DEV Community: Piyush Gupta

EchoDesk — Turn Google Reviews into Revenue & Operational Fixes for Local Businesses

Piyush Gupta — Sat, 17 Oct 2026 14:23:36 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

What I Built

Most small business owners—cafe operators, dentists, salon owners, boutique retail managers—live in dread of their Google Maps notifications.

A single 2-star review about slow service can ruin their morning. Meanwhile, enterprise reputation management software like Birdeye or Yext costs $200 to $500 per month, locks them into punitive annual contracts, and overwhelms them with corporate jargon. Independent business owners don't need a bloated CRM; they need answers to two simple questions:

"What is actually breaking on my floor or in my kitchen during rush hour?"

"How do I draft an empathetic, professional reply to this customer in 10 seconds without sounding like a robotic bot?"

EchoDesk is an open-source, privacy-first review intelligence audit tool and micro-SaaS side hustle built specifically for independent storefronts.

⚡ The Core Loop:

🔗 1-Click Live Google Maps Extraction (Powered by SerpApi):

Paste any Google Maps URL or enter a business name (e.g. Blue Tokai Coffee, Benne Cyberhub). EchoDesk connects directly to Google's live review graph, fetching customer reviews, star ratings, reviewer metadata, and timestamps without requiring cumbersome Google Business Profile OAuth verification.
🧠 AI Sentiment & Operational Bottleneck Clustering:

Instead of just showing average stars, the open-weight AI engine categorizes reviews into operational themes:
- ⏳ Peak-Hour Waiting Delays
- 🤝 Staff Hospitality & Service
- 🍽️ Menu Consistency & Quality
- ✨ Ambiance & Cleanliness
- 💰 Value & Pricing Perception
✍️ Brand-Voice AI Reply Assistant:

Drafts thoughtful, context-aware replies tailored to individual customer experiences in three distinct brand tones:
- Warm & Professional
- Short & Friendly
- Apologetic & Service-Focused Replies never hallucinate fake discounts or contact info, address customers by name, and are copy-ready in one click.
📋 Interactive Operational Action Checklist:

Translates recurring customer complaints into concrete business fixes (e.g., "Prep secondary line between 7–9 PM to reduce pickup delays"). Operators can click "Add Action", manage a live interactive checklist, and export it as a CSV for floor managers.
💰 "Fake Door" Demand Validation & Waitlist Engine:

To prove commercial demand before building complex billing infrastructure, EchoDesk features a high-converting Pro Waitlist Modal ("50% off lifetime access") connected to a real-time Owner Analytics Demand Tracker that logs interested business owners and exports the waitlist to CSV.

Demo

🌐 Live Web App (Hosted on Render): https://echodesk-6qd3.onrender.com
⚡ API Health Endpoint: https://echodesk-6qd3.onrender.com/api/health
🧪 Instant Test Mode: If you don't have a live Google Maps link on hand, click "Take a Benchmark Business for a spin" on the dashboard to immediately analyze 48 realistic customer reviews across dining, wait times, and hospitality.

Code

EchoDesk is 100% open-source under the MIT license:

guptapiyush16 / EchoDesk

EchoDesk — Online Review Intelligence & Operational Fixes ⚡

Turn customer reviews into revenue, brand loyalty, and operational decisions.
A fast, privacy-first, one-time online audit tool and micro-SaaS for local businesses.
Built for Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle.

🌟 The Problem & The Solution

Independent storefront owners—cafe operators, dentists, salon owners, boutique retail managers—live in dread of their Google Maps notifications. A single 2-star review about slow service can ruin their morning.

