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Precisely Data Matching and Entity Resolution vs Senzing Entity Resolution

Precisely Data Matching and Entity Resolution

precisely.com

Senzing Entity Resolution

senzing.com

Side by side

FigurePrecisely Data Matching and Entity ResolutionSenzing Entity Resolution
Price from—$4,880/mo
Free plan——
Free trial—Yes
Open source——
WebYesYes
WindowsYesYes
macOS—Yes
LinuxYesYes
API—Yes
Self-hostedYesYes
Plans published11
Spec score · Identity Resolution Software7.2 (#19)8.0 (#8)
DeploymentPrecisely says its matching solutions work across on-premises and cloud environments.The maker lists bare metal, Docker, Kubernetes, private cloud, AWS, Azure, and air-gapped deployment options.
Founded19682017
IntegrationsPrecisely’s partner ecosystem includes AWS, Azure, Google Cloud, Cloudera, Confluent, Databricks, Snowflake, SAP, ServiceNow, and Splunk.Senzing lists Python, Java, C#, Rust, Node.js, and an MCP server for connecting the engine to applications and AI agents.
PurposeConnects records across systems that refer to the same real-world entity to create a trusted view of customers, suppliers, assets, and other entities.Senzing resolves fragmented records into entities and reveals relationships between them for fraud, compliance, and AI systems.
SupportPrecisely offers customer support plans, including 24/7 severity support, and a portal with documentation, downloads, API information, and forums.Senzing says support is included with paid subscriptions at no additional charge and is free.

Plans

Precisely Data Matching and Entity Resolution

  • Data matching and entity resolution solutionsPriced on request

Precisely Data Matching and Entity Resolution pricing →

Senzing Entity Resolution

  • Senzing Subscription Pricing — 10M DSRs$58,560 a year

Senzing Entity Resolution pricing →

In their own words

Precisely Data Matching and Entity Resolution

Precisely Data Matching and Entity Resolution links records across systems when they refer to the same real-world entity. It is designed to create trusted views of people, households, businesses, suppliers, assets, products, parts, and locations for uses such as customer 360, fraud detection, anti-money laundering, and business decisions. Configurable matching and AI/ML support work across large, complex datasets with less dependence on IT. Precisely solutions can profile data, apply business rules, and enrich records with demographic, firmographic, and location intelligence before matching. Spectrum Quality provides phonetic, distance-based, and country-specific algorithms for B2B and B2C names across more than 200 countries. The solutions work in on-premises and cloud environments; listed platforms include Linux, Windows, web, and self-hosted. Batch file import, household matching, and organization matching are supported. Precisely reports that Schwan’s experienced a 25% decrease in new customer duplicate data. Pricing is available on request. The company was founded in 1968 and is headquartered in Burlington, Massachusetts, USA.

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Senzing Entity Resolution

Senzing Entity Resolution combines fragmented records into entity profiles and surfaces links among them for fraud, compliance, and AI applications. The maker describes its engine as real-time, relationship-aware, self-tuning, and self-correcting, without custom training or tuning. It says the engine starts in under one second and scales from tens to billions of records within a customer’s infrastructure. Decisions can include an audit trail explaining matches, contributing features, and a confidence score. Senzing says customer data stays in that infrastructure and does not flow to Senzing, Inc.

Deployment options include bare metal, Docker, Kubernetes, private cloud, AWS, Azure, and air-gapped environments. Integrations include Python, Java, C#, Rust, Node.js, and an MCP server; AWS Marketplace and Microsoft Marketplace handle real-time JSON requests and responses. The SDK’s free license covers 500 source records, while the AWS Marketplace trial covers 250,000. A listed subscription is $58,560 a year for 10M DSRs, with support included.

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