TiloresReal-time customer data unification for resolving fragmented records across systems
Overview
Key features
- Fuzzy matching and entity resolution
- Real-time unified customer profiles
- REST and GraphQL APIs
- Configurable matching rules
- Connects multiple data sources
- Scalable cloud infrastructure
Pricing
- Model
- Free
- Category
- Data Analysis
- Rating
- 4.5 / 5 (6)
Use cases
Fraud Detection Across Systems
Unify customer records from multiple sources in real time to spot duplicate identities, suspicious patterns, and inconsistencies that indicate fraudulent activity.
Compliance and KYC Checks
Consolidate fragmented customer data to support compliance workflows, ensuring accurate identity verification and regulatory reporting across databases and applications.
Personalized Marketing Campaigns
Query unified customer profiles via API to power segmentation and personalization, delivering consistent messaging based on a complete view of each customer.
360° Customer Support View
Give support teams a single, real-time view of customer interactions and records pulled from CRMs and other systems without migrating data to a central warehouse.
Pros & Cons
Pros
- Real-time entity resolution across disparate sources
- API-first design for easy integration
- Handles fuzzy matching and inconsistent data
- Scales to large datasets without manual cleansing
Cons
- Requires technical setup and engineering resources
- May be overkill for small or simple datasets
- Pricing and configuration less suited to non-technical users
Reviews
Average from 6 ratings.
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Solid for our team
We rolled this out across the team last quarter and handles fuzzy matching and inconsistent data. Scalable cloud infrastructure fits neatly into how we already work, and rEST and GraphQL APIs removed a step we used to do by hand. but it has held up under daily use.
Skeptical, then convinced
I went in skeptical — most tools in this space overpromise. It actually delivers on configurable matching rules, and scales to large datasets without manual cleansing caught me off guard. still, I'd recommend giving it a real trial.
Does the job
Pretty happy overall. Real-time unified customer profiles just works and handles fuzzy matching and inconsistent data. Requires technical setup and engineering resources can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.
Solid for our team
We rolled this out across the team last quarter and scales to large datasets without manual cleansing. Configurable matching rules fits neatly into how we already work, and configurable matching rules removed a step we used to do by hand. Requires technical setup and engineering resources, which is the main caveat, but it has held up under daily use.
Use it every day
Honestly didn't expect to like it this much. Scalable cloud infrastructure is exactly what I needed, and aPI-first design for easy integration. but I reach for it almost every day now and it just clicks.
Years in this space
I've evaluated a lot of these over the years. What stands out here is real-time unified customer profiles — handled better than most — and real-time entity resolution across disparate sources. Requires technical setup and engineering resources is my one real gripe. Worth the time if this is your use case.
Q&A
What integration options are available for accessing unified customer profiles?
Tilores exposes unified profiles through both REST and GraphQL APIs, allowing easy integration with applications, analytics tools, or downstream services across any language or platform.
Asked by Linda Petersen · Feb 19, 2026
Can Tilores be used for high‑volume use cases like fraud detection or KYC compliance?
Yes, the platform is built on scalable cloud infrastructure and can process large datasets in real time, making it suitable for fraud detection, AML/KYC checks, and other compliance scenarios.
Asked by Hosanna Marte · Feb 18, 2026
What technical resources are required to set up Tilores in an organization?
Implementation needs engineering or data‑team involvement to configure data source connectors, define matching rules, and integrate the API; it is not a plug‑and‑play solution for non‑technical users.
Asked by Aaliyah Johnson · Nov 25, 2025
How does Tilores handle real-time entity resolution without a centralized data warehouse?
Tilores connects directly to source systems and applies fuzzy matching and configurable rules on the fly, creating unified customer profiles via its REST and GraphQL APIs without moving data into a separate warehouse.
Asked by Gustav Lindberg · Nov 21, 2025
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