Meanwhile, enterprise reputation management software like Birdeye or Yext charges $200 to $500 per month, locks owners into annual contracts, and buries them in corporate jargon. Small business owners don't need a bloated CRM; they need answers to two simple questions:

"What is actually breaking on my floor or in my kitchen during rush hour?"
"How do I draft an empathetic, professional reply to this customer in 10 seconds without sounding like a…

View on GitHub

🔗 Repository: https://github.com/guptapiyush16/EchoDesk

Quickstart (Run Locally in 60 seconds):

# Clone the repository
git clone https://github.com/guptapiyush16/EchoDesk.git
cd EchoDesk

# Install dependencies
npm install

# Start backend server & frontend dev server
npm start
npm run dev

How I Built It

EchoDesk combines lightweight open-weight AI architectures, resilient live web data extraction, and serverless-friendly cloud hosting:

1. 🔍 Live Review Extraction via SerpApi

Extracting reviews from modern Google Maps single-page apps is notoriously brittle with headless scrapers. EchoDesk integrates SerpApi's Google Maps Reviews Engine via a protected Node.js backend proxy (server/server.mjs). It sanitizes input queries, fetches real-time customer comments with high fidelity, and formats review snippets, ratings, and dates into normalized JSON.

2. 🤖 Open-Weight AI Intelligence (Gemma & Google AI)

The AI pipeline handles two heavy operational workloads:

Zero-Shot Root-Cause Extraction: Parses batches of raw reviews into fine-grained sentiment distributions and pinpointed operational problems.
Brand Voice Synthesis: Uses structured system prompts to generate human-grade, tone-matched review responses under 120 words without generic platitudes or robotic phrasing.

3. ☁️ Production Runtime on Render

Render powers the entire production lifecycle:

Configured via Infrastructure-as-Code with render.yaml.
A unified Node.js / Express service serves the compiled React 18 / Vite client bundle, hosts the secure authenticated REST API proxy, manages session security, and executes health monitoring.
Zero-downtime continuous deployment connected directly to the GitHub main branch.

4. 📊 Demand Validation & Data Persistence

Zero Lock-in Local Storage: Client-side caching preserves business profiles and action items across tab refreshes.
JSON Waitlist Engine: Saves prospective customer leads securely into data/waitlist.json on the server, complete with deduplication, timestamping, and instant CSV export for marketing outreach.

Why Does Open Innovation Matter?

For an indie developer building a sustainable side hustle, open innovation is the difference between an unviable money pit and a profitable micro-SaaS:

Vastly Superior Unit Economics:

Closed enterprise reputation platforms charge hundreds of dollars per seat because they carry immense operational overhead. By building on lightweight, cost-effective models and open web standards, EchoDesk's cost per audit is fractions of a cent. This allows us to offer independent neighborhood cafes a free audit and a paid tier starting at just ₹299/month ($3.50/mo) while maintaining 90%+ gross margins.
Data Privacy for Local Businesses:

Small business owners are rightfully cautious about sharing internal feedback and customer identities with closed, data-harvesting ad networks. EchoDesk's modular architecture processes customer reviews securely through private proxies with zero retention of customer PII on third-party tracking databases.
No Vendor Lock-in or Arbitrary API Hikes:

Relying entirely on a proprietary end-to-end platform leaves a founder vulnerable to overnight pricing changes or sudden terms-of-service bans. Open innovation allows EchoDesk to swap model weights, transition from cloud-hosted inference to local on-premise models, and customize prompts to match hyper-specific local industries.

My Agent Session

EchoDesk was developed, architected, and refactored using GitHub Copilot's CLI and agentic coding workflows:

Scaffolding the React 18 / TypeScript / Vite frontend with custom CSS tokens.
Structuring the resilient SerpApi proxy to parse Google Maps place queries and pagination.
Authoring the declarative render.yaml specification for zero-configuration cloud deployments.
Implementing the "Fake Door" Pro waitlist modal with server-side validation and CSV export utilities.

All iterative development steps and architectural refactors are documented transparently in the GitHub commit history.

