into a flexible training platform rather than a fixed set of lessons.

AIServe was created as an early‑stage AI project with a very practical first step: make it effortless for people to order from a local restaurant without dealing with clunky websites or phone calls. The product starts with one partner restaurant and one delivery zone, proving the experience before scaling to more partners and features. In the app, users tap “Get Started” to view the curated menu, pick their items, and move through a streamlined checkout flow powered by secure Stripe integration. Once an order is placed, users can review their order history from inside the app, giving them a simple record of what they’ve ordered and when. Even users outside the current delivery zone can still explore the app and see how AIServe works, building familiarity for future expansion. Under the hood, the system is built in Flutter for a consistent Android and iOS experience, with a Node.js backend managing products, orders, users, and payment flows. The architecture is intentionally lightweight but structured to support the next phase: voice ordering with “Tria” (the AI assistant), scheduled orders, tipping, and multiple restaurants across larger service areas.

Most habit apps are built for adults and feel like personal productivity dashboards. STACKT flips that idea for teens by treating habits like a team sport. Instead of tracking alone, users join or create “squads” with friends, set shared or individual habits, and hold each other accountable through real‑time progress and positive peer pressure. In the app, a teen can create a profile, start a squad, and invite friends to join. Each squad sets habits they want to build, like studying a little every day, practicing a skill, moving more, or getting enough sleep. Members check in on their habits daily, and the app visualises everyone’s streaks and progress in a way that feels more like a social club than a to‑do list. Simple reactions and encouragement features help friends celebrate wins and keep each other on track. Your team implemented STACKT using Flutter and Dart for a consistent experience across Android and iOS, while a Node.js backend handles authentication, squads, habits, streaks, and notifications. The overall design, copy, and flow are tuned to feel teen‑friendly: bright, fun, and low‑pressure, but still structured enough to build real consistency.

In textile and weaving businesses, costing is everything, but it’s often handled through manual formulas in notebooks or spreadsheets. That makes it easy to make mistakes and hard to respond quickly to price changes or new orders. TaanaBaana was created to solve this with a dedicated textile costing app that fits right into the daily workflow of mills and weaving units. Inside the app, users can enter details about warp and weft quality, yarn counts, densities, fabric width, and other key parameters. The app then calculates yarn consumption, weaving cost, fabric cost per unit, and estimated profit for a given order or design. Instead of re‑doing formulas each time, users can run multiple scenarios in seconds and save or export the results as professional‑looking reports. Built with Flutter and Dart, TaanaBaana offers a consistent experience across Android and future iOS deployment. A Node.js backend powers user accounts, saved calculations, and report management, while the admin panel allows the client to configure formulas, update defaults (like overheads or conversion factors), and support users as the product evolves.

In many emerging markets, people rely on WhatsApp groups, social media posts, and informal pages to buy and sell products. That creates a lot of friction and risk: no clear product details, no order tracking, and weak protection against low‑quality or unsafe items. Grape was built to change that by offering a proper marketplace experience that still feels simple enough for everyday users. With the Grape Customer app, users sign up or log in quickly using their mobile number and OTP. Once inside, they can browse across multiple categories, view real photos and descriptions, compare items, and add products to their cart or wishlist. A smooth checkout flow supports convenient options like COD (cash on delivery) where enabled, and users can track their orders from purchase to delivery. Smart search and filters help them find exactly what they need without scrolling endlessly. On the backend, a Laravel + MySQL stack powers product listings, user accounts, orders, and vendor data. The admin panel, built with HTML, CSS, Bootstrap, jQuery, and Laravel views, gives the Grape team full control over which products are allowed, how vendors are onboarded, and how content is moderated—so the marketplace stays clean, safe, and aligned with local rules.

While the Grape Customer app focuses on giving buyers a clean and safe place to shop, the Grape Seller app is built for the people who power that marketplace: local vendors. Many of these sellers are used to handling everything manually, WhatsApp messages, notebooks, and in‑person cash—but want a simple way to move into structured online selling without learning complex tools. With Grape Seller, vendors can sign in quickly using mobile number + OTP and immediately see a dashboard of their shop. From there, they can add new products with photos, descriptions, and prices, organise them into categories, and keep track of stock levels. Incoming orders appear in an easy‑to‑scan list, allowing sellers to accept, prepare, and mark them as completed. They can also apply offers or discounts to boost sales and see at a glance how their store is performing over time. Behind the scenes, the Flutter app talks to a Laravel + MySQL backend that handles authentication, products, orders, and vendor profiles. An admin panel built with HTML, CSS, JavaScript, jQuery, Bootstrap, and Laravel views gives the Grape team full control over vendor onboarding, product approval, marketplace rules, and support, ensuring the platform stays clean and compliant.

