Proactively govern, enrich, and activate data with full context, observability, and automation—ensuring trusted, AI-ready data flows seamlessly across your enterprise.
Connect hundreds of systems as sources that contribute data and metadata to the unified model.
Keep your systems in sync with master records, no iPaaS needed
Resolve entity identities across systems.
Control data authority, policies, role management, global deletes, and compliance.
Workflows that operate on 360° data across multiple domains.
Activate datasets in business systems in near realtime.
Create unified data models for any domain.
Tag, search, report and certify metadata.
Programmable MDM, functions, actions, custom functions.
Common categories, phone number conventions, addresses and more.
Apply DQ policies to make sure incoming data adheres to your standards.
Fix data quality issues, manage duplicates and merge records.
Create metrics, summaries and signals from across unified models via datasets.
Version control for your data, time machine for your data.
Monitor, alert and report on data anomalies and metadata changes across systems.
Create and share live dashboards and reports from your source of truth master data.
Make master data available directly to in existing BI tools, AI infrastructure and other ecosystems via SQL or APIs.
Effortlessly integrate data across multiple domains with advanced bi-directional connectors. These schema-aware connectors link various sources to a unified data model. Synapse, our robust and intelligent API connector, understands each connection’s schema, ensuring precise data synchronization and workflow execution across all connected systems.
Establish a unified data model and perform data quality analysis, remediation, and normalization. Configure merge and dedupe policies for any-entity resolution and achieve a comprehensive 360-degree data set to seamlessly operate across multiple domains.
Seamlessly apply a data governance framework with fine-grain control from the entity level down to individual fields. With robust access controls, detailed change logs, and comprehensive tracing, ensure data integrity and security at every level. Syncari enforces data lineage visibility and centralized correction capabilities, while data authorities ensure consistent data ownership and accuracy across all systems.
Listen for signals, triggers, and data conditions to keep data fresh and AI/LLMS ready. Leverage active master data, metadata, and virtual entities in process automations—all from a single platform that can function independently or work seamlessly with existing tools.
Align teams around key metrics across unified systems, ensuring consistent data visibility in the tools they love. Access the centralized data store or integrate your own for seamless BI/analytics and data product consumption.
Point solutions solve point-in-time problems. Syncari grows with you as your needs evolve.
Unlock intelligent, autonomous data management with real-time governance and trusted data activation. Test Drive Syncari now and accelerate your data modernization.
Syncari Autonomous Data Management (ADM) platform is the future of MDM.
Syncari ADM is one cohesive platform to sync, unify, govern, enhance, and access data across your enterprise. Experience continuous unification, data quality, distribution, programmable MDM, and distributed 360°.
Syncari capabilities covers the existing MDM capabilities and more. Syncari is paving the way for next-gen MDM. What makes Syncari the next wave are the following:
Syncari, with its suite of advanced features, is well-positioned to be considered as part of the MDM 3.0 or next-generation MDM wave, especially due to its alignment with modern data management trends and the growing demands for agility and scalability in enterprise data environments. Given the characteristics below, Syncari can be seen as embodying the principles of MDM 3.0 by offering a comprehensive, modern solution that addresses the complex data challenges faced by today’s enterprises. Its features promote improved data governance, integration, usability, and real-time operations, all of which are hallmarks of next-generation MDM systems.
Unlike traditional API-based connectors, Syncari Synapses deeply connect to top business systems and manage the impact of data and schema changes across sources. They’re fault tolerant and can be configured in a few simple steps – keeping your focus on your business, not the business of APIs and integration.
Multi-directional sync refers to a type of data synchronization (sync) between multiple systems, where data is updated and exchanged in one or more direction at the same time, rather than just one-way or bi-directionally. This prevents data drift, allows for data to be updated, synchronized and governed across your entire tech stack, making consistent data system available for activation and consumption. Oh yeah, and Syncari holds a patent on this.
For those who want to geek out:
Our patented multi-directional sync engine provides a highly configurable unification, transformation and augmentation layer. It also handles data congruency and integrity. It can scale to manage thousands of concurrent data streams. These data streams are near real-time, are generated by our Synapses (see below), and all look the same.
Data synchronization (sync) and data integration are related concepts but have some key differences.
Synchronization refers to the process of making sure that data is both available and consistent across multiple systems. This is done by regularly comparing the data in each system and updating it as needed to ensure that it remains in sync.
Data integration, on the other hand, refers to the simpler process of sending data from one system to another, often in a style that looks like copy/paste. When it comes to customer data, synchronization is a must-have.
We’ve created a unified data model that functions as a semantic layer over all of your source systems, allowing the entire organization to run using a single data language. This includes how you integrate, how you unify and transform entities, how you define core metrics, and ultimately how you understand what changes these metrics by looking at data more holistically. Also, the unified data model is elastic and is able to easily accommodate changes to data schemas over time. For example, when a system admin adds new fields to entities in a source system, an elastic data model would enable you to remediate schema drift and incorporate that change without breaking any downstream processes or reports.
It is designed to be flexible and scalable, able to adapt to changing requirements and business needs without requiring significant overhauls to underlying systems or data architecture.