industries

Every industry. One substrate.

The highest-value AI workloads in every vertical need more than one data model at once. Thirteen industries, seventy-eight workloads — each mapped to the query shapes it actually requires.

01
Banking

Retail, corporate & transaction banking

Customer 360 · AML graph · RM copilot
SQL Graph Vector
02
Financial Services & Payments

Aggregators, PSPs, networks & fintech platforms

Merchant risk · real-time fraud
Graph SQL Vector
03
NBFCs

Non-banking financial companies & co-lending

Alternate-data credit · NPA early warning
Vector SQL Graph
04
Lending

Digital origination, BNPL & embedded credit

Document intelligence · fraud rings
Vector Full-text SQL
05
Insurance

Life, general, health & takaful

Fraud networks · claims STP · underwriting
Graph Vector SQL
06
Wealth Management

Private banking, RIAs & family offices

RM copilot · household graph · suitability
Vector Full-text SQL
07
Mutual Funds

Asset management companies, RTAs & distribution

Distributor graph · redemption prediction
SQL Graph Vector
08
Capital Markets

Broking, exchanges, clearing & institutional

Surveillance · algo audit · research
Graph SQL Full-text
09
E-Commerce & Retail

Marketplaces, D2C & omnichannel retail

Semantic search · recos · promo abuse
Vector SQL Graph
10
Healthcare

Providers, payers & health systems

Patient 360 · clinical copilot · revenue integrity
SQL Graph Vector
11
Telecom

Mobile network operators, ISPs & tower companies

Network RCA · churn · revenue assurance
SQL Vector Graph
12
BPOs & Contact Centres

BPM providers, captives & global capability centres

Agent assist · full-population QA
Vector Full-text SQL
13
Airlines & Aviation

Carriers, cargo, MRO & ground handling

IROPS recovery · predictive MRO
Graph SQL Vector

Impact statements across these pages are directional targets referenced to published industry research — calibrate against your own baseline.

the pattern underneath

Different industries. The same architectural problem.

01
Fraud and abuse are graph problems.

Every vertical on this page faces an adversary that operates as a network. Rings and collusion are invisible to per-entity rules — the pattern only exists in the relationships.

02
Every copilot is a hybrid-retrieval problem.

Copilots rarely fail by generating badly. They fail by retrieving a plausible document while missing the live record, the entitlement or the relationship that changes the answer.

03
Explainability is a write-path property.

Regulators ask you to reconstruct the decision. That is only answerable if the decision, its evidence and its audit trail were written together in the first place.

Start with your data challenge — not a product demo.