BigEye

Bigeye (legal entity Bigeye Data Labs Inc.) develops an enterprise-grade data observability platform that helps data teams establish trust in data used for analytics, reporting, and machine learning. The product combines data lineage, anomaly detection, data quality rules, data reconciliation, and incident management in a single system intended to provide visibility into data pipeline performance and quality. Rather than relying solely on hand-written rules, the platform uses dynamic metadata — continuous data profiling, lineage, and other monitoring techniques — to detect both known and previously unseen data problems automatically across pipelines.

The company positions its current offering as an "AI Trust Platform" built on its lineage-enabled observability technology, organized into modules: metadata management (cataloging, tags, owners, data domains), data lineage across modern and legacy stacks, data observability (anomaly detection and monitoring), data sensitivity (scanning and classifying PII, PHI, PCI in structured and unstructured environments), data governance (certification, stewardship, business glossary, semantic layer), and AI Guardian, which applies runtime enforcement of data access policies so AI applications only access approved data. An AI component branded bigAI provides suggested resolutions and preventions for detected issues. The company frames these capabilities against regulatory drivers such as the EU AI Act and ISO 42001.

Operationally, Bigeye is delivered both as a fully managed SaaS service and for on-premises/private cloud deployment. It instruments datasets and pipelines with data quality metrics, detects anomalies, and alerts data owners, integrating through APIs and pre-built connectors to database, ETL, and BI systems. Developer-facing tooling includes bigConfig, a CLI, a Python SDK, REST and lineage APIs, an MCP server, a browser extension, and Slack integration.

Founding story

Co-founders Kyle Kirwan and Egor Gryaznov met at Uber, where Gryaznov ran the company's first internal SQL bootcamp and Kirwan attended it; they bonded over exchanging progressively harder SQL challenges. The two worked together on the data pipelines behind Uber's in-house A/B testing tool, which reported standardized metrics across thousands of experiments, and encountered data quality as a growing problem on a platform with hundreds of petabytes and thousands of weekly data users. Their conclusions — that testing does not scale, that automation must preserve control and understandability, and that analysts and engineers should share the same tools — informed the product. They founded Bigeye in 2019.

Business model

Bigeye sells software to enterprise data and AI teams, offered as a fully managed SaaS service and also for on-premises or private cloud deployment. The platform is modular, allowing customers to select components (metadata management, lineage, observability, data sensitivity, governance, AI Guardian) according to their use cases.

The sources describe a commercial software product sold to enterprises via demos and sales engagement, delivered as managed SaaS or on-premises/private cloud; specific pricing or contract structures are not disclosed in the sources.

Traction

At the September 2021 Series B, Bigeye reported that customer usage had doubled in each of the previous four quarters and that headcount had tripled from 10 to 30 in six months, with customers including Instacart, Udacity, Mindstrong, Alpha Exploration (Clubhouse), and SignalFire. Company-published figures state 45+ employees, 500+ data engineering customers, 50 million+ data checks run, and $66 million in total investment. Customer testimonials on the site cite outcomes such as a 20-40% reduction in analytics errors, detection times cut from 3+ days to under 24 hours at Udacity, and a 60% reduction in time to merge.

Latest developments

Bigeye has repositioned around an enterprise AI Trust Platform layered on its data observability and lineage technology, adding modules for data sensitivity scanning, data governance, and AI Guardian runtime enforcement of data access policies for AI agents and applications. It announced the acquisition of Data Advantage Group, with expanded lineage capabilities described as forthcoming, and is promoting new detection of AI agent cost anomalies requiring no setup. Product documentation covers agent trust setup, AI platform connections, bigAI chat, and an MCP server.