Introduction

Amodal is a git-repo-centric cloud platform for agents. Your agent's configuration — connections, skills, knowledge, tools, stores, pages, automations, and evals — lives as files in your repository. Studio reads these files, deploys them to a hosted runtime, and gives your team the operational surface around the agent: sessions, costs, logs, source history, deployments, and evals.

How It Works

Your Repo
  ├── amodal.json          ← agent identity, provider config
  ├── connections/          ← API credentials + docs (or plugins)
  ├── skills/              ← Markdown reasoning frameworks
  ├── knowledge/           ← Domain knowledge documents
  ├── tools/               ← Custom HTTP/chain/function tools
  ├── automations/         ← Scheduled or trigger-based runs
  └── evals/               ← Test cases for agent quality
 
       ↓ deploy from Studio
 
Hosted Runtime
  ├── Context Compiler     ← builds optimized prompts
  ├── Token Allocator      ← manages context window budget
  ├── Security Layer       ← field scrubbing, output guards, action gates
  ├── Provider Adapter     ← Anthropic / OpenAI / Google Gemini
  └── Session Manager      ← durable scoped sessions

The Core Loop

Every agent runs the same fundamental cycle:

Explore → query connected systems, load knowledge, gather context
Plan    → reason about findings, decide next steps
Execute → call APIs, dispatch sub-agents, present results, learn

Simple questions skip planning. Complex questions get the full loop with multi-agent dispatch and skill activation. The runtime matches depth to the question automatically.

Key Capabilities

Capability	What It Does
Multi-provider	Anthropic Claude, OpenAI, Google Gemini — with failover
Git-native config	Everything is a file. Version, diff, review, and deploy your agent like code
20+ connection plugins	Slack, GitHub, Stripe, Datadog, Jira, PagerDuty, Salesforce, and more
Security infrastructure	Field scrubbing, output guards, action gates, scope checking, leak detection
Evaluation framework	LLM-judged evals, experiments, cost tracking, multi-model comparison
Studio deployments	Commit source changes, deploy them, promote production, and inspect history
React SDK	`@amodalai/react` components and chat widget for embedding
Operations UI	Session replay, activity logs, runtime logs, deploy state, and usage analytics

Next Steps

Quick Start — Build and deploy your first agent in Studio
Project Structure — What goes where in your repo
Embedding & Multi-tenancy — Put a deployed agent in your product