AnankeANANKE

Ananke is the intelligence layer beneath Provarion.

Ananke structures entities, relationships, evidence, exposures, scenarios, provenance, and reasoning into a shared economic intelligence layer.

Product system

Ananke

SYS: ANANKE
ServesPlatform team, data layer
Primary workflowShared intelligence infrastructure
Powered byANANKE

Inputs

SRC
Portfolios
Issuers
Sectors
Macro series
Filings
News

SYS: ANANKE

Intelligence layer

Entity registry
Ontology
Evidence graph
Exposure engine
Scenario engine
Provenance
Evaluation
Reasoning

Product surfaces

OUT
Metis
Themis
Kairos
Nemesis
Shared ontology, evidence graph, provenance, and reasoning standards keep product surfaces coherent.

Problem and audience

Built for the Provarion platform and product family.

Financial information is scattered across tickers, portfolios, filings, news, macro series, sector classifications, models, and client conversations. Ananke exists to turn those fragments into a structured layer where relationships can be represented, tested, traced, and explained.

How it works

Ananke starts by resolving entities and economic concepts, connects them through an evidence graph, then applies exposure, scenario, relevance, provenance, evaluation, and reasoning layers before any product surface explains the result.

Key capabilities

What Ananke is designed to support.

ANANKE-01

Core architecture

Ananke combines an entity registry, economic ontology, evidence graph, ingestion layer, exposure engine, scenario engine, event relevance layer, provenance system, evaluation layer, and reasoning layer.

ANANKE-02

Entity registry

Companies, assets, sectors, macro variables, filings, news, portfolios, and client contexts are represented as inspectable entities.

ANANKE-03

Economic ontology

Economic concepts and relationships are modeled so the system can reason over exposures, dependencies, and relevance.

ANANKE-04

Evidence graph

Ananke should not create relationships because they sound plausible. A relationship exists only when supported by evidence, source metadata, method, timestamp, and confidence.

ANANKE-05

Exposure and scenario intelligence

Portfolios and entities can be connected to sectors, rates, geographies, inputs, filings, events, and macro variables so scenario context is structured before it is explained.

ANANKE-06

Reasoning with boundaries

Language models may explain and reason over structured intelligence, but they do not invent market facts, fabricate relationships, or create recommendations.

ANANKE-07

Provenance and evaluation

Outputs are designed to carry source data, method, timestamp, confidence, system version, and uncertainty.

ANANKE-08

Product power layer

Ananke powers Metis, Themis, Kairos, and Nemesis with a shared ontology, evidence graph, and reasoning standard.

Example workflow

From signal to structured context.

STEP 01Raw financial inputs
STEP 02Entity and concept resolution
STEP 03Evidence graph construction
STEP 04Exposure and relevance analysis
STEP 05Provenance and evaluation checks
STEP 06Product-surface explanation

Boundary

Designed for decision support, not unsupported advice.

Ananke is infrastructure for analytical and workflow intelligence. It is not a trading system, brokerage, robo-advisor, or recommendation engine.

Not a standalone dashboard science project.
Not a source of unsupported financial facts.
Not a trade recommendation engine.

G-01

Traceable outputs

Source, method, timestamp, confidence, and uncertainty stay visible.

G-02

Structured reasoning

Models explain over structured intelligence; they do not create financial facts.

G-03

Evidence boundaries

Unsupported relationships, prices, risks, or recommendations are out of bounds.

G-04

Advisor-safe language

Communication support respects compliance-sensitive boundaries.

G-05

Uncertainty-aware

Uncertainty is shown as part of the intelligence, not hidden behind fluent text.