👋Welcome to Woven.dev

Woven.dev monitors your application code for upcoming schema and model changes, so your team always knows what’s going to change and why — before it breaks dashboards, pipelines, or compliance guarantees.

Your next data outage is already in a pull request — Woven catches it first.

Why It Matters

Data breaks silently — new fields, renamed columns, or missing tags can cascade into hours of debugging or compliance risk. Woven brings visibility upstream, where changes start.

  • 🔍 Shift-left visibility — see schema diffs before they’re merged

  • 💬 Collaborative alerts — Slack threads bring engineers, data, and compliance teams together

  • ⚙️ Actionable context — every alert links to impacted models, PRs, teams, and pipelines

  • 🧩 Extendable — optional automation hooks handle post-merge updates and pre-merge policy checks

Unexpected schema and data changes are the leading cause for Data teams spending so much time firefighting — Woven.dev is here to change that and bring back trust to your data.


What can Woven do?

Woven’s foundation is Observability, powered by GitHub + Slack. You can extend it with metadata automation and governance workflows — built around how your teams actually work.

🟢 Core Superpower: Observability

Goal: Know what’s about to change, when, and why — instantly sent to your Slack channel.

Feature
Description
Example

Schema Change Detection

Watches every PR for schema changes

orders.amount renamed to order_total in PR #42”

Slack Alerts

Sends context-rich messages to relevant channels

“Column added in users — possible PII:email

Lineage Awareness

Highlights affected models or dashboards

“This change impacts 3 downstream dbt models”

Integrations required:


🟣 Extension 1: Post-Merge Automations

Goal: Eliminate manual updates after schema changes land — using metadata and ownership context.

Feature
Description
Example

Snowflake on autopilot

Syncs metadata, tags, data masking, permissions to Snowflake

“New table detected -> horizon catalog + cortex AI refreshed and data masking updated”

Replication Automation

Auto-updates replication configs (e.g. Fivetran,)

“New column detected → Fivetran configuration updated”

dbt Model Sync

Updates dbt models, source layers, semantic models, and tags

“New column → dbt source + schema.yml refreshed”

Additional Integrations required:


🔒 Extension 2: Pre-Merge Controls

Goal: Capture metadata and ownership at the source — before a change merges.

When a developer opens a pull request, Woven intelligently interrupts the flow (in-PR comment or check) to collect:

  • Ownership — who’s responsible for this model or table

  • Metadata — purposes, data categories, sensitivity tags, retention, etc.

This keeps your catalog accurate without separate onboarding steps. Data models can also be onboarded organically, by service, repo, or team — no need for a big-bang migration.

Feature
Description
Example

Compliance Checks

Flags missing or incorrect data classifications

“Blocked: new table missing business purpose”

Privacy Enforcement

Ensures all fields are tagged and masked properly for GDPR

user_ssn requires PII classification and TTL before merge”

Policy Gates

Integrates with CI (GitHub Actions) for merge blocking

“PR #84 failed — privacy policy check”

Trust & Security

Woven is built with security and transparency at its core. We never access your raw data — only metadata. Your code will be accessed by Woven within your CI runners and only sends metadata over to Woven servers.

➡️ Learn more about our compliance, data handling, and SOC 2 controls at trust.woven.dev.


Next Steps

Ready to see Woven in action? Start with Observability — install the GitHub App, connect Slack, and get your first schema alert in minutes.

👉 Get Started with Observability →

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