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Platform · Sfere Blocks

Connect everything,
enrich every signal

Sfere Blocks is the customer data infrastructure (CDI) that brings every customer signal in, stitches it to one identity, enriches it for AI and activation, and distributes governed data to every tool, without rip-and-replace

Book a Demo Fire a signal
  • Typed events
  • Real-time stitch
  • Governed by default
  • No rip-and-replace

Playable · The pipeline

Fire a signal,
watch it join a profile

Seven touchpoints, one stream, one identity. Fire events from the sources below and watch identifiers stitch into a golden profile the moment they land. Then flip to the nightly batch and see what real-time collection changes

01 · Signals arrive

email loyalty ID device cookie same color = same customer

Fire them in any order, or press ▶ Watch the story. When two threads share a colored dot, they merge and a customer appears in panel 03

02 · Threads wait for a match

Nothing has happened yet. Each source you fire drops its identifiers here as a thread. A thread that shares a colored dot with the customer on the right gets pulled in; one that shares nothing waits

Threads land here, colored by the identifiers they carry:
fire a signal to start the stream

03 · One customer emerges

No customer yet
The moment two threads share a colored identifier, they merge into one known customer here and their whole history back-fills

Same profile, onward to every tool

CRM Ads Email Support

Destinations light up once a profile resolves. Each receives the same resolved customer, not a different export

A customer who buys at 7:42 PM is known at 7:42 PM, not tomorrow morning: that is the whole argument for stitching in real time

What Blocks gives you

Every signal,
one governed pipeline

Blocks handles collection, enrichment and delivery across your data stack, so every downstream system works from the same resolved customer profile

  1. 01

    Data collection

    Ingest events from every customer touchpoint (web, app, ticketing, streaming, point-of-sale, and offline sources) through an open connector framework. Raw payloads are normalized and validated as they arrive, so the data feeding your profiles is already clean before it reaches Sfere ID

  2. 02

    Identity stitching

    Match identifiers across devices, channels, and sessions as events land, so stitching runs in real time rather than as a nightly batch job. The resulting graph, its merge rules, and the governed profile live one layer up, in Sfere ID

  3. 03

    AI-ready enrichment

    Enrich every customer profile with first-party signals and derived attributes before they leave your environment, so downstream models and agents receive governed, structured context instead of raw event logs

  4. 04

    Reverse ETL

    Push governed customer data from your warehouse back to every operational tool in your stack. CRM, ad platforms, email, and support systems all receive the same resolved profile rather than a different export pieced together from each source

  5. 05

    Integrations

    Connect your existing marketing, analytics, and data-science tooling through a programmable integration layer. Configuration is API-driven and version-controlled, so integrations behave like infrastructure you own, not a vendor console you depend on

AI enablement

Structured context,
not raw events

Models and agents perform best when they receive governed, structured input, not raw event streams with inconsistent identifiers and missing attributes. Blocks enriches and structures customer data before it reaches any AI surface, so every downstream agent starts from a profile that is already resolved, governed, and enriched

  • Profiles are enriched inside your environment before they reach any external surface, so governance and residency rules are honored end to end
  • Derived attributes and scored features land on the same profile that drives segmentation, so AI context and activation context stay in sync
  • Reverse ETL suppresses already-converted customers from ad audiences, so budget reaches people who can still move
  • Every enrichment step runs on data you own and control; no vendor sees the underlying customer graph
See how profiles are segmented →

Drag the divider: enrichment is the difference between a log and a person

How it works

Collect, stitch, distribute

Blocks sits at the base of the Sfere platform, normalizing raw signals into typed events, resolving identifiers in real time, and distributing governed data to every tool in your stack

  1. 01

    Collect every signal

    Client-side SDKs and server-side connectors capture events across every touchpoint and deliver them into a typed, normalized event stream. No custom ETL to write, no parallel database to maintain alongside the sources you already run

  2. 02

    Stitch and resolve in real time

    Events are deduplicated and matched across identifiers as they arrive. The customer graph grows with every new signal, and every new resolution back-fills history across all linked identifiers, so profiles are always as complete as the data allows

  3. 03

    Distribute to the full stack

    Resolved, enriched profiles flow forward to Sfere ID for segmentation and downstream to every operational tool through reverse ETL. One governed source of truth, with no exports to re-sync between systems

Connect the stack you already run

See Sfere Blocks collect, stitch, enrich, and distribute on your own sources. Book a walkthrough and we'll map the pipeline to your tools, your warehouse, and your residency requirements

Book a Demo