Thoughts from an experienced AI engineering team since 2019

A beast with many heads: AI Agents, RAG, MCP, Workflow Automation.....

AI Agents, RAG, MCP, Workflow Automation, and Agent Swarms: What They Actually Mean and When You Need Them Bite-size insights ConceptWhat It IsBest ForThink of It As... Workflow AutomationPredefined steps that run the same way every timeRepeatable, predictable processes with no decision-makingSimiliar preprogrammed steps RAGAsk AI to look up a

AIAgent

Agent Swarm vs Anthropic Workflows vs LangGraph: Which Multi-Agent Architecture Should You Use?

The phrase "Agent swarm" is everywhere right now. But behind the hype, there are fundamentally different approaches. What does it mean? What do I do with it? How can I use it within my context to meet my needs? Here are some of our thoughts: What Is a

Fine-Tuning

How to Fine-Tune Kimi K2.5 on Your Local Machine — A Practical Guide

Fine-tuning a 1-trillion-parameter model on consumer GPUs? It's possible — here's how. What is Kimi K2.5? Released January 27, 2026 by Moonshot AI, Kimi K2.5 is the most powerful open-source multimodal model available. It's a 1-trillion-parameter Mixture-of-Experts (MoE) model — but thanks to its

Fine-Tuning

How to Fine-Tune DeepSeek OCR V2 on Your Own PDFs — From Install to Inference

A practical, step-by-step guide to running and fine-tuning DeepSeek's 3B-parameter document understanding model on your local machine. Why DeepSeek OCR V2? Released January 27, 2026, DeepSeek OCR 2 isn't your typical OCR tool. Traditional OCR scans documents left-to-right, top-to-bottom — like reading a book one pixel row

DocumentAI

Why DeepSeek-OCR 2 Could Change Document AI Forever

Yesterday, DeepSeek dropped a paper that might quietly reshape how machines read documents. It's called DeepSeek-OCR 2: Visual Causal Flow, and if you work anywhere near document processing, OCR, or enterprise AI — pay attention. The Problem Nobody Talks About Every vision-language model today reads images the same way:

AIAgent

The Three Layers of Useful AI: Agents, MCP, and SKILL.md

You've heard "AI agent" a hundred times this year. Here's what it actually means—and why the new developments matter for your business. The "AI Agent" Buzzword, Decoded Let's cut through the noise. An AI agent is simply an AI

SaaS Featured

SaaS at a Junction Point: What we learned building AI in 2025

2025 has been an eventful year for most businesses. Tariff hikes, market volatility, renewed bubble talk—and, inevitably, everything AI. This year, we worked across mortgage, retail, real estate, and marketing—but the common thread wasn’t the industry, it was the economics. We built workflow automation for marketing agencies

Making Serverless Inference on SageMaker for a multi-input HuggingFace model

Hola! It has been a while since we dove into technical posts. We have been very busy building several deep-learning projects in the mortgage and call center industries, ranging from analyzing bank statements to analyzing human voices. One of the recent projects called for making inferences with AWS SageMaker’s

Keras Data Generator for Images of Different Dimensions

When using CNN, we often have to provide the dimension of images ahead of time. Note that I used singular, not plural “Dimensions”. That’s because most of the time, it requires us to input tensors of the same dimension. However, we have a little bit of a problem here.

deep learning

Tensorflow Keras LSTM source code line-by-line explained

In this blog, I will go through line by line of Keras' LSTM source code to explain how the tensor computations work.

machine learning

What are inside sales emails? Using machine learning to understand them.

In this blog, we will talk about how to use two different machine learning techniques (LDA and Word2Vec) to analyze and query the topics in sales emails (or all emails). I will also share the code (<50 lines) for you to start querying your emails immediately. You don'

Applying Machine Learning in Sales Enablement and Sales Operations [Part 3]

In the previous blog, I talked about enhancing Sales Enablement with machine learning. In this blog, I will go into some examples of using machine learning to improve sales operations. Machine Learning in Sales Operations Sales operations, despite its name, has more focus on business intelligence and data analytics. Back

revenue opeartions

Applying Machine Learning in Sales Enablement and Sales Operations [Part 2]

In this post, let's talk about how Softmax Data leveraged machine learning to improve sales enablement for some of our clients.

revenue opeartions

Applying Machine Learning in Sales Enablement and Sales Operations [Part 1]

How Softmax Data applied learning in improving Sales Enablement and Sales Operations for some of our clients

CRM Cleaning: Merging Salesforce Objects using SOAP API (with a Python Focus)

We recently helped a client to clean up their Salesforce CRM. First, we made our proprietary solution to find all of the duplicate records that would pass the client’s criteria and then had to use Salesforce native merge functionality to remove the duplicates. By doing the deduplication process, we

database

Brutal-force Migration of Postgres from Azure to AWS (or vice versa)

In this short blog post, I want to show how to move the entire Postgres from one cloud server to another with brutal force.

machine learning

What is machine learning (ML)? How about AI? Why now?

“We are drowning in information and starving for knowledge.” — John Naisbitt. The Era of Big Data We have entered the era of big data. For example, there are about 60 trillion web pages; 300 hours of video are uploaded to YouTube every minute, amounting to 10 years of content every

machine learning Featured

Multi-input Seq2Seq generation with Keras and Talos

In this technical blog, I will talk about a common NLP problem: Seq2Seq, where we use one sequence to generate another sequence. Add to it, I also illustrate how to use Talos to automatically fine tune the hyperparameters, a daunting task for beginners.

machine learning

Words According to r/Vancouver [Part I], word2vec

Using word2vec to analyze the reddit comments on r/vancouver