You will get AI Deal Flow Intelligence System — LLM + RSS + SEC Data Pipeline Next.js
Project details
An angel investment fund was drowning in noise — 10+ RSS tabs open every morning, SEC filings searched by hand, deals tracked in a shared Google Sheet. Three hours of analyst time wasted before 10am. Every day.
I built DealRadar: a private AI-powered deal flow dashboard that eliminates the manual work entirely.
What it does:
The system ingests RSS feeds (TechCrunch, VentureBeat, Crunchbase) and SEC EDGAR Form D filings automatically. A Groq-powered LLM (Llama 3) reads each article and extracts structured data — company name, funding stage, round size, investors, and sector — in under a second per deal.
Before any article even reaches the LLM, a keyword filter screens out irrelevant content. This keeps API usage lean even at scale — critical for a prototype budget.
Every deal is then scored 0–100 based on stage, funding amount, investor quality, and LLM confidence. Duplicates across sources are eliminated via MD5 hashing. The highest-signal deals rise to the top automatically.
Built in Next.js 14 with a FastAPI backend. Analysts filter by stage, sector, and status. One-click workflow: Interested → Tried → Pass → In Round. Per-deal notes saved to the database.
I built DealRadar: a private AI-powered deal flow dashboard that eliminates the manual work entirely.
What it does:
The system ingests RSS feeds (TechCrunch, VentureBeat, Crunchbase) and SEC EDGAR Form D filings automatically. A Groq-powered LLM (Llama 3) reads each article and extracts structured data — company name, funding stage, round size, investors, and sector — in under a second per deal.
Before any article even reaches the LLM, a keyword filter screens out irrelevant content. This keeps API usage lean even at scale — critical for a prototype budget.
Every deal is then scored 0–100 based on stage, funding amount, investor quality, and LLM confidence. Duplicates across sources are eliminated via MD5 hashing. The highest-signal deals rise to the top automatically.
Built in Next.js 14 with a FastAPI backend. Analysts filter by stage, sector, and status. One-click workflow: Interested → Tried → Pass → In Round. Per-deal notes saved to the database.
AI Algorithms
Autoencoder, Convolutional Neural Network, Gated Recurrent Unit, Generative Adversarial Network, Large Language Model, Linear Discriminant Analysis, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Classification, AI-Generated Art, AIOps, Conversational AI, Natural Language GenerationAI Development Language
PythonAI Tools
Bing AI, GitHub Copilot, Hugging Face, NVIDIA AI Platform, PyTorch, Replit, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, DALL-E, GPT-3, GPT-4, GPT-J, GPT-Neo, LLaMA, Midjourney AI, Stable DiffusionWhat's included
| Service Tiers |
Starter
$150
|
Standard
$300
|
Advanced
$550
|
|---|---|---|---|
| Delivery Time | 4 days | 6 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
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About Muhammad
Senior Ai Engineer | AI Agent Developer | AI Automation Expert
100%
Job Success
Islamabad, Pakistan - 4:59 am local time
I build autonomous AI agents, LLM pipelines, and n8n automation workflows — systems that read documents, make decisions, call APIs, and take action without constant human input. My work lives in production, not in Notion docs.
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⚡ WHAT I'VE ACTUALLY SHIPPED
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🔹 PropAgent.AI — Autonomous property investment agent that sources, analyzes, and scores real estate opportunities in real time
🔹 MedLex AI — Legal intake automation system; AI reads case details, extracts key facts, and routes to correct workflow — replacing hours of manual intake work
🔹 Crime Research Agent — AI pipeline that processed and structured 46 case files in under 2 minutes
🔹 Deal Flow Intelligence System — LLM + RSS + SEC filings pipeline for automated investment research and signal detection
🔹 AI WhatsApp Ordering System — High-performance ordering bot built on Groq + LLaMA 3.3 + n8n; handles orders, confirmations, and CRM updates end-to-end
🔹 Real Estate Voice Agent — LiveKit-based voice AI with RAG knowledge base + HubSpot CRM integration; books appointments autonomously
🔹 Autonomous SEO Content Pipeline — LLM + external API integration generating clinical health content at scale
🔹 AI Resume Parsing Pipeline — LLM-powered extraction, entity normalization, and structured output from unstructured CVs
🔹 Generative AI (ComfyUI + RunPod) — LoRA training, Flux image generation, serverless deployment for e-commerce (Shopify try-on, product variation generation)
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🛠 CORE CAPABILITIES
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AI Agents & Automation
n8n, Make . com, CrewAI, AutoGen, multi-agent orchestration, autonomous research agents, document processing pipelines
LLMs & RAG
LangChain, LlamaIndex, OpenAI (GPT-4o), Claude, Groq, LLaMA 3, Mistral, Pinecone, ChromaDB, FAISS, Qdrant — from simple Q&A to enterprise knowledge retrieval
Voice AI
LiveKit, Vapi, Retell AI, ElevenLabs, Deepgram — full voice agent pipelines with CRM and calendar integration
Generative AI & Image
ComfyUI, RunPod (serverless), Flux, LoRA/QLoRA fine-tuning, SDXL, virtual try-on, product image generation
Integrations
WhatsApp Business API, HubSpot, Shopify, Google Sheets, Notion, Airtable, Slack, REST APIs, Webhooks, SEC/RSS feeds
Backend
Python, FastAPI, Node Js, Next Js, Nest Js, Firebase, Supabase PostgreSQL, MongoDB, Docker, AWS, serverless architecture
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✅ GOOD FIT
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✔ You have a real workflow you want automated or AI-augmented
✔ You need something production-ready — not a prototype
✔ You want one person who can own the whole system, end to end
✔ Speed and reliability matter more than the cheapest quote
❌ NOT A FIT
✖ You want a ChatGPT wrapper built in a weekend
✖ You're still exploring AI with no defined use-case
✖ Price is the only variable in your decision
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💬 Let's talk. Tell me what's eating your team's time — I'll tell you exactly what an AI system can do about it, and what it'll take to build.
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Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Architecture Development
Implementation & Execution