Platform Overview¶

A guided tour of Synaptiq's key features and navigation.

Application Layout¶

Synaptiq's frontend is built as an Angular 21 shell with a responsive layout:

┌─────────────────────────────────────────────────────┐
│  🧠 Synaptiq          [Theme Toggle] [User Menu]    │  ← Header
├──────────┬──────────────────────────────────────────┤
│          │                                          │
│  Chat    │     Main Content Area                    │
│  History │                                          │
│          │  ┌──────────────────────────────────┐    │
│  ────────│  │  Chat Messages                   │    │
│          │  │  + Component DSL Rendering        │    │
│  Workflow│  │  + Interactive Components          │    │
│  List    │  │                                    │    │
│          │  └──────────────────────────────────┘    │
│          │                                          │
│          │  ┌──────────────────────────────────┐    │
│          │  │  💬 Message Input                  │    │
│          │  └──────────────────────────────────┘    │
└──────────┴──────────────────────────────────────────┘

Key Features¶

💬 Chat Interface¶

The chat interface is the primary interaction surface. Users type natural language queries, and Synaptiq responds with:

Text responses — natural language answers
Component DSL — rich, interactive UI components rendered inline
Suggestion chips — contextual follow-up actions
Streaming — responses appear in real-time via Server-Sent Events (SSE)

🔧 Workflow Designer¶

The workflow designer provides:

Visual flow editor — drag-and-drop node-based workflow builder
Natural language generation — describe a workflow in plain English, Synaptiq generates the flow
Templates — pre-built workflow patterns for common use cases
Execution history — view past runs with detailed step-by-step results

📚 Knowledge Base¶

The knowledge base enables RAG (Retrieval-Augmented Generation):

Document upload — ingest PDFs, text files, and CSVs
Automatic embedding — documents are chunked and vectorized
Contextual search — relevant passages are injected into chat responses
Source citations — responses reference specific document sections

⚙️ Administration¶

Tenant administrators can configure:

AI Persona — customize the AI's name, behavior, and guardrails
Branding — logos, color palettes, fonts, and theme presets
User Management — invite users, assign roles, manage permissions
Model Configuration — select LLM provider, model, temperature, and token limits

flowchart LR
    Login["🔑 Login"] --> Chat["💬 Chat"]
    Chat --> Workflows["🔧 Workflows"]
    Chat --> KB["📚 Knowledge Base"]
    Workflows --> Designer["Visual Designer"]
    Workflows --> Execute["Execute & Monitor"]
    KB --> Upload["Upload Documents"]
    KB --> Search["Vector Search"]
    Chat --> Admin["⚙️ Admin"]
    Admin --> Branding["Branding"]
    Admin --> Users["User Management"]
    Admin --> Config["AI Configuration"]

API Documentation¶

The backend exposes a full REST API documented with OpenAPI 3.0. Access the interactive API explorer at:

http://localhost:8080/swagger-ui.html

Key API groups:

API Group	Base Path	Description
Auth	`/api/v1/auth`	Login, signup, token refresh
Chat	`/api/v1/chat`	Sessions, messages (SSE streaming)
Workflows	`/api/v1/workflow`	CRUD, execute, generate, templates
Knowledge Base	`/api/v1/kb`	Document upload, search
Config	`/api/v1/config`	AI persona, branding, tenant settings
Admin	`/api/v1/roles`, `/api/v1/users`	RBAC, user management