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Graph Intelligence Platform - SarasWI by ContexQ

We are technology AI startup leapfrogging the way business
maximize their data value.

Where every entity, signal, and relationship comes together to drive growth.

Your data isn't incomplete — it's underread. ContexQ finds connections and signal-finding across every dimension, then augments with real-world intelligence to surface what matters most — from opportunity to risk.

Foundations don't get built twice.

Graph AI that compounds — solve one problem once, reuse the foundation for every problem that follows.

Without SarasW

Five teams,
five silos.

Every team rebuilds entity resolution and knowledge graphs. Resolution logic drifts. Connections are rediscovered. Intelligence is recomputed. Trust breaks, months later.

ERKGAAERKGAAERKGAAERKGAAERKGAAFive teams. Five foundations. Five truths.
Months per use case · drift accumulates · trust evaporates
With SarasW

One foundation,
everywhere it's needed.

Resolved once. Connected continuously. Intelligence shared. New use cases inherit the substrate — they don't rebuild it.

ENTITY RESOLUTIONresolved onceKNOWLEDGE GRAPHconnected continuouslyADVANCED ANALYTICSintelligence sharedEVERY TEAM · EVERY USE CASE · CURRENT & NEXTOne foundation. Compounding intelligence.
New use cases inherit the foundation · trust accumulates · intelligence compounds
01

Data cleaned once.

Entity resolution is a foundation, not a project. Resolve every customer, counterparty and beneficiary across systems, languages and scripts — once. Every team that follows works on the same trustworthy view, instead of building yet another reconciliation pipeline.

02

Relationships discovered, not declared.

A knowledge graph holds connections you knew to look for — and surfaces the ones you didn't. Hidden ownership chains. Indirect exposures. Unseen affinities. The graph keeps revealing patterns long after the original use case has shipped.

03

Intelligence that compounds.

Analytics built on shared context get sharper with every team that uses them. Features, scores and patterns become reusable assets — not one-off models. New use cases stand on top of what came before, instead of starting at zero.

Build the foundation once.
Let intelligence compound on top.