DEV Community: Mayuresh Pandit

Building an Autonomous Disaster Relief Grid with Gemini AI, Eleven Labs, Solana & Snowflake for Weekend Challenge: Generosity Edition

Mayuresh Pandit — Mon, 07 Sep 2026 06:04:20 +0000

This is a submission for Weekend Challenge:Generosity Edition

]

What I Built

During crises and natural disasters, traditional relief faces some issues, such as aid arriving with the wrong resources or a lack of transparency while handling the funds. Donors rarely know whether the funds actually reach on the ground or not. Here is the comes KindLink as a solution with a decentralised autonomous disaster response system to designed to coordinate with multi-modal generosity in real time. It unifies monetary and non-monetary aid(food, ration, transport) with on-chain transactions. It also provides an impact receipt to the donor so they will actually know where the funds are utilized.

Demo

In English :-https://youtu.be/wgNX2KGTtFU?si=Y8vL6usT6jUGNDPK

In Hindi :- https://youtu.be/tZvU03fhlrw?si=eHUalW5M0x3-4DjO

Code

Github repo :- https://github.com/GamersStop/KINDLINK-The-Autonomous-Generosity-Grid

/backend :- Used Python FastAPI ,SQLModel and python integration with solders and snowflakes

/Frontend :- Used next.js for the responsive screen across all the devices.

docker-composer.yml :- It uses for the smooth deployment

How I Built It

As explained in the video, we have 3 flows in the application to achieve that, we used the below technology

Backend on FastAPI & PostgreSQL:-

The backend is built with Python, FastAPI, and SQLModel, running inside a Docker container for seamless deployment. It handles all incoming requests from the frontend, while dedicated API endpoints process tasks like SOS and plea analysis. To organize and route requests to their specific endpoint files, we utilized FastAPI routers. Additionally, all database schemas and data structures are defined in the models directory. If volunteer click on the pay by sol button then those sponcership is directly implement via Solana devnet using the python native solders. It will generate the Solana transaction signature, which you can directly verify with the Solana Explorer. For admin dashbord we did integration with snowflakes to make charts from analytical database which provides us the great trend analysis so admin will know hows the trends were working hows the funds flows vs hows the commitment of efforts were flows with their solana on chain transactions.

Frontend Build with Next.js

We chose Next.js for the frontend with the main motive of providing a responsive ui across all devices.All the admin related UI is in /admin folder and for session maintenance, we use the components to guard on our two ngo and giver flow and use the HTTP only sessions.

Prize Categories

Best Use of Google AI

Unstructured Triage Extraction: Used the Gemini API to parse natural language distress calls and unstructured field pleas into standardized, categorized relief SKUs (rations, transport, medical supplies, physical labor).
Automated Urgency Scoring: Gemini evaluates contextual risk signals to assign priority ratings, enabling instant routing on the triage grid.

Best Use of ElevenLabs

Field Audio Dispatch: Converted critical mission updates and urgent resource alerts into natural, lifelike voice broadcasts using ElevenLabs.
Hands-Free Ground Coordination: Enabled field volunteers and first responders to listen to real-time status shifts and dispatch instructions without needing screen access.

Best Use of Snowflake

Transactional-to-Analytical Pipeline: Synchronized operational state from PostgreSQL into the KINDLINK_ANALYTICS database via snowflake-connector-python.
Multi-Modal OLAP Analytics: Built analytical SQL views (V_MODAL_AID_DISTRIBUTION and V_MISSION_CAPITAL_VELOCITY) to track resource allocation and capital velocity ratios across disaster zones without running into trial function restrictions.

Best Use of Solana

Autonomous Escrow Rails: Implemented trustless Devnet funding pipelines directly in the backend using solders and Solana RPC.
Verifiable Receipts: Every capital commitment broadcasts an immutable on-chain transaction that donors can independently audit via Solana Devnet Explorer.

Just need some ideas from other devs for my next package. I am thinking to build token budgeter and memory optimiser for AI agents. Currently, a lot of dev facing the issue of their tokens being burned even though they follow proper prompts and structure

Mayuresh Pandit — Sat, 05 Sep 2026 05:39:47 +0000

AffiStyle vs. Lasso: Is a $300+/Year Affiliate Tool Necessary?

Mayuresh Pandit — Wed, 02 Sep 2026 04:16:03 +0000

AffiStyle vs. Lasso: Is a $300+/Year Affiliate Tool Necessary?

If you run an affiliate site or review blog on WordPress, you know the drill: standard text links convert poorly, so you need high-impact product display boxes, comparison cards, and clear calls-to-action (CTAs).

For years, the default premium recommendation has been Lasso (formerly WP Lasso). It is polished, feature-heavy, and widely praised. But with pricing starting at $300+ every single year, many niche publishers, independent bloggers, and content creators are asking a valid question:

Do you actually need to spend hundreds of dollars a year just to show attractive product boxes and manage clean affiliate links?

Enter AffiStyle, a lightweight, performance-first plugin built natively for the WordPress block editor (Gutenberg).

Let's break down the head-to-head differences between AffiStyle and Lasso across performance, design, link handling, workflows, and long-term costs.

