DQLabs
DQLabs offers PRIZM, an AI-native enterprise platform that unifies data observability, data quality, and enterprise context for banks, insurers, healthcare organizations, retailers, manufacturers, governments, and utilities, sold via subscription to Fortune 500 and mid-market data teams.
- Company typePrivate
- Founded2020
- HeadquartersPasadena, United States
- Headcount101–250
- GTM typeB2B
- OfferingSoftware
What DQLabs does
DQLabs is a private enterprise software company founded in 2020 and headquartered in Pasadena, California. The company develops PRIZM, an AI-native enterprise platform that unifies Data Observability, Data Quality, and Enterprise Context into a single continuously validated control plane. The platform is built on a multi-agent architecture with specialized Discovery, Quality, Catalog, Governance, Observability, and Remediation agents, and it operates on metadata only so that customer data is never extracted. Differentiated technical components include a Criticality Engine that scores assets across 8-10 weighted factors, end-to-end column-level lineage, trust state propagation through lineage graphs, alert clustering with context-driven scoring, AI-generated documentation, a Converse Engine with approximately 300 built-in prompts, and Model Context Protocol (MCP) integrations with Anthropic Claude and Microsoft Copilot.
DQLabs serves enterprise customers across Banking/Financial Services/Insurance, Healthcare and Life Sciences, Retail and Consumer Goods, Government, Energy and Utilities, Manufacturing, and Technology. Named customers and case studies reference Wipro, Deloitte, Tokio Marine, DXC, United Community Bank, a leading American bank, a global consumer goods leader, a global toy and entertainment leader, a global industrial tech leader, a leading waste management company, the City of Spokane, Tacoma Public Utilities, and Brazosport College. The platform is sold through subscription-based enterprise contracts positioned at an accessible price point below legacy catalog suites, with deployment options including cloud SaaS and in-VPC for regulated environments.
The go-to-market combines enterprise field sales (with a prominent "Book a Demo" motion and consultative evaluation), event-driven demand generation (PRIZM World Tour, Gartner Data and Analytics Summit, Snowflake Summit), and product-led growth elements including a Data Observability ROI Calculator, eBooks, webinars, and case studies. DQLabs reports no public revenue or funding data; the company is led by founder and CEO Raj Joseph with Ankush Jain as CMO and David Casillo as CRO, and has been recognized by Gartner (Visionary in the 2026 Magic Quadrant for Augmented Data Quality Solutions, second consecutive year; Representative Vendor in the 2026 Market Guide for Data Observability Tools), Everest Group (Leader in PEAK Matrix 2025), and G2 (Leader in Spring 2026 Data Observability Grid Report). The company holds SOC 2 Type II and HIPAA compliance certifications.
DQLabs firmographics
Firmographics- Name
- DQLabs
- Legal name
- DQLabs, Inc.
- Website
- https://dqlabs.ai
- Company type
- Private
- Founded year
- 2020
- Operating status
- Operating
- Headcount range
- 101–250 employees
- Short description
- DQLabs offers PRIZM, an AI-native enterprise platform that unifies data observability, data quality, and enterprise context for banks, insurers, healthcare organizations, retailers, manufacturers, governments, and utilities, sold via subscription to Fortune 500 and mid-market data teams.
- Ownership category
- akta.pro rank
DQLabs industry classification
Industry- Product category
- Data Observability and Data Quality Software
- NAICS
- Software Publishers (51321)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- Enterprise AI Governance, Risk & Compliance Platforms (Model Risk, Audit, Policies) (HDAEANAE)
- akta.pro secondary industry
- Business Rules & Decision Management Platforms (BRMS/DMN) (HDAEAKAG)
Keywords
Where DQLabs is headquartered
LocationHeadquarters
- HQ city
- Pasadena
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
DQLabs business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Technology or R&D, Personnel, Marketing or Sales, Infrastructure, Operations
Revenue model
- PRIZM Platform Subscription: Subscription-based pricing model for the PRIZM enterprise platform. Positioned at accessible enterprise price point compared to legacy catalog suites. Includes unlimited AI tokens in the first year of subscription.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Subscription | Annual | Enterprise platform subscription with comprehensive features |
Go-to-market motion3 records
Distribution channels2 records
Marketing channels9 records
DQLabs product offering
Product offeringCore offering
DQLabs sells PRIZM, an AI-native enterprise SaaS platform that unifies data observability, data quality, and enterprise context into a single continuously validated control plane. The platform combines autonomous anomaly detection, column-level lineage, AI-suggested quality rules, and an MCP integration that exposes catalog and trust context to external AI agents such as Claude and Microsoft Copilot. It is sold via annual subscriptions to enterprise data teams in banking, healthcare, retail, government, manufacturing, energy, and technology.
