What is Cyntex?

Cyntex is the next-generation rebuild of TapData — a data integration platform designed for the Agentic AI era.

It does three things:

1. Capture — Continuously sync data changes from any source system (CDC / full snapshot / API pull)
2. Model — Join, merge, filter, and transform data streams to build unified business views
3. Serve — Publish processed data as APIs, event streams, or materialized views

Core Differentiators

YAML-first, AI-native

The task description language (DSL) is YAML, with file extension .cyn.yml. No SQL→DAG frontend, no drag-and-drop canvas — all data pipelines are declared in YAML, authored by an AI agent or human engineer.

my-pipeline.cyn.yml

apiVersion: cyntex/v1
kind: pipeline
id: user-profile-sync

source: mysql-prod

transforms:
  - name: enrich
    filter: "record.status == 'active'"

sync:
  - source: users
    target:
      collection: user_profiles

A single JSON Schema drives everything from the same source: authoring completion / validation errors / e2e tests / MCP tool generation — invest once, benefit everywhere.

BYO-agent, model-agnostic

Cyntex does not bundle any LLM. You bring your own AI agent (Claude, GPT-4o, Gemini, …) and integrate via three layers:

Layer	Form	Capability
Skill	Offline, imported into agent	Understands DSL syntax, generates .cyn.yml
MCP server	In-process, HTTP transport	Real-time CRUD + lifecycle control
CLI	Standalone native binary	Validate / scaffold / offline REPL

AI can: create/edit/delete connections and tasks, start/stop tasks, query run status, lag, and errors. AI cannot: auto-fix (human in the loop).

Open Core

The core is fully open source (Apache 2.0). Closed-source components are limited to enterprise-grade plugins (RBAC / LDAP / enterprise connectors), plugged in via SPI interface — no license gating.

Use Cases

Scenario	Example
FDM → MDM master data sync	MySQL / PostgreSQL → MongoDB unified customer view
Multi-source CDC real-time streaming	Multiple databases → Hazelcast in-memory → downstream consumers
Data publishing API	Synced data published directly as a REST API (GA phase)
AI-driven data pipeline	Conversation → YAML → one-click deploy

What Cyntex Does Not Do

• Not an ETL batch processing tool (does not replace Spark / Flink batch jobs)
• Not a data warehouse (does not store historical analytics data; Paimon incremental data lake is an external add-on at the end of GA)
• Does not include AI models (BYO-agent; model costs are on the user’s side)
• No multi-tenant isolation (not in v1; added with enterprise RBAC after GA)

Current Status

Cyntex is in the POC phase, implementing the first sub-slice (full DSL grammar module + offline CLI native binary). See the Roadmap for details.