Blog Insights

The Roadblock to Generative AI Implementation Generative AI (GenAI) holds immense promise for manufacturers seeking to automate complex processes like custom quoting. Our client, an Iowa based Injection Molder (manufacturing process for producing parts by injecting molten material into a mold), was eager to implement GenAI to enhance their quoting speed...

Highlighting how Source Allies employees have used their talents to give back to the broader community.

How an iterative migration system unlocked our team to deliver a NoSQL to SQL migration.

Tired of chasing missing time entries? We built a Slack bot that automates weekly time checks, nudges teammates, and flags anomalies, making time tracking effortless.

Most software decisions can be undone in a sprint, yet teams debate them for months. Learn how to spot two-way doors, run quick experiments, and stop treating every decision like it's permanent.

In my last post, I talked about a change to our call pattern that allowed us to save a significant amount of money for our client, but I kind of hand-waved over the optimization work that allowed us to reduce our server cluster from >400 servers to ~10.

Most software projects are pretty simple. We take something off the shelf, or a couple off the shelf components, and do a little bit of customization for a client's specific needs. This both saves time and is generally the way to do right by the client.

In this post we combine the learnings of two previous Technically Speaking videos in order to build an AI driven analytics chatbot

We dive into the world of requirements management and how we've combined ALM tools like Codebeamer with AI to streamline this critical process

We walk through building out a simple Lambda in Typescript that is able to pull cost and usage data, build an HTML report, and email it once a day