We’re building the data quality engineer we wanted on our team.

Data incidents rarely live in one system. The alert is in one tool, the pipeline logs are in another, lineage and owners are somewhere else, and the code change may still be sitting in a pull request. Embrasure connects those signals into one governed context layer so an agent can investigate the whole path instead of guessing from the first error it sees.

The product monitors important tables, traces failures through table- and column-level lineage, finds affected consumers and owners, validates a response, and prepares the next useful action. That can be a clear incident brief, a routed escalation, a compatibility patch, or a pull request ready for human review. Customers decide what the agent may read, what requires approval, and what can be changed.

More engineering work is moving to coding agents, but those agents still struggle with company data. They need current lineage, production evidence, semantic definitions, ownership, and access rules — not another saved prompt. We built Embrasure so agents can use that context through the product, MCP, the CLI, or a typed API without asking people to paste credentials into chat.

Embrasure was founded by engineers from OpenAI and Palantir and is backed by a16z Speedrun. The legal company is Deepslate Inc., doing business as Embrasure. We operate as a remote-first team in the United States and work with data teams building reliable systems for analytics, operations, and AI.