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Bijection vs Quantexa

Quantexa is a London company best known for entity resolution: it takes records from many systems, works out which ones describe the same customer, company or supplier, and builds a graph of how they connect. Banks, insurers and public bodies use it for anti-money laundering, KYC, fraud and customer intelligence, with investigators working from explainable scores. It runs on premises, in the cloud or both, and was a Leader in Gartner’s 2026 Magic Quadrant for Decision Intelligence Platforms.

Bijection also links records across systems into one model, but to run operations rather than to investigate networks: a transactional database for your ontology and operations, defined in TypeScript, where each change is approved, recorded and sent back to the systems that own the data. It has nothing like Quantexa’s entity resolution at scale, and it is much smaller.

What it is
BijectionA transactional database and runtime for your ontology, operations and applications.
QuantexaA decision intelligence platform that resolves records into entities, builds a graph of how they connect, and scores them for investigation.
Where you start
BijectionAn operational model: objects, operations and approval rules.
QuantexaYour records, resolved into entities and a network of relationships.
How you build
BijectionTypeScript definitions in your Git repository, written by developers or coding agents. There are no visual builders yet.
QuantexaConfiguration on a Scala, Spark and Python platform, with ready-made configurations, low-code tools and packaged products such as Cloud AML.
Identity across systems
BijectionRelationships declared in code, with each source’s own identifiers kept.
QuantexaEntity resolution across very large volumes of records, as the core of the product.
Where it runs
BijectionA dedicated single-tenant environment per customer, operated by us. Not in your cloud account or on premises today.
QuantexaOn premises, in the cloud or hybrid, including a SaaS anti-money-laundering product on Azure.
AI
BijectionModel calls are bounded steps with typed output. Agents reach data through scoped MCP endpoints and go through the same approvals as people.
QuantexaQ Assist, grounded in the entity graph and working with the major model providers, and an agent gateway that supports MCP.
Maturity
BijectionEarly. A small team and a focused core.
QuantexaFounded in 2016, more than 900 people, with customers such as HSBC, Standard Chartered and Vodafone.

Choose Quantexa if

  • Your core problem is financial crime, KYC or fraud across very large volumes of records.
  • You need entity resolution and network analytics with explainable scores for investigators.
  • You must run on premises or in a hybrid setup.

Choose Bijection if

  • Your need is to run processes: people and agents changing records across systems, with approvals and a record of every change.
  • You would rather define the business in code, reviewed and versioned like the rest of your software, and let coding agents write most of it.
  • You want a dedicated environment and a small team that builds your first process with you.
Talk to us How Bijection handles security

Sources

What this page says about Quantexa comes from these public pages, last read on 28 September 2026. Products change; if something here is out of date, tell us and we will correct it.