StreamFuse
Entity resolution for messy operational data

Resolve records while the business is still moving.

StreamFuse turns duplicate companies, accounts, people, and vendors into durable entity IDs across APIs, CSV/XLSX imports, and event-driven pipelines with explainable match evidence.

Streaming identify API Bulk import with profiles Identifier-aware decisions Evidence on every match
Live match decision company-account · balanced profile
Matched in 74 ms

Incoming records

Salesforce Acme Health, Inc.
acmehealth.comChicago, IL
HubSpot ACME Healthcare
acmehealth.com312-555-0188
Billing Acme Dental Group
acmedental.coDenver, CO

Candidate search

Domain agreement0.99
Phone + geo signal0.93
Name normalization0.88
Domain conflictblocked

Canonical entity

Created / linked ent_company_8fd2...a77c
Matched fieldsdomain, phone, city
Blocked recordDenver dental org
Confidence0.96 auto
Actionlink + explain
API + bulksame match engine
Profilesper entity behavior
Evidencewhy it matched
Ops readyhealth + metrics
Event Stream
StreamFuse
Canonical Entity

Deploy StreamFuse alongside Kafka, APIs, or event-driven pipelines to resolve entities as events arrive.

1

Semantic matching + confidence scoring

Resolve entities based on meaning and context — not brittle rules or exact matches.

2

Sub-second resolution at stream scale

Millisecond-level response times optimized for real-time streaming workloads.

3

Multi-tenant, production-ready

Secure API with organization isolation, auditability, and enterprise controls.

Implementation Blueprint

A typical rollout follows a simple three-step path: configure matching behavior, validate quality with your data, then move traffic from pilot to production.

1

Set up workspace + API key

Create your organization, generate credentials, and connect your first source system.

2

Define match behavior

Choose entity type and start with a preset like high-precision, person-matching, company-matching, high-recall, or balanced.

3

Go live with streaming traffic

Send events through `/v1/identify` and return canonical IDs to downstream systems in real time.

Accurate Entity Resolution

Accurately resolves entities based on meaning and context — not brittle rules or exact matches.

Tune for precision when incorrect merges are costly, or recall when coverage matters most.

Built for Streaming

Designed for Kafka, APIs, and event-driven architectures where entities arrive continuously.

Built to operate inline, not as a batch step.

Production-Ready by Design

Secure, multi-tenant API built to run reliably in production environments.

Includes isolation, auditability, and enterprise controls.

Where Teams Deploy StreamFuse

StreamFuse fits event-driven platforms where identity quality must be maintained continuously, not via delayed batch cleanup.

Fraud and identity ops

Resolve identities during transactions to reduce false positives and missed matches.

Customer 360 pipelines

Unify profiles across channels as events arrive, without waiting on nightly jobs.

Event enrichment services

De-duplicate and enrich records inline before forwarding to downstream topics.

ML feature infrastructure

Feed cleaner entity identifiers into real-time features and model serving systems.

Pricing

Start with a real pilot, then scale by resolved-record volume and throughput needs.

Evaluation

Free pilot

$0 to validate fit
  • Test API and bulk workflows
  • Create match profiles for your domain
  • Review evidence before rollout
  • No contract required
Start free
Pro

Higher throughput

30M identify calls / month
  • 100 requests per second
  • 1M rows per bulk import
  • Larger files and higher-volume jobs
  • Built for serious operational pipelines
Talk through Pro

Exact plan checkout appears after signup in Billing.

Ready to resolve entities in real time?

Get started in minutes and send your first event through StreamFuse.

Get Started

Contact StreamFuse

Questions about a pilot, setup, imports, or matching behavior? Reach out and we will help you get moving.

support@streamfuse.com sales@streamfuse.com