At a Glance: Key Differences

Feature	Lasso	AffiStyle
Primary Architecture	SaaS-style dashboard + Custom shortcode/embed engine	Native WordPress Block Editor (Gutenberg)
Pricing	~$289–$389+/year (recurring subscription)	100% Free on WordPress.org
Frontend Script Footprint	External CSS + Dynamic JS scripts	Zero frontend JS, pure vanilla CSS
Core Web Vitals Impact	Can cause layout shifts on unoptimized setups	0.000 CLS, built for 100/100 PageSpeed
Link Cloaking / Redirects	Built-in custom redirection engine	Built-in clean link redirection
Compliance Disclosures	Global / per-box FTC disclosures	Integrated FTC-compliant disclosure blocks
Coding Standards	Proprietary architecture	Strict WordPress Coding Standards (WPCS 3.0)

1. Speed, Page Weight, and Core Web Vitals

The single biggest operational difference between the two tools comes down to frontend performance.

Google’s Core Web Vitals directly impact mobile rankings. When a mobile visitor loads a post with 5 to 10 affiliate product cards, the way those boxes render can make or break your metrics:

Lasso: Uses its own database tables and asset pipeline. While it looks slick, loading dynamic scripts, remote tracking hooks, and heavier CSS files across multiple card displays can introduce Cumulative Layout Shift (CLS) and inflate the Total Blocking Time (TBT) on mobile devices.
AffiStyle: Engineered specifically to eliminate bloat. It requires zero external JavaScript dependencies on the frontend. The boxes and CTA buttons render server-side as native HTML elements styled with minimal vanilla CSS. That means 0.000 CLS and an easy path to maintaining 100/100 Google PageSpeed scores—even on media-heavy listicles.

If your SEO strategy depends on passing Core Web Vitals on low-powered mobile devices, AffiStyle’s minimal footprint gives you a distinct technical edge.

2. Editor Workflow: Native Gutenberg vs. Custom UI

How you build and insert product boxes impacts your daily publishing speed:

Lasso

Lasso operates with an internal dashboard that feels like an external SaaS app inside WordPress. You create "Displays" inside Lasso’s hub, pull Amazon data via its interface, and insert them into your posts via custom blocks or shortcodes.

The Benefit: If you need to change a single affiliate link that appears across 200 posts, updating it once in Lasso updates it globally.
The Drawback: It feels separated from the native Gutenberg editing flow. You are bouncing between post editing and a dedicated plugin dashboard.

AffiStyle

AffiStyle is built directly into the native WordPress Block Editor. You add an AffiStyle block exactly like you add a Paragraph, Heading, or Image block.

The Benefit: What you see in the editor matches what visitors see on the page. You get real-time visual control over layouts, badges, and button text without learning a proprietary third-party interface or touching shortcodes.
The Drawback: It focuses on direct page-level block composition rather than a massive multi-site centralized inventory database.

3. Link Cloaking & Search Compliance

Search engines and regulatory bodies have strict requirements for commercial content:

FTC Disclosures: Both plugins solve this requirement cleanly. AffiStyle provides built-in, automated disclosure styling so you don't have to manually type legal disclaimers on every review box.
Search Engine Attributes: AffiStyle automatically enforces rel="sponsored nofollow noopener" on outbound commercial buttons. You stay 100% compliant with Google’s link-attribution guidelines without hunting through block attributes.
Clean Link Redirection: Lasso features robust custom redirect management. AffiStyle also comes with native link cloaking built in, allowing you to transform messy affiliate query strings into clean, readable redirect URLs without needing a secondary plugin like Pretty Links.

4. The Cost Equation: $0 vs. $300+/Year

When evaluating ROI, consider where you are in your publishing journey:

Who is Lasso Best For?

If you manage an enterprise network of 50+ affiliate sites with dedicated full-time editors, massive teams, and a five-figure monthly affiliate budget, Lasso's price tag is a rounding error. Its inventory dashboards and out-of-stock keyword tracking can save large publishing teams significant maintenance hours.

Who is AffiStyle Best For?

If you are an independent blogger, niche publisher, or developer who wants:

Fast-loading, conversion-optimized affiliate cards,
Full compliance with Google Core Web Vitals (0 CLS, pure CSS),
Built-in link cloaking and FTC compliance,
Zero annual subscription overhead,

Paying $300+ every year for display boxes is simply unnecessary.

Final Verdict

Lasso is a heavy-duty management suite built for enterprise affiliate teams.

AffiStyle is the modern, performance-first alternative designed for the Gutenberg era. It provides the visual polish, mobile responsiveness, and click-through power of dedicated product display boxes—without dragging down your PageSpeed or cutting into your affiliate profits.

Ready to upgrade your affiliate boxes without slowing down your site?

Download AffiStyle for free from the official WordPress.org Plugin Directory and test your mobile scores today.

Building "112 for Dogs": How I Combined Gemini AI, Solana, and Voice Agents to Save Strays

Mayuresh Pandit — Mon, 17 Aug 2026 06:13:02 +0000

This is a submission for Weekend Challenge: Dog Days Edition

What I Built

PawID & Care is an enterprise-grade, multi-role emergency response and biometric identification platform built for community animal welfare and stray management. Operating as a "112-for-dogs" system, the platform bridges cutting-edge artificial intelligence, distributed ledgers, enterprise analytics, and autonomous voice agents into a single unified workflow.