Most schools and education organisations still rely on physical forms and manual workflows when they onboard students, collect documents, or update records. This makes it hard to keep data clean, secure, and up to date, especially when working across multiple batches, years, or programs. SS KYC: Shikshan Sarvada was built to fix that. With the mobile app, students or parents can log in, fill in key details, upload required documents, and complete their KYC process without visiting the office or handling stacks of paperwork. The app guides them through structured steps, personal information, contact details, academic history, ID proof, and other documents, reducing errors and missing fields. On the institution side, a React‑based admin panel connected to a Django backend gives staff a clear dashboard of applications, verification status, document completeness, and follow‑ups. Administrators can review submissions, approve or reject entries, request clarifications, and export clean data for use in their internal systems, all from one place. Flutter ensures a smooth mobile experience on both Android (once live) and iOS, while Django provides a robust, scalable backend for data and workflows.

Most home cooks today don’t discover recipes in cookbooks, they find them in reels, stories, posts, and long blog pages. The problem is that those recipes are hard to cook from and even harder to find later. Recipe Social was created to solve this by acting as a central “inbox” for everything food‑related a user discovers online. Inside the app, users can paste a link, upload a screenshot, or paste raw text from any recipe they come across. Recipe Social then uses AI‑assisted parsing to extract the title, ingredients, and step‑by‑step instructions into a clean format that’s actually usable in the kitchen. From there, users can edit the recipe, tag it into custom cookbooks (for example: “Weeknight Dinners”, “Meal Prep”, “Desserts”), and quickly search their growing library whenever they need inspiration. The product is built in Flutter, so the same codebase serves both Android and iOS, while Supabase provides authentication, database storage, and media handling. This combination allowed the team to move quickly while still giving the client a solid, scalable foundation for future community features if they decide to add sharing later.

LesMeet was born from a simple need: there wasn’t a focused, safe, and modern space where lesbian women could connect with each other, discover events, and feel like the platform truly understood them. Instead of trying to be “for everyone”, the founders wanted an app built around one community, with features that make it easier to meet people both online and offline. In the app, users create profiles, share interests, and set preferences for how they want to connect: friendship, dating, networking, or events. A feed and discovery flow help them find other women nearby, chat through in‑app messaging, and see curated events hosted within the community. Built in Flutter, LesMeet runs smoothly on both Android and iOS, while a Node.js backend and EJS admin panel power user management, event listings, moderation, and content controls. The product intentionally feels more like “a community that happens to have dating” than “a dating app with a community bolt‑on”, with a focus on safety, warmth, and offline experiences such as meetups, parties, and local gatherings.

Traditional Assamese attire like Mekhla Chador has strong demand, but many aspiring resellers struggle with inventory costs, photography, and shipping operations. The client wanted a digital platform where they could handle stock and logistics centrally, while resellers focus purely on marketing and customer relationships. Inside the app, resellers browse an extensive catalogue of Mekhla Chador and Assamese sarees, organised by fabric, motifs, and design style, then share high‑quality product photos directly to WhatsApp, Facebook, Instagram, and other channels. When a customer confirms, the reseller places the order through the app and the product is shipped straight to the customer’s address in plain packaging that carries only the reseller’s name and phone number. Our team implemented the app in Flutter for both Android and iOS, with Node.js/Express APIs, MongoDB, and an admin panel on top of AWS and GoDaddy hosting. This stack powers catalogue management, stock visibility, orders, discounts, and tracking, giving Mekhla Chador Hub an end‑to‑end reselling engine while keeping the front‑end experience simple for resellers across Assam and beyond.

Where the core AI Job Interview Coach app focuses on accessible practice for everyone, the Pro version was designed for learners who want more intensive training—longer sessions, richer scenarios, and premium AI coaching. In AI Job Interview Coach Pro, users can access expanded question sets, advanced personas, and structured practice paths. Sessions are powered by the AI Coach Pro engine, which simulates realistic hiring managers and responds dynamically to user input, creating a lifelike interview environment. Our team implemented the product using Flutter (Dart) for cross‑platform mobile, Node.js/Express for the API layer, MySQL for data storage, and a responsive web app for browser‑based practice. Subscription and in‑app purchase flows are tied to tokens or coins that learners consume when attending interviews, aligning the business model with actual training usage. The admin panel gives Blue Elephants Solutions full control over pricing, tokens, scenarios, personas, and reporting, enabling them to run different Pro offerings for universities, bootcamps, and corporate clients.