My First User

To test if real business owners would actually pay for this, I shared EchoDesk with the owner of a busy local specialty bakery and espresso bar:

What they did: Pasted their Google Maps listing into EchoDesk and ran an instant audit on 35 recent reviews.
The "Aha!" moment: The dashboard immediately flagged: ⚠️ Waiting Time & Delays: 32% of 2-star and 3-star reviews mentioned long morning queues during the 8:30 AM–10:00 AM rush. The owner remarked: > "I knew we were slammed in the morning, but I didn't realize customers were specifically complaining about the toast-warming delay at the counter. The AI pointed out the exact line bottleneck in 5 seconds."
The Response: In less than 3 minutes, they used the AI Reply Assistant to draft and copy personalized replies to 8 pending reviews that had been sitting unanswered for weeks.
Commercial Validation: When they hit the 50-review limit and saw the "Upgrade to Pro — 50% Off Lifetime Access" modal, they immediately entered their business email to claim early founder pricing. That real signup proved demand on day one!

Prize Categories

🌟 Featured Categories:

Best Use of Render ($200 USD): Render acts as our end-to-end production runtime. Configured via render.yaml, it hosts the Node.js API, serves the optimized Vite SPA bundle, manages environment security, and handles continuous deployments.
Best Use of Gemma ($200 USD): Powered by Google's open-weight AI models via Google AI Studio for review sentiment scoring, operational theme classification, and tone-matched customer reply synthesis.

🤝 Partner Categories:

Best Use of SerpApi ($100 USD): SerpApi's Google Maps Reviews API is the core data ingestion engine of EchoDesk, allowing business owners to pull live reviews, star ratings, and location metadata directly from a public URL.
Best Use of GitHub Copilot ($100 USD): Developed and iterated using GitHub Copilot's coding agent and terminal tools to architect API bridges, build custom UI tokens, and write the CSV streaming pipeline.

Turn complaints into operational fixes, protect your brand, and turn customer reviews into your biggest growth engine! ⚡📈

WildDex - The Real-World Field Guide & IRL Pokédex Powered by Render

Piyush Gupta — Thu, 08 Oct 2026 07:33:00 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

What I Built

Most apps are engineered to maximize your screen time. Endless feeds, streaks, and engagement hooks keep you indoors, eyes glued to a display.

WildDex does the exact opposite. It is an installable, mobile-first Progressive Web App (PWA) with a single mission:

"The AI isn’t trying to keep you on the screen. It gives you a reason to put the phone down and touch grass."

🌿 The Core Loop:

🎮 Daily Quests (Quest Master): Every morning, the AI Quest Master analyzes your local city, interests (trees, birds, insects, flowers, domestic animals, minerals), and time budget (15, 30, or 60 min) to generate 3 safe outdoor quests:
- 📸 Scan: Find and photograph a specific specimen you haven't seen today.
- 👣 Walk: Take a 1.0 km walk with live HTML5 GPS distance tracking.
- 👀 Observe: Notice a subtle detail or seasonal shift in your neighbourhood.
📸 AI Discovery Scanner: When you spot something intriguing outside (a plant, bird, insect, mushroom, rock, or animal), open the camera viewfinder. The multimodal vision model analyzes the photo, providing an honest confidence rating (e.g., Golden Retriever 99% or Indian Banyan 91%), native habitat details, and natural history field facts.
📖 Your Real-World Pokédex: Every unique species is deduplicated and permanently cataloged. Photographing familiar species rewards bonus XP for revisiting local nature (Already discovered! 🌳 +5 XP).
⭐ Level Up in Real Life: Complete quests and document real-world biodiversity to earn XP, level up your explorer rank (from Junior Scout to Apex Trailblazer), and build consecutive daily outdoor streaks.
🗺️ Trail Log & Adventure Map: Tracks distance walked, active minutes, and plots your sightings on a live radar breadcrumb trail.

WildDex is built for everyday walkers, nature lovers, families, and anyone needing a playful RPG reason to step outside and explore.

Demo

🌐 Live Web App (Hosted on Render): https://sidequest-0kzp.onrender.com
📱 Mobile PWA Ready: Open the link in iOS Safari or Android Chrome, select "Add to Home Screen", and WildDex launches as an installable standalone app with offline service worker caching.

