Industries
Purpose-built AI systems for the industries we serve.
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AI-native search that understands natural language and delivers direct answers
Multi-tenant AI CRM with a per-industry module architecture — each new industry gets a tailored feature set on shared infrastructure
AI orchestration layer coordinating agent workflows across CRMs, email, and marketing tools
Business analytics platform for data-driven decisions
Practice management software with AI-powered patient communication
Autonomous AI agents for ecommerce buying journeys
Intelligent scheduling that handles complex availability
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The AI Search Playbook for Product Teams
Practical guide with implementation patterns, code examples, and real results
Who is this playbook for?
This playbook is designed for product managers planning AI search features and engineers implementing them. Whether you're adding search to a new product or replacing legacy keyword search, this guide provides the frameworks, code patterns, and lessons learned from 20+ real-world implementations.
We cover everything from initial scoping and user research to production deployment and monitoring. Each chapter includes practical exercises, code snippets in Python and JavaScript, and decision frameworks you can use immediately.
What's inside
Chapter 1: Scoping AI Search Projects
How to identify high-impact search use cases and build a business case for AI search investment.
Chapter 2: User Research for Search
Templates and methodologies for understanding how users search and what they expect from results.
Chapter 3: Architecture Patterns
From simple widget integration to complex multi-source enterprise deployments.
Chapter 4: Implementation Guide
Step-by-step code examples for Python, JavaScript, and REST API integrations.
Chapter 5: Testing & Quality
A/B testing frameworks and metrics for measuring search quality improvements.
What you get:
Frequently asked questions
No. This playbook is designed for product teams, not ML specialists. We explain concepts in practical terms and provide ready-to-use code that doesn't require deep ML knowledge.
Code examples are provided in Python and JavaScript, with REST API patterns that work with any language. We also include curl examples for quick testing.
While examples use Zunkiree APIs, the concepts, patterns, and frameworks apply to any AI search implementation. The playbook is designed to be practical regardless of your vendor choice.