Entity intelligence
for AI systems that make real decisions.
When AI can't reliably identify who it's dealing with, decisions break down. Tilores resolves entity ambiguity at the infrastructure level — built under production pressure, not for demos.
Available on AWS Marketplace · Other hyperscalers and on-premise also supported
Your records are scattered. Your systems disagree. Your decisions suffer.
Customer data sits in your CRM and your support tool and your data warehouse. Supplier data sits in your procurement system and your risk database and your accounting platform. Transaction data sits everywhere.
The same person, company, or transaction shows up in multiple places under multiple spellings. Records get duplicated. Relationships get missed. And every team in your business — fraud, compliance, marketing, analytics, AI — ends up working from a different version of reality.
The downstream cost is real. Duplicates inflate marketing spend and hide fraud rings. Fragmented records break KYC and create compliance gaps. And every AI system you run — fraud models, customer assistants, supply chain intelligence — produces outputs only as good as the entity data it retrieves from.
AI you can't trust
Your fraud model, your customer assistant, your supply chain AI — all retrieving from fragmented records. Inconsistent inputs produce inconsistent outputs, and no amount of prompt engineering fixes a data problem.
Fraud you can't see
The same fraudster signs up three times under name variations. Your system treats them as three new customers.
Compliance you can't prove
KYC, AML, and sanctions screening fall apart when you can't reliably tell whether two records are the same entity.
One resolved view of every entity — updated as data arrives.
Tilores connects to your existing systems, matches records as they arrive, and maintains a single resolved view every team can read from. It sits as a layer in your stack — not a platform you rebuild around.
Real time, not batch
Records are matched as they arrive - sub-300ms ingestion, ~150ms query response. Your resolved data is never out of date. There is no overnight job, no waiting until Tuesday morning, no static snapshot.
Matching rules you can explain to a regulator
Rules are explicit, tunable, and auditable. You can show exactly why two records were linked. You can adjust precision and recall to fit your use case. No black box.
Sits as a layer in your stack
Tilores doesn't demand a sandbox. Source data flows in via GraphQL or pre-built connectors. Resolved entity events flow out to your data warehouse, your fraud platform, your AI applications - whatever you've already built.
# Resolve a company across all your sources
query {
search(input: { name: "Acme Inc." }) {
entities {
id
recordInsights {
name: newest(field: "name")
email: first(field: "email")
phone: first(field: "phone")
sources: valuesDistinct(field: "source")
}
}
}
}{
"entities": [{
"id": "ent_7f2a9b04",
"recordInsights": {
"name": "Acme Inc.",
"email": "contact@acme.com",
"phone": "+1 650 555 0100",
"sources": ["CRM", "ERP", "Shopify"]
}
}]
}Every use case, one platform
From fraud detection and KYC compliance to Customer 360 and AI pipelines — the same resolved entity graph powers every team.
Fraud Detection & Prevention
Detect fraud rings and linked accounts in real-time
Learn more →Customer 360
Build a truly complete view of every customer
Learn more →KYC & AML Compliance
Accelerate identity verification and reduce false positives
Learn more →Data Quality & Governance
Continuously clean and deduplicate your data
Learn more →Marketing & Personalization
Stop duplicate campaigns and personalize with complete data
Learn more →Customer Data Platform
Identity resolution backbone for your CDP
Learn more →Master Data Management
Real-time entity resolution for always-current golden records
Learn more →Supply Chain Intelligence
Resolve company entities before your supply chain intelligence runs
Learn more →Data Privacy Compliance
Answer every DSAR in minutes — not weeks of database archaeology
Learn more →The data layer your AI needs — and that every team already depends on.
Every AI system you deploy — fraud detection, KYC automation, customer assistants, supply chain intelligence — depends on knowing who it's talking about. Not approximately. Exactly. The same entity across every system you have.
When your records are fragmented, your AI guesses. It returns inconsistent answers about the same customer, misses fraud connections that span systems, and hallucinates relationships that don't exist. The problem isn't the model. It's that the model has no reliable entity truth to retrieve from.
Tilores is the resolved entity layer underneath. Think of it as persistent entity memory for your AI — a real-time graph of every resolved person, company, and transaction that every model, agent, and RAG pipeline in your business can retrieve from consistently.
Entity memory for agents and RAG
Vector databases return semantically similar documents. Tilores returns the resolved entity — the unified, canonical view of a customer or company across all your sources. For questions like "who is this person?" you need entity resolution, not similarity scores. The two are complementary.
Always current, never stale
AI that retrieves from last week's batch job will confidently give wrong answers. Tilores resolves new records in under 300ms and updates the entity graph live — so every query returns current truth, whether your agent is checking a supplier risk score or a customer's fraud history.
Auditable, so your AI can explain itself
Every entity link is explicit and traceable. When a regulator asks why your AI flagged this entity or resolved that match, you can show exactly which records were linked and why. No black box. No "the model decided."
Why Tilores, not the alternatives
In head-to-head evaluations, Tilores has won on the hardest data — the noisy, partial, multilingual records no other solution could match reliably.
A team that works alongside yours
Implementing entity resolution well is technical work. The teams who succeed with Tilores aren't the ones who buy the software and disappear - they're the ones who collaborate closely with our engineers to get the matching rules right for their data. Our team works that way by default.
"Accurate supplier data matching and normalization are essential foundations for meaningful data exchange in our ecosystem. Tilores' expertise in entity resolution aligns perfectly with our commitment to providing companies with the technical infrastructure they need to collaborate effectively while maintaining data sovereignty."
Most deployments are running in weeks, not months.
See what resolved entity data does for your business — and your AI.
Whether you're building AI applications that need reliable entity data, or evaluating entity resolution to replace something that's stopped scaling — the fastest way to know if Tilores fits is to see it with your data.
30 minutes with our team to walk through your use case.
Evaluate locally before deploying to AWS or on-premise.
Used by teams at Inato, Grover, Cofinity-X, and others.