u/Forsaken_Clock_5488

I just mastered CTTR but the PSP version, and I see in my opinion the achievements looks ugly comparing to the Ps2 version. I played the PSP version because it's smoother to emulate.
I wanna play the Ps2 version and start the game all over again to get the achievements, but that gives me an unemployed feeling, while I'm busy already nowadays. I just play games whenever I'm free, and I do achievements because it motivates me to finish the childhood games 100%. Other than that I'm not a gamer person. ( The second picture of the Ps2 version achievements is not mine, it's for the comparison )
Feel free to add me though: Adham10

Most real estate agencies are losing leads at 11 PM when no one's answering the phone.

I built an AI Virtual Assistant in n8n that handles the entire client conversation 24/7, without human intervention.

Here's what it does in a single chat message:

→ Checks calendar availability in real time
→ Books, reschedules, or cancels appointments automatically
→ Retrieves existing events on demand
→ Searches a private FAQ knowledge base (powered by Google Gemini embeddings) to answer property and agency questions
→ Finds documents from a connected file folder
→ Sends a confirmation email to the client instantly via Gmail
→ Remembers the full conversation using Postgres Chat Memory

The agent is powered by AI model, runs through a single AI Agent node, and every response is parsed and routed through a JavaScript Code node before any action is taken, keeping the logic clean and auditable.

No missed leads. No scheduling back-and-forth. No after-hours gaps.

Just a virtual assistant that works like your best employee, except it never sleeps.

Most real estate agents lose deals not because of bad leads, but because of slow follow-up.

I built an AI-powered CRM automation in n8n that fixes that. Here's how it works:

Every morning at a set time, the workflow automatically pulls new leads from Google Sheets and runs them through an AI scoring engine.

The AI enriches each lead by analyzing intent signals, urgency, and fit, then routes them into three tiers: Hot, Warm, or Cold.

🔴 Hot leads? A Slack alert fires instantly so the agent can call within minutes. A priority email goes out right away.

🟡 Warm/Cold leads? They enter a nurture sequence with automatically personalized emails and zero manual work.

Every action gets logged back to the CRM and appended to an audit sheet, so nothing ever falls through the cracks.

The result: faster response times, smarter prioritization, and agents focused only on leads that are actually ready to convert.

What if every new lead was qualified, scored, logged, and followed up with in seconds without a human lifting a finger?
That’s exactly what this AI-powered Lead Qualification workflow does.

I recently built an automated lead qualification system that works 24/7 to identify high intent prospects and streamline the sales process.
Here's how it works:
✅ Lead Capture: A webhook receives incoming leads from forms, ads, CRMs, or landing pages.
✅ Data Normalization: Lead information is cleaned and standardized to ensure consistent processing.
✅ AI Qualification: An LLM analyzes the lead details and determines fit, intent, and overall quality based on predefined criteria.
✅ Structured Parsing: AI outputs are converted into actionable fields such as lead score, qualification status, and lead tier.
✅ Smart Routing: The workflow automatically categorizes leads based on their qualification level.

🔥 Hot Leads
Instant alert sent to the sales team via email
Enables rapid response when buying intent is highest
📊 CRM Logging
Every lead is automatically recorded in Google Sheets for tracking and reporting
📧 Automated Follow-Up
Qualified leads receive personalized follow-up communications without manual intervention
⚡ Result: Faster response times, consistent lead evaluation, reduced manual work, and a scalable process that never sleeps.

AI workflows aren't just about automation; they're about helping teams focus on the conversations that actually drive revenue.

What if every new lead was qualified, scored, logged, and followed up with in seconds without a human lifting a finger?
That’s exactly what this AI-powered Lead Qualification workflow does.

I recently built an automated lead qualification system that works 24/7 to identify high intent prospects and streamline the sales process.
Here's how it works:
✅ Lead Capture: A webhook receives incoming leads from forms, ads, CRMs, or landing pages.
✅ Data Normalization: Lead information is cleaned and standardized to ensure consistent processing.
✅ AI Qualification: An LLM analyzes the lead details and determines fit, intent, and overall quality based on predefined criteria.
✅ Structured Parsing: AI outputs are converted into actionable fields such as lead score, qualification status, and lead tier.
✅ Smart Routing: The workflow automatically categorizes leads based on their qualification level.

