Bigeye
Bigeye is a San Francisco-based enterprise data observability platform founded in 2019 by Kyle Kirwan and Egor Gryaznov, two former Uber engineers who identified critical gaps in how large organizations manage data quality and reliability.
Profile
Bigeye provides data observability and governance software that helps enterprises monitor data quality, ensure AI safety, and enforce data access policies across their data stacks.
Bigeye is a San Francisco-based enterprise data observability platform founded in 2019 by Kyle Kirwan and Egor Gryaznov, two former Uber engineers who identified critical gaps in how large organizations manage data quality and reliability. The company began as Toro Data Labs before rebranding to Bigeye in November 2020. Across a remote-first operation of approximately 65 employees, Bigeye has built a unified platform that combines data quality monitoring, sensitivity classification, data lineage, governance, and runtime policy enforcement.
As of December 2025, the company has generated $7.2 million in annual recurring revenue, up from $6.5 million in July 2025, and has raised $73.5 million across multiple funding rounds led by Sequoia Capital, Coatue, Costanoa Ventures, Alteryx, and In-Q-Tel, with a strategic $5 million investment from USAA in October 2024. Bigeye serves a customer base spanning financial services, technology, healthcare, and retail, with publicly disclosed clients including USAA, Zoom, Cisco, Freedom Mortgage, Blue Cross Blue Shield, Zimmer Biomet, Williams-Sonoma, Burberry, Canva, and Centene. In 2025, the company pivoted toward AI governance, hiring Mohamed Alimi as VP of Engineering in June 2025 (previously at Datadog leading LLM observability) and launching AI Guardian in December 2025—a runtime enforcement layer that controls how AI agents access enterprise data by evaluating requests against data quality, lineage, sensitivity, and policy signals. Bigeye was named a Representative Vendor in the 2026 Gartner Market Guide for Data Observability Tools and joined Snowflake's Open Semantic Interchange initiative in April 2026, positioning the company as a foundational layer for responsible AI deployment in enterprise environments.
Who buys this
- Large financial services firms managing regulatory compliance and data risk (e.g., USAA, Blue Cross Blue Shield, Freedom Mortgage)
- Technology companies with complex data pipelines and AI workloads (e.g., Zoom, Cisco, Mozilla, Canva)
- Healthcare and insurance organizations requiring sensitive data governance (e.g., Centene, Zimmer Biomet)
- Enterprise data teams deploying AI agents and requiring runtime control over data access
- Snowflake and cloud data warehouse users managing multi-source data quality
Publicly disclosed clients
- USAA
- Zoom
- Cisco
- Freedom Mortgage
- Blue Cross Blue Shield
- Zimmer Biomet
- Williams-Sonoma
- Burberry
- Canva
- Centene
Strengths and what to watch
Strengths
- Clear market timing: data quality cited as the top obstacle to AI success by 44% of enterprise leaders in 2025, up from 19% in 2024
- Assembled a credible leadership team with deep observability expertise (Mohamed Alimi from Datadog, founders from Uber data infrastructure)
- Strong customer concentration in regulated, data-intensive verticals (financial services, healthcare) that demand governance rigor
Watch for
- Unproven commercial viability of AI Guardian—launched in private preview December 2025, no public adoption metrics or revenue contribution disclosed
- Competitive intensity: established players like Datadog, Monte Carlo Data, and Great Expectations have entered data observability; Bigeye must differentiate beyond feature parity
- Revenue trajectory flatness: $7.2M ARR with 65 employees suggests modest land-and-expand economics; growth rate and net retention not publicly disclosed
Recent moves
- 5mo ago Bigeye Joins Snowflake-Led Open Semantic Interchange to Power Data and AI Interoperability
- 9mo ago Bigeye Announces AI Guardian to Give Enterprises Control Over Agent Data Access
- 11mo ago Bigeye Expands Data Quality with Advanced Enterprise-Ready Features
- 1y ago Bigeye Named as a Representative Vendor in Gartner® Market Guide for Data Observability Tools
- 1y ago Bigeye Appoints Mohamed K. Alimi as Vice President of Engineering to Lead AI Trust Platform Development
Key Information
- Industry
- Data Quality & Observability
- Founded
- 2019
- Headquarters
- San Francisco
Frequently Asked Questions
What is Bigeye?
Bigeye is a San Francisco-based enterprise data observability platform founded in 2019 by Uber data engineers Kyle Kirwan and Egor Gryaznov. It provides unified software for monitoring data quality, enforcing governance, classifying sensitive data, and ensuring AI safety across enterprise data stacks.
What does Bigeye do?
Bigeye monitors data quality across enterprise systems, identifies data issues in real-time, enforces access policies, classifies sensitive information, traces data lineage, and controls AI agent data access through its AI Guardian runtime enforcement layer. It supports financial services, healthcare, technology, and retail organizations.
Which companies use Bigeye?
Bigeye serves Fortune 500 and scale-up customers across regulated industries. Notable clients include USAA, Zoom, Cisco, Blue Cross Blue Shield, Freedom Mortgage, Zimmer Biomet, Canva, Williams-Sonoma, Burberry, and Centene. These organizations use Bigeye to ensure data quality and enforce governance policies.
