Solution Plays

A solution play is a complete, deployable AI solution — the unit of work in FrootAI. Each play bundles primitives, infrastructure, evaluation pipelines, and configuration into a self-contained package wired through the FAI Protocol.

What’s in a Play?

Every play ships with four toolkits plus a protocol manifest:

Toolkit	Folder	Contents
DevKit	`.github/`	Agents, instructions, prompts, skills, hooks — the 7 primitives
TuneKit	`config/`	Model parameters, evaluation thresholds, guardrail configs
SpecKit	`spec/`	ADRs, architecture diagrams, implementation notes
Infrastructure	`infra/`	Bicep templates for Azure resources
FAI Manifest	`fai-manifest.json`	Protocol wiring — connects everything above

DevKit gives the AI coding agent context. TuneKit controls quality gates. SpecKit captures design decisions. The manifest binds them all.


solution-plays/01-enterprise-rag/
├── .github/                    # DevKit
│   ├── copilot-instructions.md
│   ├── agents/                 # builder, reviewer, tuner
│   ├── instructions/           # coding standards
│   ├── skills/                 # step-by-step procedures
│   └── hooks/                  # security guardrails
├── config/                     # TuneKit
│   ├── openai.json
│   └── guardrails.json
├── spec/                       # SpecKit
├── infra/                      # Azure Bicep
│   ├── main.bicep
│   └── parameters.json
├── evaluation/                 # Quality pipeline
│   └── test-set.jsonl
└── fai-manifest.json           # FAI Protocol

Play Categories

🔍 RAG & Search

#	Play	What It Deploys
01	Enterprise RAG Q&A	AI Search + OpenAI + Container App
09	AI Search Portal	Enterprise search with facets
21	Agentic RAG	Autonomous retrieval + multi-source
26	Semantic Search	Vector + hybrid + reranking
28	Knowledge Graph RAG	Cosmos DB Gremlin + entities

🤖 Agents & Multi-Agent

#	Play	What It Deploys
03	Deterministic Agent	Reliable agent with guardrails + eval
07	Multi-Agent Service	Orchestrated agent collaboration
22	Multi-Agent Swarm	Distributed teams + supervisor
23	Browser Automation	Playwright MCP + vision
42	Computer Use Agent	Vision-based desktop automation

🏗️ Infrastructure & Platform

#	Play	What It Deploys
02	AI Landing Zone	VNet + Private Endpoints + RBAC + GPU
11	AI Landing Zone Adv.	Multi-region + DR + compliance
12	Model Serving on AKS	GPU clusters + model endpoints
14	Cost-Optimized Gateway	Smart routing + token budgets
29	MCP Gateway	Proxy + rate limiting + discovery

🔒 Security & Compliance

#	Play	What It Deploys
10	Content Moderation	Safety filters + content classification
30	AI Security Hardening	OWASP LLM Top 10 + jailbreak defense
35	AI Compliance Engine	GDPR, HIPAA, SOC 2, EU AI Act
41	AI Red Teaming	Adversarial testing + safety scoring

🎙️ Voice & Speech

#	Play	What It Deploys
04	Call Center Voice AI	Real-time speech + sentiment analysis
33	Voice AI Agent	Speech-to-text + conversational AI

📄 Document Processing

#	Play	What It Deploys
06	Document Intelligence	PDF/image extraction pipeline
15	Multi-Modal Doc Proc	Images + tables + handwriting
38	Document Understanding v2	Multi-page PDF + entity linking

ℹ️

Browse all 100 plays at frootai.dev/solution-plays or use the Configurator to find the right play for your use case.

How to Choose a Play

By use case — What are you building? RAG chatbot → Play 01. Landing zone → Play 02.
By complexity — Plays range from Low (single service) to High (multi-region, multi-agent).
By Azure services — Filter by the services you already use or want to adopt.
By WAF pillar — Need security hardening? Filter by the security pillar.

Use the interactive Configurator for a guided recommendation.

Working with Plays

Scaffolding


# Initialize a play's DevKit
npx frootai init-devkit 01
 
# Validate all primitives
npm run validate:primitives

Deploying


# Preview Azure deployment
az deployment group what-if \
  --resource-group rg-frootai-01 \
  --template-file infra/main.bicep
 
# Deploy
az deployment group create \
  --resource-group rg-frootai-01 \
  --template-file infra/main.bicep \
  --parameters infra/parameters.json

Evaluating


# Load play and verify wiring
node engine/index.js fai-manifest.json --status
 
# Run quality gate evaluation
node engine/index.js fai-manifest.json --eval

Creating Your Own Play

See the cookbook recipe: Initialize a Solution Play or follow Your First Solution Play for a guided tutorial.

Next Steps

Your First Solution Play — build and deploy Play 01
FAI Protocol — how plays are wired via manifests
Primitives — the building blocks inside every play
How to Contribute — create and share your own play