VendorForge AI hilft Resellern beim Weiterverkauf mit KI-Copilot
VendorForge AI ist eine autonome Open-Source-Workspace-Lösung für unabhängige E-Commerce-Reseller und Secondhand-Händler. Das im Rahmen der Hacktoberfest AI Challenge entstandene Projekt soll aus ungeordnetem Lagerbestand Umsatz machen.

Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle Submission 💸
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle
VendorForge AI is an autonomous side-hustle workspace and revenue engine for independent e-commerce resellers, vintage curators, and secondhand merchants.
There are over 30 million part-time resellers selling on Etsy, eBay, Shopify, Poshmark, and Mercari. Every single reseller wrestles with two fatal bottlenecks:
Any reseller or side-hustler sourcing physical goods who wants to turn their weekend finds into cash without spending their entire week writing descriptions. In our validated pilot, a reseller managing 2,400+ online sales confirmed a willingness to pay $15/month after saving over 3 hours of listing labor on a single Sunday batch.
The complete source code is open-source and MIT-licensed on GitHub:
https://github.com/saquib-shahid/vendorforge-ai Enter fullscreen mode Exit fullscreen mode Architecture Diagram ┌─────────────────────────────────────────────────────────────────────────────┐ │ VENDORFORGE AI AGENT PIPELINE │ └─────────────────────────────────────────────────────────────────────────────┘ │ [ Sourced Item Intake & Photo Specs ] │ ▼ ┌──────────────────────────────────────────────┐ │ Step 1: MongoDB Atlas Semantic Comp Memory │ │ - Atlas Vector Search over store history │ └──────────────────────┬───────────────────────┘ ▼ ┌──────────────────────────────────────────────┐ │ Step 2: SerpApi Live Marketplace Grounding │ │ - Scrapes active eBay & Etsy sold comps │ └──────────────────────┬───────────────────────┘ ▼ ┌──────────────────────────────────────────────┐ │ Step 3: TabPFN-3.5 Tabular Predictive ML │ │ - In-context Bayesian price & velocity ML │ │ - Computes 14-day sale probability & margin │ └──────────────────────┬───────────────────────┘ ▼ ┌──────────────────────────────────────────────┐ │ Step 4: Google Gemma 2 Copy Synthesis │ │ - Gemma 2 (9B/27B) open-weight instruction │ │ - Etsy (13 tags, story) + eBay (80ch, specs)│ └──────────────────────┬───────────────────────┘ ▼ ┌──────────────────────────────────────────────┐ │ Step 5: ElevenLabs Voiceover Reel Narration │ │ - 15-second social reel audio pitch │ └──────────────────────┬───────────────────────┘ ▼ ┌──────────────────────────────────────────────┐ │ Step 6: Sentry Agent Tracing & Observability│ │ - Real-time spans, latency, token metrics │ └──────────────────────────────────────────────┘ Enter fullscreen mode Exit fullscreen mode 🛠️ How I Built It VendorForge AI is built using Node.js, Express, and Vanilla CSS, coordinating a multi-partner AI stack:
For copy synthesis, we used Google DeepMind's open-weight Gemma 2 ( gemma-2-9b-it ). Gemma 2 punches far above its weight class, generating rich storytelling descriptions that match Etsy's organic ranking criteria while strictly respecting eBay's 80-character title limit and item-specific filter taxonomy. It runs locally via Ollama or on low-cost cloud GPU instances with zero per-token marginal billing.
Standard text LLMs hallucinate prices because they cannot reason mathematically over tabular ledgers. We integrated TabPFN-3.5, Prior Labs' revolutionary tabular foundation model. TabPFN ingests the seller's past sales CSV ledger in-context without expensive fine-tuning. It computes:
The multi-step agent pipeline is orchestrated using the Mastra Agent Architecture. The agent deterministically transitions between memory lookup, external comp scraping, tabular inference, and copy synthesis while maintaining structured state.
Every step of the agent execution is instrumented with Sentry Agent Tracing. The telemetry inspector records individual spans ( llm_call, ml_inference, tool_call, db_lookup ), duration in milliseconds, token counts, and calculates exact dollar savings compared to closed commercial APIs.
Generates a 15-second natural human audio voiceover pitch for each listing, making it effortless for resellers to post video listings to TikTok, Instagram Reels, and YouTube Shorts.
The full-stack application is deployed to Render using a native render.yaml blueprint with continuous deployment and health monitoring.
"Why does open innovation matter for what you built? What did it make possible that a closed API wouldn't?"
For small-scale entrepreneurs and side-hustlers, open-source AI is not a philosophical preference— it is the difference between a viable business and financial failure:
We'd love to see how you built it. Save your agent session with DevRelay and embed it in your post, or link to it. It's optional, but it helps the judges understand your process.
VendorForge AI was developed and paired with an autonomous AI coding agent. You can inspect the complete, untruncated development session transcript directly in our open-source repository:
🔗 View Full Agent Session Transcript on GitHub
To satisfy the challenge bonus criteria, we tested VendorForge AI with a real-world vintage reseller:
Tester: Marcus S. Profile: Vintage & workwear clothing curator on Etsy, Depop, and Instagram (2,400+ lifetime sales). Item Tested: 1990s Carhartt J97 Detroit Jacket (Moss Green) Results:
VendorForge AI is proudly submitted for the Overall Grand Prize and the following 8 partner categories:
In architecting VendorForge AI, we drew direct inspiration from community discussions on open-source AI and agent design on DEV:
VendorForge AI is open-source under the MIT License. Built for builders, side-hustlers, and open innovation.
Expand Saquib Shahid Saquib Shahid Saquib Shahid Follow I am Saquib Shahid, software developer, learner, passionate coder. Joined Feb 16, 2025 • Oct 14 Dropdown menu Copy link Hide Insighfulll
Like comment: 2 likes Like Comment button Reply Collapse Expand Saquib Shahid Saquib Shahid Saquib Shahid Follow Backend Engineer with 2+ years of production experience building microservices at scale using Node.js, TypeScript, Kafka, and Redis. Experienced in distributed systems and CI/CD pipelines. Email saquibk894@gmail.com Location Kolkata, India Education B.Tech in Computer Science & Engineering Pronouns dev Work Backend Engineer @ Edwid Technologies Pvt Ltd Joined Jan 3, 2023 • Oct 14 Dropdown menu Copy link Hide Thanks