What is Bigeye AI Guardian?
AI Guardian is Bigeye's runtime enforcement layer launched in December 2025. It controls how AI agents access enterprise data by evaluating requests against data quality, lineage, sensitivity, and policy signals. It enables responsible AI deployment by preventing unauthorized data access in real-time.
Does Bigeye help with data quality monitoring?
Yes, Bigeye's core function is real-time data quality monitoring across enterprise data stacks. It detects quality issues automatically, classifies sensitive data, traces lineage, and enforces access policies. Most enterprise leaders cite data quality as their top obstacle to AI success.
Who founded Bigeye?
Bigeye was founded in 2019 by Kyle Kirwan and Egor Gryaznov, both former Uber data infrastructure engineers who identified critical gaps in enterprise data management. The company rebranded from Toro Data Labs in November 2020 and is backed by $73.5 million in funding.
How Bigeye compares
Direct head-to-head against 3 competitors. Picked by 7wData.
Bigeye
- Positioning
- Bigeye provides data observability and governance software that helps enterprises monitor data quality, ensure AI safety, and enforce data access policies across their data stacks.
- Customer segments
- Large financial services firms managing regulatory compliance and data risk (e.g., USAA, Blue Cross Blue Shield, Freedom Mortgage)
- Strengths
- Clear market timing: data quality cited as the top obstacle to AI success by 44% of enterprise leaders in 2025, up from 19% in 2024
- Watch for
- Unproven commercial viability of AI Guardian—launched in private preview December 2025, no public adoption metrics or revenue contribution disclosed
- Recent moves
- Bigeye Joins Snowflake-Led Open Semantic Interchange to Power Data and AI Interoperability
Monte Carlo
- Positioning
- Enterprise data and AI observability platform. Monitors pipeline health, model inputs, and agent outputs in production.
- Customer segments
- Enterprise data and ML engineering teams at large organizations running complex multi-source pipelines and production AI workloads.
- Strengths
- Automated anomaly detection without manual threshold configuration, covering tables, pipelines, and BI assets end to end.
- Watch for
- Out-of-the-box monitors generate alert noise in high-volume environments. Customers report tuning requires significant engineering time.
- Recent moves
- Launched Agent Observability in September 2025, extending coverage to AI agent inputs, outputs, and reasoning traces.
Soda
- Positioning
- Code-first data quality platform with data contracts and open-source checks. Targets engineering-led organizations managing dbt pipelines.
- Customer segments
- Data engineering teams at mid-to-enterprise organizations that version-control quality logic alongside dbt and Airflow pipeline code.
- Strengths
- SodaCL contract language lets teams define, version, and enforce data quality rules directly in pipeline code repositories.
- Watch for
- Cloud-first enterprise pivot has left Soda Core open-source users reporting slower feature parity and unclear roadmap commitment.
- Recent moves
- Acquired NannyML, a Belgium-based AI model performance monitoring company, in June 2025.
Datafold
- Positioning
- Data reliability and migration automation platform. AI agents translate legacy SQL and validate data parity before deployment.
- Customer segments
- Data engineering teams migrating legacy warehouses to Snowflake, BigQuery, or Databricks, or requiring CI/CD data quality gates.
- Strengths
- Column-level data diffing catches breaking changes between pipeline versions before they reach production.
- Watch for
- Pivot toward migration automation narrows pure observability use case. 35-person team may constrain enterprise post-sales support depth.
- Recent moves
- Raised $4M Series A extension in May 2025, backed by NEA. Total funding $26.1M.
Sources
- www.bigeye.com — Product positioning, customer list (Freedom Mortgage, Bank of Ireland, Blue Cross Blue Shield, Cisco, Zoom, Mozilla, Centene, Zimmer Biomet, USAA, Williams-Sonoma, Burberry, Canva, Hertz, NOV, Magellan Health)
- www.bigeye.com — Founding story (Kyle Kirwan and Egor Gryaznov met at Uber), company mission, customer testimonials, 45+ employees milestone, $66M total investment, 50M+ data checks executed
- getlatka.com — Revenue $7.2M ARR as of December 2025 (up from $6.5M in July 2025), employee count 65 people as of 2026, growth trajectory
- techcrunch.com — Series B funding of $45M in September 2021 led by Coatue, with participation from Sequoia Capital and Costanoa Ventures
- www.bigeye.com — AI Guardian product details, December 2025 launch, runtime enforcement capabilities, private preview status
- www.einpresswire.com — Mohamed Alimi appointment as VP of Engineering in June 2025, prior role at Datadog leading LLM Observability product
- www.einpresswire.com — USAA $5 million strategic investment in October 2024, bringing total funding to $73.5 million, investor list (Sequoia Capital, Costanoa Ventures, Coatue, Alteryx, In-Q-Tel, USAA)
- www.linkedin.com — Headquarters: San Francisco, CA; Founded: 2019; Employee count: 65 employees; Industry classification: Software Development