Blog
AI Apps & Integration
Practical guides on LLM integration, AI chatbots, computer vision, and agents — how to ship AI features that work in production, not just demos.
8 articles
Custom AI Chatbot Development — 2026 Playbook
Off-the-shelf chatbots frustrate users. Custom ones solve real problems — when built correctly. Here's the playbook we use for production AI chatbot development, from RAG architecture to evaluation harnesses to human handoff.
Read · 9 min
Virtual Assistant Development in 2026 — A Practical Guide
Virtual assistants are moving from demos to production. Here's what separates the two — voice vs text architecture, multi-turn design, escalation logic, testing, and cost engineering.
Read · 8 min
LLM Integration Playbook for SaaS Teams
LLM integration isn't just "call the API." Here's the playbook we use for production SaaS integrations — from model selection to RAG to evals to cost engineering.
Read · 9 min
AI-Powered Predictive Analytics for Business
Predictive models are only as good as the questions you ask. Here's the framework we use for building AI-powered analytics that actually drive decisions — from data readiness to model deployment to drift monitoring.
Read · 8 min
Computer Vision in Production — The Testing Checklist
A CV model that hits 95% accuracy in the lab can drop to 60% in production. Here's the checklist we use to catch that before users do — lighting, edge devices, bias, latency, drift, and adversarial inputs.
Read · 7 min
AI Agents in Production — Why Most Fail (And How to Fix It)
AI agents work beautifully in demos. In production, they fail on the same five things — and every one is fixable. Here's how we build agents that survive real-world use.
Read · 9 min
Third-Party AI API Integration Guide
You don't need to train your own models. But you do need to integrate third-party AI APIs smartly — vendor selection, cost modeling, rate limits, fallbacks, and testing. Here's how.
Read · 7 min
AI Strategy & Roadmap for 2026
Most companies adopt AI backwards. Here's the right sequence — use case selection, vendor evaluation, build vs buy, ROI modeling, and a phased roadmap that de-risks execution.
Read · 8 minNotes from the lab.
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