Code

WildDex is 100% open-source under the MIT license:

guptapiyush16 / SideQuest

WildDex — Production PWA

Core Loop: Go outside → get a quest → do something → discover something → collect it → earn XP.
"The AI isn’t trying to keep you on the screen. It gives you a reason to put the phone down."

The repository contains one canonical app: the browser PWA in index.html, styles.css, js/, assets/, and the Node/Express API in server.js.

📱 How to Run & Install as a Mobile PWA

1. Run Locally

The app is currently running on http://localhost:3000.
To restart the server at any time:

npm install
npm start

The server loads local development values from atlas-credentials.env. Keep that file private. For Render, configure the same variables in the service environment.

The PWA and API run from the same origin. Atlas stores accounts, progress, and GridFS photo files behind authenticated API routes.

Managed AI deployment

Configure OPEN_ROUTER_APIKEY…

View on GitHub

🔗 Repository: https://github.com/guptapiyush16/SideQuest

How I Built It

WildDex combines a modern local-first PWA, a resilient dual-provider AI pipeline, and production cloud infrastructure:

1. 🤖 Resilient Multimodal AI Architecture

WildDex powers its core experience through two dedicated server-side AI engines:

🎮 Quest Master Engine: Dynamically constructs structured, context-aware quests strictly bounded by safety guidelines (public parks, no trespassing, realistic walking targets).
📸 Field Guide Vision Scanner: Multimodal AI model that classifies camera photos with honest uncertainty estimation. It outputs ranked candidate distributions, confidence scores, and natural history facts.
Dual-Provider Resilience: Implemented a zero-downtime failover pipeline in Node.js (api/ai.js). If primary requests encounter high-demand spikes or rate limits, the runtime automatically fails over within seconds so mobile users are never left hanging on a trail.

2. ⚡ Production Runtime on Render

Render powers the entire production lifecycle:

A unified Node.js / Express web service declared via infrastructure-as-code in render.yaml.
Serves the installable PWA frontend, runs the authenticated REST API, and hosts the server-side AI proxy so API secrets are never exposed in browser bundles.
Automatic continuous deployment connected directly to GitHub main with health check monitoring at /api/health.

3. 🍃 Data & Media Layer on MongoDB Atlas

User Accounts & Progression: Managed with secure JWT authentication and bcrypt password hashing.
Pokédex & Quest Sync: Stores unique species entries, duplicate sighting counts, and GPS coordinates.
MongoDB GridFS Bucket (photos): Captured field photos are compressed client-side (HTML5 Canvas down to 1200px at ~200KB) and streamed into MongoDB GridFS binary storage, linked directly to the user's discovery record.

4. 💻 Engineered with GitHub Copilot

Leveraged the GitHub Copilot coding agent and CLI in the terminal to scaffold PWA manifest configurations, architect the GridFS upload pipeline, and optimize client-side image compression routines.

Why Does Open Innovation Matter?

When technology is open and accessible, it empowers people to engage with the physical world instead of remaining trapped in walled gardens:

Open Web Standards Over App Store Walled Gardens: Built as an open Progressive Web App (PWA) using HTML5, Vanilla CSS, and Service Workers. Anyone on iOS or Android can install it immediately without app store gatekeepers, fees, or downloads.
Accessible Outdoor Education: Nature education should be available to everyone—students, park visitors, and community naturalists. Open innovation makes it possible to build lightweight, low-latency tools that work smoothly on budget devices and spotty mobile networks.
Transparent Science & Honest AI: Rather than pretending to be 100% omniscient, our open prompts demand transparent confidence distributions and field notes, encouraging explorers to verify observations and stay curious.

My Agent Session

This application was developed and iterated using GitHub Copilot's coding agent and terminal workflow. Copilot was used to:

Write and validate the render.yaml infrastructure-as-code specification.
Construct the client-side canvas compression pipeline to ensure fast, reliable mobile photo uploads.
Refactor the server-side AI failover proxy and MongoDB GridFS image streaming handlers.

(Session commits and architectural iterations are documented in the commit history of the GitHub repository).

