
Stacksync
Stacksync · Coding · Marketing
Stacksync is a real-time, two-way data sync platform that keeps CRMs, ERPs, databases and data warehouses in step, with no-code workflows and AI agents that run on live records.

About Stacksync
What Is Stacksync
Stacksync is a no-code integration platform built around one promise: data written in one system shows up in the other before anyone notices a delay. It connects CRMs like Salesforce and HubSpot to databases like PostgreSQL, warehouses like BigQuery and Snowflake, and enterprise systems like NetSuite, then keeps records matched in both directions.
The problem it targets is familiar to anyone who has built a CRM database integration. Traditional sync tools run on schedules, break on schema changes and cost more to maintain than the feature they support. Stacksync drops that delay to milliseconds and puts the mapping, direction and permissions in a no-code console. Most teams arrive looking for a Salesforce Postgres sync they can stop babysitting by hand.
The company is Swiss, came through Y Combinator's W24 batch, and sells mostly to mid-market and enterprise teams. Pricing starts at $1,000 per month billed annually, which tells you where the product sits: this is infrastructure for companies with real integration workloads, not a weekend experiment.
Getting Started
- Create a workspace at app.stacksync.com and pick a region for processing.
- Connect both systems through OAuth or a service account, then choose the tables you want to sync.
- Review the field mappings Stacksync proposes, set read and write directions, and save the sync in a paused state.
- Run a test pass on a small table, check the logs, then switch the sync live.
Product Information
A quick look at Stacksync's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- RevOps teams
- Data platform engineers
- IT and security leads
- Operations staff at manufacturers and retailers
Tasks
- Syncing CRM records with a database
- Writing warehouse insights back to the CRM
- Automating order and inventory flows
- Reconciling records across systems
Scenarios
- Replacing a legacy connector
- Real-time lead routing
- Month-end reconciliation
Key features
Real-Time Two-Way Sync
Stacksync reads and writes to both sides of a connection, so a change in Salesforce reaches PostgreSQL in milliseconds and the reverse trip works the same way. You set the direction per object, which matters when one system is the system of record for some fields and a consumer for others. The sync engine handles deletes, updates and inserts as separate events rather than treating everything as a full refresh. It isn't an ETL alternative in the usual sense, because there's no nightly load to schedule.
Field Mapping and Schema Control
The platform proposes mappings between source and target fields, and you adjust them before anything runs. Field names can differ as long as the types line up. When a connected system changes its schema, Stacksync asks you to review the configuration instead of silently dropping fields, which is the failure mode that costs teams a week of cleanup.
No-Code Workflow Automation
Workflows run your own logic on top of synced data: transform a record, call an API, branch on a condition, queue a retry. Logic is versioned, and each run executes either synchronously or in the background. EDI documents and event queues use the same building blocks, so a supply chain flow doesn't need a second tool.
AI Genies on Live Data
Genies are cross-system agents that run documented processes against live operational data, such as multi-system reconciliation, exception triage, enrichment or case preparation. They run unattended in the background and log every step. Each run adds context to the process, which is how Stacksync gets closer to predictable execution instead of a fresh guess every time. That gap between AI agents for enterprise data and a chat window that can't touch a record is the whole point.
MCP and Agent Access
Stacksync runs an MCP server at mcp.stacksync.com, so you can add the workspace to Claude, ChatGPT, Cursor or Claude Code and sign in with OAuth instead of pasting an API key. From there an assistant can list connections, inspect tables, draft a sync and create workflows, all inside the permissions of the signed-in user.
Governance, Audit and Regional Processing
Every agent and every employee sees only the data you authorize, down to specific records and fields. Audit logs record each step, guardrails cap what an agent may do, and processing regions keep data inside a chosen geography. The Pro plan adds SOC 2 Type II, ISO 27001 and HIPAA coverage along with a management API and config as code.
Enterprise OS for Internal Apps
Enterprise OS is the third product in the platform. It gives teams a managed place to deploy internal apps with SSO, roles and audit inherited from your identity provider, plus versioned deploys and one-click rollback. The pitch is that it replaces the usual pile of Git, hosting, CI and auth services with one governed layer.
Pros and cons
Pros
- Millisecond propagation, which removes the batch window that makes CRM data feel stale.
- Direction and field control per object, so you can keep the CRM authoritative for some fields and the database for others.
- No-code setup for the common case, with an API and config as code when you need to manage syncs like infrastructure.
- Compliance coverage that satisfies enterprise security reviews: SOC 2 Type II, ISO 27001 and HIPAA on the Pro plan.
- MCP access means an AI assistant can build and inspect syncs without a separate integration project.
Cons
- Entry pricing at $1,000 per month billed annually puts it out of reach for small teams and solo builders.
- Record-based billing means cost climbs with volume, so a large dataset needs a usage estimate before you commit.
- The connector list is deep on CRM, ERP and warehouse systems but thinner for niche SaaS tools than general-purpose iPaaS rivals.
- Genies and Enterprise OS are newer than the sync engine, so teams that need mature agent tooling should test carefully before relying on them in production.
Frequently asked questions
It keeps records identical across two systems in both directions, in real time. The common setup pairs a CRM such as Salesforce or HubSpot with a database or warehouse such as PostgreSQL, BigQuery or Snowflake, so edits on either side show up on the other within milliseconds.
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