The core goal is to solve the fragmentation in animal rescue: pet owners lose dogs, street animal injuries go unreported, and cities lack real-time community health tracking. PawID & Care provides instant biometric triage, role-based portals for Owners, Rescuers, and Vets, and real-time emergency voice dispatching.

Demo

📹 Watch the Demo Video: https://youtu.be/_B-2dL2fDX4

Code

GitHub Repository: [https://github.com/GamersStop/paw-id-care]


bash
# Clone the repository
git clone [https://github.com/GamersStop/paw-id-care](https://github.com/GamersStop/paw-id-care)

# Install dependencies
npm install

# Start the server
npm start

Safeguard Your AI Apps: Introducing ai-prompt-firewall

Mayuresh Pandit — Thu, 13 Aug 2026 15:05:18 +0000

Building AI-powered applications is exciting, but transmitting unfiltered user input directly to Large Language Model (LLM) providers creates significant security and compliance risks.

From accidental API key leaks (sk-proj-...) to exposed PII (emails, phone numbers, internal IPs), unmonitored prompts can violate privacy regulations and expose sensitive system credentials.

To solve this, I built and published ai-prompt-firewall — a lightweight, zero-dependency Node.js and TypeScript library designed to intercept, sanitize, and secure prompt streams before they hit your LLM provider.

🚀 Key Features

⚡ Zero External Dependencies: Ultra-lightweight footprint with fast execution times.
🛡️ Built-in Pattern Detection: Automatically identifies critical tokens (OpenAI, Anthropic, AWS, Stripe, GitHub, Google API, Slack, Private Keys, Bearer Tokens) and PII (Emails, Phone Numbers, IPv4 Addresses).
🎯 Three Operational Modes:
- redact: Replaces detected secrets with safe placehold tags (e.g., [OPENAI_KEY_REDACTED]).
- block: Triggers a zero-trust block state when sensitive tokens are detected.
- warn: Passes the prompt while capturing findings for background auditing.
📊 SIEM-Ready Auditing: Returns exact character offsets (startIndex, endIndex, length) for security compliance logging.
🏢 Multi-Tenant Support: Pre-compile isolated firewall instances with custom regex patterns per tenant.

📦 Quick Start

1. Installation

Install directly via the npm registry:

npm install ai-prompt-firewall

2. Basic Usage

import { scan } from 'ai-prompt-firewall';

const userPrompt = "Here is my secret key: sk-proj-1234567890abcdef1234567890abcdefABCDEF";

// Scan and redact in real time
const result = scan(userPrompt, 'redact');

console.log(result.safePrompt);
// Output: "Here is my secret key: [OPENAI_KEY_REDACTED]"

console.log(result.findings);
// Output: Detailed array containing token type, severity, and exact character offsets

3. Advanced Features

Custom Regex & Runtime Options
You can extend the firewall with custom domain-specific pattern checks at runtime:

const customPatterns = {
  INTERNAL_PROJECT_ID: /PROJ-[A-Z]{3}-\d{4}/g
};

const result = scan("Access details for PROJ-XYZ-9876", "redact", { customPatterns });

4. Multi-Tenant Pre-Compiled Firewall

For multi-tenant SaaS platforms, pre-compile dedicated firewall instances to optimize regex compiling performance:

import { createFirewall } from 'ai-prompt-firewall';

const tenantFirewall = createFirewall({
  customPatterns: {
    TENANT_BADGE: /BADGE-\d{5}/g
  }
});

const tenantResult = tenantFirewall.scan("Badge code BADGE-99887", "block");

🔗 Try It Out!
npm Package: https://npmjs.com/package/ai-prompt-firewall

GitHub Repository: https://github.com/GamersStop/ai-prompt-firewall

Feedback, issues, and contributions are welcome! If you find this package useful for your AI tech stack, give it a ⭐️ on GitHub!

Why I Built a Lightweight Form Validation Library for Modern Web Apps

Mayuresh Pandit — Thu, 06 Aug 2026 17:11:16 +0000

Hey everyone! 👋

When working on modern JavaScript and TypeScript applications—especially when integrating with frameworks like Angular—handling form validation is a daily task. However, I often found myself wanting a clean, straightforward solution without bringing in heavy, bloated dependencies.

To solve this, I decided to build and publish my own open-source package from scratch: universal-form-validator.

What it does:
Zero Dependencies: Keeps your project bundle lightweight and fast.

Flexible Schemas: Easily handles common validation requirements like strings, strict numbers, emails, dates, and passwords.

Framework Friendly: Tested and structured to plug smoothly into modern workflows.

If you are looking for a clean, minimalist validation engine for your next project, you can check out the repository or install it directly via npm:

npm:

npm i universal-form-validator

GitHub: universal-form-validator

I built this to solve a specific workflow problem, and I'd love to hear your thoughts or feedback if you try it out. Happy coding! 🚀