Product overview
DQLabs offers PRIZM, an AI-native enterprise platform that unifies three core modules—Data Observability, Data Quality, and Enterprise Context—into a single continuously validated system. The platform operates as a control plane where these three disciplines work as one, providing autonomous monitoring, AI-suggested quality rules, and contextual intelligence for both human and AI consumers. Additional capabilities include Agentic AI Data Management for exposing context to AI agents via MCP integration.
Differentiator
Problem solved
Functional benefit
Brands
- PRIZM: AI-native enterprise platform that unifies data observability, data quality, and context into a single continuously validated system.
Products and services
- PRIZM Platform PRIZM is an AI-native enterprise SaaS platform that unifies data observability, data quality, and enterprise context into a single continuously validated control plane. It serves enterprise data teams and AI agents with autonomous anomaly detection, column-level lineage, AI-suggested quality rules, a Converse Engine with approximately 300 built-in prompts, and Model Context Protocol integration that exposes catalog and trust context to external AI assistants. It is sold via annual subscription to enterprises in banking, healthcare, retail, government, manufacturing, energy, and technology.
- Data Observability Data Observability is the monitoring capability of the PRIZM platform that performs autonomous detection of freshness, schema, volume, distribution, lineage, and dependency anomalies across pipelines, warehouses, lakehouses, and BI tools, including alert clustering and lineage-aware root cause analysis.
- Data Quality Data Quality is the rule and scoring capability of the PRIZM platform that delivers policy-driven data quality rules, AI-suggested quality checks, and reusable quality scores that travel with data from raw ingest through to regulatory reporting.
- Enterprise Context Enterprise Context is the catalog, lineage, and business meaning layer of the PRIZM platform that combines automated discovery, classification, tagging, business glossary, semantics, and lineage to help agents and users find the right data, ownership, and governance context.
- Agentic AI Data Management Agentic AI Data Management is the capability of the PRIZM platform for managing AI agents that act on enterprise data, including context exposure through Model Context Protocol, trust state propagation, and stewardship-grade governance.
Quantifiable outcome
- Leading American Bank improves regulatory data accuracy by 75%
- +7 more outcomes
Companies that use DQLabs
Customer profileNamed customers14 records
Segments12 records
Ideal customer profiles6 records
DQLabs technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration37 records
AI capability9 records
Feature10 records
DQLabs partnerships and signals
Strategic signalPartnerships
14 partnerships are on record, tiered core and standard.
- SnowflakecoreDeep technology integration with Snowflake data warehouse. Prizm connects to Snowflake for metadata ingestion and observability monitoring across Snowflake tables and pipelines. Listed as primary platform integration on website.
- DatabrickscoreTechnology integration with Databricks Lakehouse platform. Prizm monitors Databricks environments for data observability across Spark jobs, schema drift, and quality practices. Dedicated eBook resource for Databricks observability.
- AWScoreAmazon Web Services integration covering S3, Redshift, Athena, EMR, and other AWS services. Part of multi-cloud integration strategy.
- Microsoft AzurecoreAzure integration including Azure Synapse, ADLS, ADF Pipeline, Azure Active Directory, and other Azure services. Listed as platform integration.
- Google Cloud PlatformcoreGoogle Cloud Platform integration covering BigQuery and other GCP services. Part of multi-cloud integration coverage.
- SAPcoreSAP integration for enterprise customers. SAP HANA and SAP data sources monitored for data quality and observability. Case study references SAP master data governance.
- dbtcoredbt integration for transformation layer observability. End-to-end lineage covers dbt models through warehouse to BI. dbt-centric teams highlighted as key persona.
- TableaustandardTableau integration for BI tool observability and usage tracking. Downstream consumption monitoring includes Tableau dashboards.
- Power BIstandardMicrosoft Power BI integration for BI observability. Usage patterns and downstream consumption tracked for prioritization.
- AlationstandardCatalog interoperability with Alation. Domains can be synced from Alation to Prizm. Competitive positioning vs Alation discussed in catalog tools comparison.
- Microsoft PurviewstandardCatalog interoperability with Microsoft Purview. Domain sync capabilities allow customers to consolidate context from existing catalog investments.
- dbt (MetricFlow)standardSemantic layer integration with dbt MetricFlow for metric definitions. Absorbs definitional truth from dbt semantic layer as input to context platform.
- Anthropic (Claude)coreMCP (Model Context Protocol) integration enabling Claude and other AI assistants to query Prizm context, lineage, definitions, and trust signals directly. Strategic integration for AI-native platform positioning.
- Microsoft CopilotcoreMCP integration with Microsoft Copilot allowing Copilot to read Prizm context layer. Strategic integration for enterprise AI workload support.
