Data-driven companies use the Tilores API to create a unified customer view across all their source systems. They build real-time solutions to manage risk, uncover fraud, and deliver personalized digital experiences, without the engineering complexity.
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Inconsistent, incomplete, and out-of-date customer data makes it hard to align, plan, and report across your business. Before businesses can make use of their customer data, first they need to standardise their schemas, then unify new and historic data.
Even then, building on top of unified customer data in a single centralised system often requires dedicated development resource. Instead, unified customer data should be synced back to each department’s source system, making each system a distributed source of truth. Only then can businesses effectively manage risk, uncover fraud, and better serve their customers.
SOLUTION
Turn scattered and siloed customer data into a unified Customer 360 view. Sync complete profiles to each department's source system to better serve customers, align internal teams, and inform product development.
SOLUTION
Detect fraud at account creation by querying a real-time stream of your unified customer data to match new sign-ups to existing customers or uncover their relationships with other account holders.
SOLUTION
Upgrade your LLM's performance by using realtime fuzzy search on your structured data, so it can retrieve accurate, relevant, and unified customer or company data, and respond to prompts with greater context.
Unify new and historical customer data, and build new use cases on top of it.
Sync unified customer data back to every source system without the engineering complexity or overheads.
Query unified customer data with clear reasoning for each profile merge or relationship mapped.
How Banxware unified their scattered customer data to improve internal reporting, credit risk assessment and prevent fraud at sign-up.
Connect your source systems using our globally distributed GraphQL API or prebuilt connectors like Salesforce, Hubspot or Snowflake. Before ingestion, all customer data is cleansed, normalised, and enriched to match a unified schema. Read Docs
Unify your customer data and sync back to source systems. Understand the rationale behind unified records or relationship mapping, and adjust parameters to align with your business needs. Read Docs
Each source system is up-to-date so internal departments can report and build on their customer data independently, without relying on a data analytics team or waiting for developer resource. Use Cases
The API to unify scattered customer data in real-time.
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