AI coding tools are everywhere โ but most teams are still experimenting in isolated demos. In this architect-level walkthrough, Keyhole Software Chief Architect Zach Gardner shows how we use tools like Claude Code in real, production delivery: with planning mode, constraints-first prompting, multi-agent workflows, and the governance required for enterprise environments.
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Deploying ML Models to Edge Devices with TensorFlow Lite and WebAssembly
Artificial intelligence is no longer limited to large data centers and high-powered servers. Today, more organizations are deploying ML models to edge devices such as smartphones, tablets, and IoT hardware. These devices work in environments where connectivity is not guaranteed and computing resources are restricted. By running models directly on edge hardware, businesses reduce latency, enable offline functionality, and improve …
CI/CD for Legacy .NET Framework Apps: How to Automate Deployment Pipelines
Outdated deployment practices can slow down even the best software teams. When youโre still manually moving files between servers, itโs easy for small mistakes to slip through and updates to take longer than they should. At Keyhole Software, weโve seen firsthand how this approach can hold back your projects. The solution is to automate deployment pipelines. It brings consistency, reliability, …
How to Migrate Legacy Applications to AWS or Azure (With Real Examples)
A familiar challenge for many businesses is knowing when itโs time to modernize. Legacy applications that once ran smoothly on in-house servers start to feel like a burden as competition increases and technology advances. At Keyhole Software, we help companies migrate legacy applications to AWS or Azure to stay ahead. We take what already works and move it to a …
LLMOps for Enterprises: Deploying Private Large Language Models at Scale
As organizations look to stay competitive in 2025, one area that canโt be ignored is LLMOps for enterprises. Large language models (LLMs) have become essential for automating tasks, improving productivity, and gaining insights from data. However, most conversations about LLMs focus on public cloud services or small-scale tools. For large enterprises, these solutions often fall short in security, scalability, and …

