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AtlasPE — Enterprise AI Operations & PMO Control Center
Built entirely with Lovable for the #lovablechallenge.
AtlasPE is an elite, full-stack AI operations platform built for high-end management consultants and ISO 9001 auditors, transforming standard appointment booking into an automated enterprise control center.
Key Features Built:
• AI Process Mining & ISO Readiness Engine: Instant diagnostic tool measuring compliance scores and cost-leakage.
• Automated SOW & Proposal Generator: Compiles diagnostic data into a downloadable professional Statement of Work.
• Intelligent SLA Capacity Planner: Real-time executive scheduling grid.
• Executive Dark-Mode Command Center: Glassmorphism dashboard with live telemetry.
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Most inbound bottlenecks aren't caused by low lead volume—they happen during triage.
When inquiries roll into a Google Sheet or CRM, operations teams often waste 10–15 minutes per submission reading through messy paragraphs, deciphering budget mismatch, and manually deciding who gets an immediate call vs. a standard rate sheet.
Instead of adding a bulky CRM add-on, I documented a lightweight 3-step automation pipeline built inside Make:
Intake & Extraction: An active listener triggers immediately upon a new submission, extracting core variables: client scope, target deliverables, timeline, and stated budget.
Context-Aware Evaluation (Gemini 2.5 Flash): The payload passes through an AI evaluation node with strict guardrails:
Evaluates budget against minimum agency criteria.
Assigns a triage score: Hot (immediate priority), Warm (nurture), or Cold (disqualified/template reply).
Generates a strict 15-word operational summary—no long paragraphs.
Determines an automated next step (e.g., routing to an account lead or flagging for asynchronous follow-up).
Data Return & Clean Pipeline: Appends the structured classification directly back to the master operational tracker, keeping the sheet filterable and clean.
The outcome: The sales and operations team can filter the entire board by priority status in two clicks, cutting first-touch response time to minutes without manually reading every single submission.
I’ve documented the full scenario map, execution logic, and data schemas below.
Curious how other agency operators and automation leads here handle their lead enrichment layer—are you doing AI scoring at the form level, or later in the CRM pipeline?:
For the budget gate, I'd keep an unstated budget separate from one explicitly below your minimum. Does the Make route ask for clarification when the amount or currency is missing, so a potentially suitable lead doesn't fall into Cold by default?
FirstReply — reply first, win the booking
Description
Event venues lose bookings because they reply a day late. By then the client has booked somewhere else. FirstReply answers every inquiry with a priced proposal and a held date in seconds.
The automation
1. An inquiry arrives from the venue page, or staff paste in an email.
2. AI extracts event type, date, guests, budget and requests, each with a confidence level and the exact words it came from.
3. Missing date or guest count? It writes a clarifying reply instead.
4. It matches the smallest free space that fits (or the two nearest free dates when it's booked), prices the right package and holds the date for 5 days.
5. The client gets their own proposal page and books with one tap. The hold becomes a confirmed booking.
6. Unsure details, over-budget totals or Review mode send it to a review queue first. Humans step in only when needed.
7. Views, acceptances and expiring holds update the pipeline and alert the team live. Every step is logged to the second.
The design A full design system first (tokens, type scale, components), built as a clickable prototype, then rebuilt in Base44 from prompts. Client pages are mobile-first; the venue side is desktop-first.
Try it Client side: firstreply.base44.app · Venue side: firstreply.base44.app/dashboard
🚀 ST Automation Cloud - Enterprise AI Automation SaaS
What it does:
ST Automation Cloud is a next-generation platform that connects your daily business tools (Gmail, Google Sheets, Slack, Discord, Webhooks) into one unified workspace. Powered by Gemini AI, it allows users to build visual, multi-step automation workflows without writing a single line of code. It handles everything from data syncing to executing complex, autonomous AI pipelines.
How it is profitable (Business Value):
Massive Time & Cost Savings: By automating repetitive tasks (like lead generation, email sorting, and data entry), it saves hundreds of man-hours, directly reducing operational costs.
Zero Human Error: Automated workflows ensure 100% accuracy in data transfer between different apps, eliminating costly manual mistakes.
Infinite Scalability: Businesses can scale their operations 10x without needing to hire more staff. The autonomous AI agents work 24/7 in the background.
High-Throughput ROI: With enterprise-grade security and a premium user interface, it provides a quick return on investment by streamlining critical pipelines.
In short: It transforms manual, time-consuming operations into a fast, reliable, and fully automated digital workforce.
I'd distinguish a completed action from a completed workflow in the run history. If Gmail sends successfully but the next Slack step fails, can a user resume from Slack without sending the email again?