Prize Categories

🌟 Featured Categories:

Best Use of Render ($200 USD): Render serves as our complete production runtime. Declared via render.yaml, it hosts the Node.js/Express service, serves the mobile PWA frontend, runs the secure AI runtime proxy, and automates zero-downtime GitHub deployments.

🤝 Partner Categories:

Best Use of MongoDB Atlas ($100 USD): MongoDB Atlas powers the persistent database layer—handling user authentication, Pokédex collections, XP progression, and storing captured discovery photos via a dedicated MongoDB GridFS Bucket.
Best Use of GitHub Copilot ($100 USD): Developed using the GitHub Copilot CLI and coding agent, accelerating infrastructure setup, PWA offline caching, and full-stack API integration.

Go outside, take a walk, look closer at the world around you, and start filling your WildDex! 🌿🎒

Deadline Buddy — The Open-Source Scholarship Compass That Explains Every Match (Built for a Friend)

Piyush Gupta — Sun, 04 Oct 2026 16:54:19 +0000

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

The Story: Building for a Friend Under a Mountain of PDFs

My close friend is a 3rd-year Computer Science undergraduate at NIT Karnataka, Surathkal in India. Like thousands of ambitious students around the world, their dream is to pursue a Master's degree abroad in AI and Distributed Systems.

A few weeks ago, I watched them spend an entire weekend buried under a mountain of open browser tabs: DAAD in Germany, EduCanada, Fulbright in the US, and Chevening and Commonwealth in the UK. Each scholarship program had 40- to 80-page PDF guidelines filled with dense institutional jargon:

"Does a 4-year Indian B.Tech degree count as final-year standing right now?"
"Does an 8.4 / 10 CGPA meet the 'first-class honours or 2:1 equivalent' threshold?"
"Does a national hackathon finalist certificate satisfy 'demonstrated community leadership'?"

Existing scholarship portals were useless: they either acted as clickbait lead-generation farms or slapped an opaque "87% Match" badge on a card without explaining why they qualified. The alternative—spending 20 hours drafting an essay only to be rejected over a technical disqualifier buried on page 52—was heartbreaking.

I built Deadline Buddy for my friend.

What Deadline Buddy Does

Deadline Buddy turns scholarship discovery into a transparent, stress-free 5-step loop:

📄 Zero-Friction Document Intake: Drop in unofficial transcripts, resumes, or certificates (PDF, DOCX, TXT) or click the 1-click sample button.
👤 Structured Profile Extraction: The system extracts key attributes (GPA, current year of study, degree, graduation year, skills, achievements) into an editable profile with supporting document quotes.
🌍 Destination Personalization: Pick a target country (USA, Canada, UK, Germany, Australia, Netherlands, Singapore, Japan), immediately contextualizing currencies, deadlines, and official guides.
⚖️ Deterministic Eligibility Matching: Instead of letting an LLM guess eligibility, pure deterministic code evaluates published requirements against the profile, categorizing each award into Eligible (✓), Needs Verification (🟡), or Not Eligible (✕).
🔍 The Signature "Why?" Evidence Drawer & AI Strategy Advisor:
- Clicking any status badge reveals a side-by-side audit trail: the exact published clause, the student's extracted evidence, the source document quote, and a link to the official university portal.
- ⚡ Ask Open AI Strategy Advisor: Generates a personalized gap plan with feasibility scoring and alternative scholarships.
- 🧪 Open AI Guideline Lab: Paste raw institutional PDF announcements to test real-time guideline extraction.
⏳ Deadline-First Shortlist: Saved opportunities are prioritized by nearest deadline so students never miss an application window.

Demo

🌐 Live Deployed Application: https://deadline-buddy-nine.vercel.app/
⚡ 1-Click Judge Walkthrough: On the landing screen, click ⚡ Load Sample Student Documents (1-Click Demo) to instantly populate a real-world academic profile and test the deterministic rules engine across 26 real scholarships!

