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LangGraph vs CrewAI: A Production Engineering Comparison
01
AI Engineering8 min read
Architecture · May 28, 2026

LangGraph vs CrewAI: A Production Engineering Comparison

After deploying both frameworks across healthcare, fintech and audio-AI workloads, our honest engineering verdict where each excels, where each quietly fails, and how to pick the right multi-agent stack for production.

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Building RAG Systems That Actually Work in Production
02
AI Systems12 min read
Deep Dive · April 14, 2026

Building RAG Systems That Actually Work in Production

Most RAG tutorials stop at the demo. This is what really changes at production scale: chunking strategy, hybrid retrieval, embedding drift, latency budgets, and the observability stack you will need on day one.

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How We Built a Multi-Agent Diagnostic System for Healthcare
03
Case Study15 min read
Case Study · March 22, 2026

How We Built a Multi-Agent Diagnostic System for Healthcare

An engineering breakdown of our Vet AI Agent: orchestrator pattern, specialist agent design, RAG-grounded medical reasoning, safety guardrails, and the decisions we would revisit.

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Automating Property Management: From 200+ Manual Workflows to Zero
04
Case Study10 min read
Automation · February 10, 2026

Automating Property Management: From 200+ Manual Workflows to Zero

How we replaced an entire real-estate operations team manual playbook with event-driven N8N orchestration, structured data pipelines and AI-assisted document parsing.

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FastAPI Production Patterns We Use on Every Project
05
Backend Engineering9 min read
Engineering · January 18, 2026

FastAPI Production Patterns We Use on Every Project

Dependency injection, async background tasks, Celery plus Redis pipelines, structured logging, request tracing and the production patterns we have standardised across every Satyron backend system.

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Building Studio-Grade Voice Synthesis Infrastructure with PyTorch
06
AI / ML11 min read
AI / ML · December 5, 2025

Building Studio-Grade Voice Synthesis Infrastructure with PyTorch

Inside the architecture of our AI Voice Cloning Backend: HuBERT speech embeddings, RMVPE pitch extraction, FAISS-based timbre retrieval, and real-time GPU inference.

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