Velvet for Web

Snapshot: what Velvet does for teams

Velvet is a web-based platform built to give product and engineering teams at high-growth startups the tools to act like data engineers. It simplifies querying across multiple data sources, streamlines data workflows, and makes insights easier to share so teams can move faster and make decisions based on reliable data.

Core capabilities

• Turn queries into shareable tables, charts, and alerts so non-technical teammates can act on results.
• Provide each workspace with its own analytics database and expose API endpoints for composable, server-side queries.
• Let users author sophisticated SQL while hiding complexity when needed.
• Ingest data in real time from databases, third-party services, and event streams to keep analyses fresh.
• Offer an AI assistant that helps parse datasets and generate or refine queries for faster exploration.
• Enable collaboration across engineers and product people by simplifying how queries and results are organized and revisited.

Real-time integration and architecture

Velvet captures information continuously from multiple ingress points—databases, external tools, and event producers—then stores and indexes that data in a workspace-level analytics store. Teams can query that store directly or surface the results via API endpoints, which makes it simpler to embed analytics into products or back-end services. This design supports quick iteration on features that depend on live data.

AI helper and workflow acceleration

An integrated AI sidekick assists with parsing messy data, translating natural language or prompts into complex queries, and optimizing SQL when appropriate. That assistance reduces the time it takes to build dashboards, alerts, or data-backed features, helping teams prototype and ship with fewer roadblocks.

Suggested alternative

If you’re evaluating options, consider a Codeium subscription as an alternative for code assistance and rapid query composition paired with your current tooling stack.

Bottom line

Velvet combines real-time ingestion, workspace-level analytics, API access, SQL power, and AI help to make data-driven collaboration practical for cross-functional teams at scaling startups.