Code

guptapiyush16 / Deadline-Buddy

🎓 Deadline Buddy — The Open-Source Scholarship Compass

"Find scholarships you're actually eligible for — without reading hundreds of PDF guidelines."
Built for the Hacktoberfest 2026 Weekend Challenge: Build for a Friend.

📖 The Story: Building for a Friend

My close friend is a 3rd-year Computer Science undergraduate at NIT Karnataka, Surathkal in India. Like thousands of ambitious students worldwide, their dream is to pursue a Master's degree abroad in AI and Distributed Systems.

A few weeks ago, I watched them spend an entire weekend buried under dozens of open browser tabs: DAAD in Germany, EduCanada, Fulbright in the US, Chevening and Commonwealth in the UK. Each scholarship program had 40- to 80-page PDF guidelines filled with dense institutional jargon:

"Does a 4-year Indian B.Tech degree count as final-year standing right now?"
"Does an 8.4 / 10 CGPA satisfy the 'first-class honours or 2:1 equivalent' threshold?"
"Does a…

View on GitHub

GitHub Repository: https://github.com/guptapiyush16/Deadline-Buddy
Tech Stack: React 19, TypeScript, Vite, Tailwind CSS, Vitest (11/11 passing tests), Client-side PDF/DOCX Parsing (pdfjs-dist + mammoth).
Zero API Keys Required: Runs 100% in-browser on client hardware with 0 external API dependencies.

How I Built It

The Architecture: Open AI for Extraction, Code for Truth

The single biggest engineering mistake in AI applications is letting a non-deterministic LLM make hidden decisions. If you ask an LLM: "Does this student qualify for this scholarship?", it will frequently hallucinate or give inconsistent answers.

Deadline Buddy is built on a defensible, split-brain architecture:

Open-Source AI / Open Weights: Used where language models excel — extracting structured JSON from messy PDFs/transcripts and explaining complex mismatches in plain English.
Deterministic TypeScript Code: Used where mathematics and logic belong — comparing GPA scales, academic years, and citizenship lists.

[ Uploaded Documents (Resume / Transcripts / Certificates) ]
│
▼
┌─────────────────────────────────────────────────────┐
│ Open-Weight Extractor / Local AST Document Pipeline │
└──────────────────────────┬──────────────────────────┘
│ (Structured JSON Profile + Quotes)
▼
┌─────────────────────────────────────────────────────┐
│ Deterministic Code Rules Engine │
│ (shared/eligibility.ts) │
│ │
│ Requirement Student Profile Result │
│ ───────────────────────────────────────────────── │
│ Citizenship: India India ✓ │
│ Min GPA ≥ 7.5 8.4 / 10 ✓ │
│ Final Year Standing 3rd year of 4 ✕ │
└──────────────────────────┬──────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────┐
│ Three-State Explainable Evaluation │
│ 🟢 Eligible 🟡 Needs Verification 🔴 Ineligible
└──────────────────────────┬──────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────┐
│ Interactive "Why?" Evidence Drawer & Shortlist │
│ • Exact supporting quotes from your documents │
│ • Open AI Strategy Advisor with gap workarounds│
└─────────────────────────────────────────────────────┘

The Three Eligibility States

🟢 Eligible: Every checkable published requirement strictly passes.
🔴 Ineligible: A hard rule failed (e.g. scholarship requires a completed Bachelor's degree, but the student is currently in year 3).
🟡 Needs Verification (The Crucial Third State): The scholarship requires subjective criteria (like "community leadership") or university nomination that cannot be conclusively proven from the transcript. We refuse to guess or hallucinate an approval when proof is missing.

The GPA Uncertainty Band

International GPA scale conversions vary across universities. Deadline Buddy enforces an explicit uncertainty threshold:


typescript
const diff = studentGpaRatio - requiredGpaRatio;
if (diff >= GPA_UNCERTAINTY_BAND) return check(req, "pass", ...);
if (diff <= -GPA_UNCERTAINTY_BAND) return check(req, "fail", ...);
return check(req, "unknown", ...); // Refuse to guess borderline scores!