Building Intelligence Beyond import ai
A Project by Kirigen.co

IMPORTANT: This project is in its INITIAL DEVELOPMENT STAGE (Yes, that means exactly what you think it means - we're still catching edge cases)

• Currently a Minimum Viable Product (Think iterative improvement)
• Actively evolving and under construction
• Expect significant changes and iterations
• Not yet production-ready (Unless you enjoy debugging in production)
• Seeking early-stage collaborators and researchers

• Framework architecture being established
• Core providers being implemented
• Experimental and research-focused
• Rapid prototyping and conceptual validation

SentientOne is what happens when you let computer scientists dream too big. We're building the kind of framework that makes traditional AI look like a calculator watching a quantum computing lecture.

Building AI systems that can:

• Think independently (But we keep the docs handy)
• Learn from experience (Not just from training data)
• Adapt to change (Faster than your deployment scripts)
• Secure itself (No more default credentials)
• Evolve over time (Darwin would be proud)

While others build neural networks, we're building neural neighborhoods:

• Advanced Memory Systems: Beyond simple state management - our agents maintain dynamic memory hierarchies with short-term, long-term, and working memory integration
• Adaptive Learning Loops: Real-time skill acquisition that makes traditional learning look slow
• Context-Aware Processing: Because understanding the context requires more than just processing power
• Meta-Learning Framework: Systems that learn to learn, because if you're going to improve, you might as well do it properly

Distributed intelligence that would make distributed systems developers actually smile:

• Emergent Intelligence: Collective behavior patterns that emerge from individual agent interactions
• Dynamic Role Optimization: Agents that evolve their roles based on system needs
• Collaborative Problem Solving: Because sometimes the best solution requires more than one perspective
• Organizational Learning: Knowledge sharing that makes collaboration look easy

Production-ready features that won't keep your SRE team up at night:

• Scalable Architecture: From development to production without breaking a sweat
• Security By Design: Because "it works on my machine" isn't a security protocol
• Compliance Framework: Regulatory requirements built-in, not bolted-on
• Enterprise Integration: Plays nicely with your existing stack

Our framework is designed to revolutionize:

• 🏢 Enterprise Operations: Self-optimizing business processes
• 🔬 Scientific Research: Accelerated discovery and analysis
• 🎮 Interactive Systems: Dynamic, adaptive user experiences
• 🤖 Robotics: Sophisticated behavioral control
• 📊 Data Analysis: Intelligent pattern recognition
• 🎯 Decision Support: Context-aware recommendation systems

We're building what's next:

• Neural-Symbolic Integration: Combining traditional logic with modern learning. The best of both worlds, without the complexity of either.

• Distributed Cognition: True parallel intelligence. Multiple agents working together, sharing knowledge, and actually getting things done.

• Explainable Intelligence: Clear reasoning, transparent decisions. When your AI makes a choice, you'll know why.

• Agent Provider: Manages the complete lifecycle of intelligent agents. From creation to retirement, with all the complexity handled for you.

• Communication Provider: Structured information exchange between agents. Clear protocols, reliable delivery, no lost messages.

• Learning Provider: Real-time adaptation and improvement. Learning from experience, not just from training data.

• Memory Provider: Reliable, consistent information storage. What goes in is what comes out, exactly when you need it.

• Persona Provider: Contextual behavior management. The right personality for the right situation.

• Reasoning Provider: Practical problem-solving capabilities. From simple logic to complex decisions, always with clear reasoning.

• Security Provider: Comprehensive protection by default. Because security shouldn't be an afterthought.

• Services Provider: Efficient resource discovery and management. The right service at the right time.

• Storage Provider: Dependable data persistence. Your information, exactly where and how you expect it.

• Tools Provider: Essential utilities for AI operations. Everything you need, nothing you don't.

• Workflow Provider: Intelligent process management. Complex flows made manageable.

• AI Researchers: Exploring cognitive architectures and multi-agent systems
• Software Engineers: Building intelligent applications with modular components
• Tech Startups: Developing AI-powered products and services
• Academic Projects: Studying adaptive intelligence and agent behaviors
• Hobbyists: Learning about AI systems through hands-on development

• Production-ready enterprise systems (yet)
• Mission-critical applications
• Real-time processing requirements
• Systems requiring formal AI safety guarantees

• Tier 0: Personal and Research Use (Free)

  • For when your AI needs more than a requirements.txt
  • Perfect for academic pursuits (and late-night debugging sessions)
  • Experiment without explaining the GPU costs to your professor

• Tier 1: Creator's License

  • For startups who've graduated from proof-of-concept
  • When your MVP needs more than just a prototype
  • Early-stage product development (bugs included as features)

Required when your project goes from development to production:

• Annual revenue exceeds $50,000
• Concurrent users surpass 50
• Total user base exceeds 1,000
• Significant computational resource usage

# Basic Agency Example (No edge cases were harmed in the making of this code)
from basic_agency import Agency, config

# Initialize with basic configuration (Easier than setting up a new project)
agency = Agency(config)

# Add departments (Like modules, but they actually work together)
agency.add_department("research")
agency.add_department("development")

# Start processing (No bottlenecks involved)
agency.start()

# Advanced Agency Example (No boilerplate required)
from advanced_agency import Agency, ExecutiveTeam, SRDepartment

# Initialize with advanced features (It's not rocket science, but close)
agency = Agency()
executive = ExecutiveTeam(agency)
sr_dept = SRDepartment(agency)

# Configure departments (Better than managing dependencies)
agency.add_department("engineering")
agency.add_department("operations")

# Start with full management (No manual intervention needed)
agency.start()
executive.start_monitoring()

• Getting Started Guide (More than just a quick start)
• Template Guides (Better than your code comments)
• API Reference (Comprehensive and up-to-date)
• Examples (Not just hello world)

• Discord Server (Where AI enthusiasts meet)
• Research Forum (Deep learning, deeper discussions)
• Blog (Better than reading the news)

• FAQ (Questions we get after troubleshooting)
• Troubleshooting (Have you tried restarting?)
• Stack Overflow Tag (Less cryptic than error messages)

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

We're actively seeking researchers, developers, and organizations who think outside the box:

• 🔬 Cognitive Computing Research (Beyond the basics)
• 🤖 Advanced AI Systems (No, not another chatbot)
• 🧮 Complex Adaptive Systems (More complex than a simple algorithm)
• 🔄 Machine Learning (But actually learning, not just optimizing)
• 🧠 Neural Architecture (Brain-inspired, not just brain-dead)

Join us in building something that makes future AI systems say "Wow, that's intelligent!"