LeadEngine AI
Status: Available for Acquisition
LeadEngine AI is an MVP with production infrastructure designed for AI-powered B2B lead generation, website analysis, and automated outreach workflows.
The platform combines business discovery, automated website auditing, AI-powered analysis, personalized outreach generation, SaaS authentication, usage limits, background processing, and billing infrastructure.
Technology Stack Backend FastAPI Python 3.11+ PostgreSQL SQLAlchemy Alembic Redis Celery Frontend Next.js TypeScript Tailwind CSS React Infrastructure Docker Docker Compose Nginx Prometheus Grafana Flower Core Capabilities B2B business discovery AI-powered website audits SEO analysis Performance analysis SSL and domain checks Conversion analysis AI-generated business insights Personalized cold email generation LinkedIn message generation Loom script generation PDF report generation Automated email delivery Follow-up email scheduling Multi-tenant user data isolation Usage and plan limits Stripe billing integration White-label branding foundation REST API Background task processing Lead Generation Workflow
The main workflow is implemented end-to-end:
User creates a campaign with targeting parameters. The system searches for businesses matching the selected criteria. Discovered leads are stored and scored. A website audit can be triggered for a lead. Multiple technical checkers analyze the website. AI analyzes the collected audit data. The system generates personalized outreach content. A PDF audit report can be generated. Outreach emails can be sent through the configured email provider. Follow-up sequences can be scheduled. Business Discovery
The platform supports multiple external data sources:
Google Places API SerpAPI Yelp Fusion API Mock provider fallback
The discovery layer uses provider fallbacks so the application can operate in demo/mock mode when external API credentials are unavailable.
Lead information may include:
Business name Website Phone Email Address City State Country Rating Review count Business category Source Website Audit Engine
Website audits are performed through multiple independent checkers.
Technical Checks SSL validity Domain information Website performance SEO metadata H1/title/meta analysis Sitemap and robots.txt Broken-link checks Conversion elements Contact forms Phone CTAs Chat/review elements
The checkers can run asynchronously as part of the audit workflow.
AI Layer
The AI layer currently supports:
OpenAI Anthropic
OpenAI is used as the primary provider, with Anthropic available as an alternative/fallback provider.
AI is used for:
Website audit analysis Identification of critical issues Business-impact analysis Recommended fixes Priority scoring Personalized email generation LinkedIn message generation Loom script generation
The code contains a provider abstraction layer, making it possible to add or replace providers without redesigning the entire application.
Current limitation: model names are configured in code rather than being fully runtime-configurable.
Background Processing
Background processing is implemented using:
Celery Redis Celery Beat
Separate task queues are used for workloads such as:
Website audits Email delivery Cleanup tasks Follow-up sequences Failed email retries
Tasks include retry mechanisms and scheduled execution.
SaaS / Authentication
The platform includes:
User registration Login/logout JWT authentication HttpOnly cookies Password hashing with bcrypt Password reset Email verification User-level data isolation Usage quotas Subscription plans Stripe billing integration
Current plans include:
Trial Starter Growth Agency
Current limitation: the application currently uses a single user role. A separate role-based access-control system is not implemented.
Infrastructure
A production Docker Compose configuration is included with services for:
PostgreSQL Redis FastAPI backend Next.js frontend Celery workers Celery Beat Flower Prometheus Grafana Nginx
Health checks and persistent volumes are configured.
The infrastructure provides a strong foundation for deployment, but additional operational hardening would be required for large-scale production use.
Testing & CI/CD
The current project does not contain a meaningful automated test suite.
Current state:
Automated unit tests: Not implemented Integration tests: Not implemented E2E tests: Not implemented CI/CD pipeline: Not active GitHub Actions: deployment template only
The application has been manually tested through the API and application interface.
Current Technical Limitations
The project is an MVP and has several areas that a buyer may want to develop further:
No meaningful automated test coverage No active CI/CD pipeline Basic scraping rather than sophisticated crawling No JavaScript browser rendering for scraping Limited request/concurrency management No automated database backup strategy No disaster-recovery system No horizontal scaling configuration No centralized log aggregation No advanced role/permission system AI model names are not fully runtime-configurable
These are primarily operational and scaling improvements, rather than a requirement to redesign the core architecture.
Documentation
The repository contains technical and project documentation covering areas such as:
Installation Deployment Architecture Features API configuration Security Privacy Terms of Service SLA Project setup Acquisition Includes
The acquisition includes:
Full source code Complete GitHub repository Backend Frontend Database schema Docker configuration Deployment configuration API configuration Documentation Architecture Intellectual property transfer Product demonstration
The codebase uses standard open-source frameworks and libraries.
Third-party API credentials and external service accounts are not included in the acquisition and would need to be configured by the buyer.
Current Product Position
LeadEngine AI should be considered a functionally developed MVP with production infrastructure, rather than a mature enterprise SaaS.
Its primary value for a technical buyer is the existing:
Software architecture Lead-generation workflow Website audit engine AI integration layer SaaS foundation Background-processing infrastructure Billing integration Docker deployment environment Documentation
A technical team can use the existing foundation to continue development, integrate the technology into an existing product, or develop it into a standalone SaaS.
Acquisition
LeadEngine AI is available for acquisition.
The transaction includes the complete software codebase and intellectual property.
Preferred transaction methods:
Escrow.com Wire transfer
Other arrangements can be discussed privately.
Contact
Email: midorimavpotoke@gmail.com
This repository is provided as a technical overview of LeadEngine AI for acquisition discussions. The project is presented transparently as an MVP with production infrastructure and known areas requiring further development.