Inheriq reimagines how businesses interact with AI. Instead of bolting on generic chatbots, companies can hire specialized AI Employees that understand their role, context, and workflows—across HR, Sales, Finance, Marketing, Operations, and Customer Support.
System Architecture Diagram
Inheriq is an AI Workforce Operating System that enables businesses to hire, manage, and collaborate with specialized AI teammates across every department.
Businesses today use disconnected AI chatbots that lack context, memory, and specialization. There's no unified system for managing AI workers across departments like HR, Finance, Sales, and Operations.
Researched enterprise AI adoption patterns, existing AI assistant platforms, and the emerging 'AI employee' paradigm. Studied how companies like Anthropic, OpenAI, and Salesforce approach AI agent frameworks.
Built on Next.js with TypeScript for type-safe frontend, Supabase for real-time database and auth, and a multi-model AI backend leveraging both OpenAI and Claude APIs for specialized task routing.
Chose Supabase over Firebase for better PostgreSQL support and Row Level Security. Used a multi-model approach (OpenAI + Claude) to leverage each model's strengths for different department tasks.
Prioritized rapid iteration over perfect architecture. Chose monorepo for speed but designed modular boundaries for future microservice extraction.
Managing context windows across long conversations, implementing reliable AI task handoffs between department agents, and building a permissions system for AI employees.
AI products need exceptional error handling—users have zero tolerance for hallucinations in business contexts. Streaming responses dramatically improve perceived performance.
Multi-tenant enterprise deployment, custom AI employee training, integration marketplace, and advanced analytics dashboard for AI employee performance metrics.