From Questions to Checkout
Research, write, and analyze
It does the research, writes the draft, formats everything. You just decide what's good.
Literature Review
Synthesize research across papers and articles. Extract citations in APA, MLA, Harvard or Chicago format.
Recent advances in artificial intelligence have raised important questions about alignment and safety (Russell, 2019; Amodei et al., 2016). As AI systems become more capable and autonomous, ensuring they remain aligned with human values becomes increasingly critical.
Multiple approaches have been proposed, including value learning, transparency, and robustness measures (Christiano et al., 2017; Olah et al., 2018). These methods aim to create AI systems that are not only powerful but also interpretable and controllable.
Try it now
Start with research or drafting—no setup required
Agentic Commerce Infrastructure
List your products on HugoGen. AI agents everywhere can sell it for you.
How it works: MCP-native integration
Expose your products through MCP protocol — AI agents discover and transact autonomously
Product Catalog
Connect your inventory — we standardize it for AI consumption
// Your products become AI-readable
{
"id": "prod_123",
"name": "Product",
"price": { "amount": 29.99 }
}MCP Server
HugoGen exposes your catalog via Model Context Protocol
Autonomous Commerce
AI agents discover, compare, and execute orders.
Ordering with AI
Say what you want to eat. It handles the rest.
Example conversation
Order me a pizza to my home address 1, double cheese no crust, large
Pizza Hut near San Francisco
Large Double Cheese Pizza (No Crust)
Here you go! Please make payment, due in 5 minutes.
Developer experience
From complex API integrations to one simple config
Build custom integrations for every store
# Custom API client for each restaurantclass RestaurantAPI: def __init__(self, api_key, base_url): self.api_key = api_key self.base_url = base_url self.session = requests.Session() def search_menu(self, query): # Handle auth headers = { 'Authorization': f'Bearer {self.api_key}', 'Content-Type': 'application/json' } # Handle pagination results = [] page = 1 while True: response = self.session.get( f'{self.base_url}/menu/search', params={'q': query, 'page': page}, headers=headers ) if response.status_code != 200: raise APIError(response.text) data = response.json() results.extend(data['items']) if not data['has_more']: break page += 1 return results def create_order(self, items, address): # Validate items # Calculate totals # Handle payment # Submit order # Handle webhooks # ...100+ more linesNatural language commands. Autonomous execution. Zero friction.
{ "mcpServers": { "hugogen": { "url": "https://api.hugogen.com/mcp", "transport": "http", "headers": { "X-HugoGen-Key": "hg_mcp_live_xxxxx" } } }}That's it
Every merchant. Every product. Every order.
Available instantly through conversation.
No APIs to build. No docs to read.
Connect to the infrastructure
One integration. Every AI agent. Autonomous distribution at scale.
Built for how you actually work
It remembers what you told it, does what you ask, and actually buys stuff for you.
Multi-agent orchestration
Chain specialized agents for research, writing, and analysis. Each agent handles a specific task—literature review, citation extraction, data analysis—then passes results to the next.
Cortex memory
Hierarchical memory system inspired by brain architecture. Implements working memory buffers, semantic knowledge graphs, and episodic trace consolidation with attention-weighted retrieval mechanisms.
Autonomous transactions
Order food, book travel, or purchase products through natural language. AI handles search, selection, and checkout—you just confirm the final order.
Open commerce protocol
Any business can integrate via standard REST APIs. Define your product schema, and AI agents automatically discover and transact with your inventory.
Hierarchical reasoning architecture
Three-layer neural architecture that processes information at different levels of abstraction—from low-level pattern recognition to high-level strategic planning.
Three-layer hierarchical processing
Foundational Reasoning
Core cognitive operations. Handles pattern recognition, semantic understanding, and direct input-output mappings for immediate tasks.
Integrative Processing
Cross-domain information synthesis models. Connects insights from research, data analysis, and context memory to form coherent responses.
Executive Reasoning
Strategic planning and high-level orchestration. Breaks complex queries into subtasks, delegates to specialized agents, and synthesizes results.
Hierarchical processing levels
Each layer operates autonomously
Information flows top-to-bottom