Woven is building AI Agents for Data & Analytics Engineers. We're expanding beyond the Application Engineering interface to the Stakeholder interface.
Interested to building together?
Talk to Woven's founders
.
Book a demo
Change Agents
AI Data Engineer teammates that continuously absorb change from application code and business usage.
Change Agents
Trigger workflows based on Application schema signals
Handles continuous product-driven schema change by resolving semantic meaning at the source and preparing review-ready downstream data engineering work.
Trigger workflows based on Analytics usage signals
Watches how the business is actually using data and prepares review-ready analytics model evolutions that amplify decision-making value.
What They do
Understands change & intent
Interprets semantics, ownership, risk, and usage in a business context.
Works with the right people, at the right time
Asks pointed questions in-flow when confidence is low or impact is high.
Acts through explicit policies and reviewable artifacts
Does real data engineering work by producing reviewable artifacts according to instruction.
get started
Schema Insights Pilot
Get application schema change summaries on PR commit, showing you prepared insights without executing any downstream work.
Usage Insights Pilot
Get a prioritized Slack digest of high-leverage data engineering opportunities, derived from Snowflake usage.
Platform
The trust and execution layer that lets the Data Engineering Agent operate inside real engineering workflows.
Signal Capture
Application Change Detection
Parse application schema changes directly from PR code diffs in GitHub/CI for real-time awareness.
Supports: Python, Rails, Go, JS, Protobuf, and more
Semantic Usage Shift Detection
Detect sustained changes in semantic expectations by analyzing downstream query intent over time.
Context Gathering
Domain & Ownership Context
Load business-domain context – product, customer, metrics, and related models – so changes are evaluated with the right priorities.
Impact & Risk Analysis
Assess schema changes based on downstream usage, dependencies, and sensitivity to determine impact level.
Schema Change System of Record
Query an auditable history of how schemas evolve over time, linked to PRs and owners.
Coordination & Delivery
PR-Native Collaboration
Deploy an embedded UX directly in a pull request to clarify intent, confirm requirements, and resolve ambiguity before merge.
Async Escalation & Reviews (Slack)
Post contextual questions, summaries, and alerts for async coordination beyond a single PR.
Execution & Artifact Sync
Generate reviewable artifacts and apply approved updates through connected data stack tools.
Controls & Guardrails
Pre-Merge Controls
Proactively enforce privacy, security, and reliability requirements before changes are merged.
Post-Merge Controls
Automatically keep access controls, PII masking, and retention policies code-synced after changes land.
Approvals & Audit Trail
Require explicit sign-off and maintain a traceable record of decisions and actions.
Solutions
Practical ways teams use Woven to solve real data engineering problems.
By Team
For Data Engineering
Eliminate firefighting and manual toil by catching upstream data changes early and automating the AppEng ↔ DataEng handoff.
For Data Platform
Keep dbt sources, models, and documentation aligned as upstream schemas evolve.
For Analytics Engineering
Improve data reliability, accountability, and cross-team coordination — without adding process overhead.
For Application Engineering
Improve data reliability, accountability, and cross-team coordination — without adding process overhead.
For Data Leadership
Understand data impact in PRs, meet requirements early, and collaborate without slowing delivery.
For Data Privacy & Security
Catch compliance risks at the source by empowering engineers to find, fix, and prevent data issues before any code ships.
By Use Case
Prevent Downstream Breakages
Catch upstream schema changes before merge to prevent breaking pipelines, dashboards, or ML.
Shift-Left Governance (Privacy & Security)
Ensure ownership, documentation, and compliance requirements are met in PRs.
Schema Change Workflow Automation
Reduce coordination overhead by automating the AppEng ↔ DataEng handoff around data changes.
Root Cause Analysis (RCA)
Trace incidents directly back to the exact code change, PR, and owner that introduced them.
...
Schema Change Auditing & Accountability
Maintain an auditable system of record for who changed what, when, and why—across teams.
Continuous Data Hygiene
Identify zombie models, risky fields, ownership gaps, and cleanup opportunities.
dbt Modeling Assistance
Prepare review-ready dbt entity and metrics PRs from stakeholder requests.
AI Analytics Enablement
Generate governed semantic models for reliable AI-driven analysis.
customer story
How Dropbox Sign transformed collaboration with Webflow
67%
Decrease in dev ticketing
Customer stories
Browse Woven
.dev
success stories
Docs
Pricing
Book a demo
Sign in
Get started
© 2026 Woven Technologies, Inc. All rights reserved.
Terms of use
|
Privacy policy
