I built a comprehensive sales tracking spreadsheet for an engine oil business that automatically tracks daily sales, calculates profit per transaction and labels each sales. The client can instantly see their most profitable product, total revenue, total costs and net profit for any period without any manual calculations.

This is exactly the kind of clarity every small business owner needs — being able to see profit per transaction and top products at a glance without manual calculations is a game changer. Great work on the performance labelling too! 🙌

Multi-Agent AI & RAG Knowledge System for Real Estate

The challenge: Design a complete agentic AI architecture for a real-estate marketplace — one capable of serving buyers, sellers/brokers, and document-verification workflows through specialized AI agents, grounded in real data rather than free-floating LLM responses.

What we built: A full multi-agent system design comprising a fleet of specialized agents (a buyer-facing conversational concierge, a seller/broker AI co-pilot, a document/listing verification agent, and a pricing-valuation agent), coordinated through a central model-routing and orchestration layer. The system is grounded by a Retrieval-Augmented Generation (RAG) pipeline spanning multiple structured knowledge bases (legal/regulatory corpus, market pricing data, locality/infrastructure data) plus a graph-based knowledge layer linking listings, agents, leads, and locations for relationship-aware retrieval — with human-in-the-loop approval gates on consequential actions.

The outcome: A complete, implementation-ready technical architecture covering agent orchestration, RAG pipeline design (vector + graph retrieval), model-routing strategy, and safety guardrails — the kind of specification an engineering team can build directly from.

What are you using for a harness