Scale indicators5 records
Recent moves6 records
Expansion highlights5 records
DQLabs competitors and assessment
Company assessmentBroad incumbents
- Informatica: Legacy data integration and data quality powerhouse with the CLAIRE AI engine. One of the largest enterprise data management vendors globally; DQLabs explicitly references Informatica as a legacy catalog suite it undercuts on price.
- Alation: Enterprise data catalog and governance platform with strong brand recognition among data leaders. DQLabs has a mutual partnership with Alation for domain syncing, indicating both partners and competitors.
- Talend: Data integration, quality, and governance platform now part of Qlik. Comparable to DQLabs in data quality and governed data delivery, particularly for enterprise customers integrating data across hybrid environments.
- Databricks (Unity Catalog): Major cloud data platform whose Unity Catalog offers native data governance, lineage, and observability for the lakehouse. Both a core integration partner and competitive threat to DQLabs' catalog and observability layers on Databricks deployments.
- Collibra: Large incumbent data catalog and governance platform serving hundreds of large enterprises, particularly regulated industries. DQLabs positions against Collibra in catalog tools comparison and competes for the same enterprise governance budgets.
Direct peers
- Soda: Data observability and data quality platform with Soda Core and Soda Cloud offerings, focused on checks-as-code and pipeline-level monitoring. Comparable to DQLabs in targeting data engineers and offering AI-assisted data quality.
- Anomalo: AI-powered data quality platform that automatically monitors enterprise data for anomalies without requiring manual rules. Comparable to DQLabs in applying ML to data validation across warehouse and BI environments.
- Bigeye: Data observability platform providing automated data quality monitoring, anomaly detection, and lineage for cloud data warehouses. Competes directly with DQLabs for enterprise data engineering and data leader buyers.
- Monte Carlo Data: Direct competitor in the data observability category, offering end-to-end data reliability monitoring across pipelines, warehouses, and BI tools. Closest head-to-head with DQLabs in the Gartner Market Guide and serves overlapping enterprise data engineering personas.
- Atlan: Modern data catalog and governance platform with active metadata, lineage, and collaboration features. Competes with DQLabs in the catalog and context layer of the data trust stack and is mentioned in their integrations as a sync partner.
Market position
Strengths5 records
Weaknesses4 records
Competitive moat5 records
Key risks2 records
Key highlights7 records
Customer concentration
DQLabs social profiles
Digital presenceDQLabs compliance and trust
Trust signalCompliance2 records
DQLabs financial estimates
Financial estimateRevenue estimate
Valuation estimate
DQLabs leadership team
Management profileNumber of profiles
Profiles3 records
DQLabs funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
DQLabs M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about DQLabs
What does DQLabs do?
DQLabs sells PRIZM, an AI-native enterprise SaaS platform that unifies data observability, data quality, and enterprise context into a single continuously validated control plane. The platform combines autonomous anomaly detection, column-level lineage, AI-suggested quality rules, and an MCP integration that exposes catalog and trust context to external AI agents such as Claude and Microsoft Copilot. It is sold via annual subscriptions to enterprise data teams in banking, healthcare, retail, government, manufacturing, energy, and technology.
Is DQLabs a public or private company?
DQLabs is a private company. It is classified as founder individual operated bootstrapped and is currently operating.
When was DQLabs founded?
DQLabs was founded in 2020. It employs 101 to 250 people.
Where is DQLabs based?
DQLabs is headquartered in Pasadena, United States, in the North America region.
How does DQLabs make money?
One revenue line is on record: PRIZM Platform Subscription.
Who are DQLabs's main competitors?
Broad incumbents on record are Informatica, Alation, Talend, Databricks (Unity Catalog) and Collibra. Direct peers are Soda, Anomalo, Bigeye, Monte Carlo Data and Atlan.
Does DQLabs have an API?
Yes. The platform exposes capabilities via MCP (Model Context Protocol), allowing AI tools such as Claude and Microsoft Copilot to read catalog metadata, query lineage, and consume trust signals directly. The Converse Engine provides approximately 300 built-in prompts covering catalog discovery, lineage queries, glossary management, metric recommendation, governance gap surfacing, and chart generation. No dedicated public API documentation or developer portal is mentioned; API access appears to be enterprise-facing and integrated through MCP rather than a standalone REST/GraphQL API.
What industry is DQLabs in?
DQLabs's product category is Data Observability and Data Quality Software. Its primary akta.pro industry code is HDAEANAE, Enterprise AI Governance, Risk & Compliance Platforms (Model Risk, Audit, Policies), with a secondary code of HDAEAKAG, Business Rules & Decision Management Platforms (BRMS/DMN). Its NAICS code is 51321 and its SIC code is 7372.