🔥 Hot Leads
Instant alert sent to the sales team via email
Enables rapid response when buying intent is highest
📊 CRM Logging
Every lead is automatically recorded in Google Sheets for tracking and reporting
📧 Automated Follow-Up
Qualified leads receive personalized follow-up communications without manual intervention
⚡ Result: Faster response times, consistent lead evaluation, reduced manual work, and a scalable process that never sleeps.

AI workflows aren't just about automation; they're about helping teams focus on the conversations that actually drive revenue.

Still reviewing real estate lease documents manually?
I built an AI-powered workflow that reads lease agreements directly from Gmail, extracts key information, summarizes risks, and automatically logs everything to Google Sheets in minutes, not hours.

This workflow was built in n8n to automate the entire lease document analysis process from end to end:
📩 Gmail Trigger
The workflow starts whenever a new lease document arrives via email.
📄 PDF Extraction
The attached document is automatically parsed and converted into readable text.
🤖 AI Lease Analysis
Using an AI model, the system analyzes the lease agreement and extracts important insights such as:
Lease terms
Renewal clauses
Rent escalation details
Critical risks or red flags
Key obligations and deadlines
🧠 Structured AI Parsing
The AI response is then formatted into structured data for downstream automation.
📧 Automated Summary Email
A clean summary report is instantly sent to stakeholders for quick review.
📊 Google Sheets Logging
All extracted lease data is automatically stored in Google Sheets for tracking, reporting, and future analysis.
This kind of workflow can save real estate teams countless hours of manual review while improving consistency and reducing missed details.

AI agents + workflow automation are changing how operations teams handle documents.

Still reviewing real estate lease documents manually?
I built an AI-powered workflow that reads lease agreements directly from Gmail, extracts key information, summarizes risks, and automatically logs everything to Google Sheets in minutes, not hours.

This workflow was built in n8n to automate the entire lease document analysis process from end to end:
📩 Gmail Trigger
The workflow starts whenever a new lease document arrives via email.
📄 PDF Extraction
The attached document is automatically parsed and converted into readable text.
🤖 AI Lease Analysis
Using an AI model, the system analyzes the lease agreement and extracts important insights such as:
Lease terms
Renewal clauses
Rent escalation details
Critical risks or red flags
Key obligations and deadlines
🧠 Structured AI Parsing
The AI response is then formatted into structured data for downstream automation.
📧 Automated Summary Email
A clean summary report is instantly sent to stakeholders for quick review.
📊 Google Sheets Logging
All extracted lease data is automatically stored in Google Sheets for tracking, reporting, and future analysis.
This kind of workflow can save real estate teams countless hours of manual review while improving consistency and reducing missed details.

AI agents + workflow automation are changing how operations teams handle documents.

Most real estate assistants stop at answering questions.

This one actually runs the business.

I built an AI-powered real estate automation workflow in n8n

that handles conversations, scheduling, lead qualification, memory, notifications, and follow-up all in one system.

This workflow acts like a full AI operations assistant for a real estate business.

Here’s what it does behind the scenes:

- Receives and processes incoming client chat messages

- Uses an AI Agent with memory for contextual conversations

- Checks appointment availability automatically

- Creates, reschedules, or cancels appointments

- Updates property data dynamically

- Stores and retrieves long-term knowledge using vector embeddings + Supabase

- Sends notifications and confirmations through Gmail

- Uses JavaScript logic nodes for custom decision-making and workflow control

The goal wasn’t just to build a chatbot.

The goal is to create an AI system that supports day-to-day operations and reduces manual work for agents.

This is where AI automation becomes truly useful:

not just generating text, but connecting tools, memory, logic, and actions into one intelligent workflow.

AI agents are moving beyond simple conversations, they’re becoming operational systems.