SYNQ provides a data observability platform focused on ensuring the reliability of business-critical data products. The platform integrates testing, anomaly monitoring, and ownership activation to proactively identify data quality issues. It utilizes an AI agent, Scout, to triage alerts, recommend tests, and generate code suggestions for immediate issue resolution within the transformation layer.
Funding
$3.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Data teams often struggle to maintain the reliability of their data pipelines, leading to inaccuracies and inconsistencies in business-critical data. Existing tools lack integration between error detection, incident management, and ownership activation, resulting in fragmented workflows and delayed issue resolution. This unreliability gap hinders the creation of trustworthy data products and analytics.
Solution
Synq provides a data observability platform that unifies error detection, incident management, and ownership activation to ensure the reliability of data products. The platform integrates dbt tests and anomaly monitors into a single testing strategy, empowering data owners to proactively manage their data. By providing end-to-end column-code lineage and root-cause analysis, Synq enables data teams to quickly triage and resolve issues across their data pipelines. Synq helps operationalize analytics data, turning it into reliable data products with measurable business impact.
Target Audience
Synq targets data teams, analytics engineers, and data-forward businesses that rely on reliable data for critical decision-making and the creation of data products.
Features
- Combines dbt tests, SQLMesh audits, and anomaly monitors for comprehensive error detection
- Automates incident management workflows, from alerting to resolution
- Maps data ownership to relevant stakeholders for faster issue resolution
- Provides end-to-end column-code lineage for root-cause analysis
- Offers quality, cost, usage, and performance analytics for data products
- Integrates with existing data stack tools, including dbt Core & Cloud and SQLMesh
- Includes Scout, a data quality AI agent that debugs issues, recommends tests, and resolves problems directly in code