FINANCEGPT 2.0

From financial intelligence to governed financial action.

FinanceGPT 2.0 connects financial analysis, quantitative finance, Native Intelligence, Knowledge, workflows, governance and Financial Actions so approved financial decisions can move from evidence to controlled action and reconciliation.

FinanceGPT platform FinanceGPT 2.0 Native Intelligence · LQMs/QLMs · Knowledge · Agents · Universal Model Switching · Financial Actions

PLATFORM ARCHITECTURE

Connect financial intelligence to governed action.

Analyse statements, companies, portfolios, forecasts and scenarios, then carry approved work through evidence, policy, authority, approvals, execution and reconciliation in the same governed system.

Action-led platform

Financial Actions gives FinanceGPT a common control plane for carrying approved financial decisions into real economic workflows.

Native-first intelligence

Auto — FinanceGPT Native prefers deterministic finance, bounded classical NLP and local semantic intelligence before escalating to generative language models.

Universal model switching

Users and policies can select eligible language runtimes without transferring deterministic calculations, approvals or financial authority into the selected model.

Knowledge as evidence

Knowledge Intelligence adds permission-aware retrieval, exact source locators, semantic reranking and persistent citation evidence.

Agents and workflows

Finance-specific agents and workflows can prepare, route and coordinate work while remaining inside explicit tool, policy and authority boundaries.

Enterprise control plane

Model routing, AI Credits, BYOK, governance, identity, data classification, evidence and execution controls are explicit platform layers rather than hidden implementation details.

FINANCIAL FOUNDATION

FinanceGPT 2.0 keeps finance-specific analysis and quantitative methods first-class.

Financial analysisBalance sheets, cash flow, profit and loss, liquidity, valuation, forecasting, scenarios and planning remain core product vocabulary and workflows.

Investment intelligenceCompany research, portfolio analytics, risk, models, performance, mandates and custody/reconciliation remain part of the platform.

Large Quantitative ModelsLQMs remain the deterministic, statistical, econometric, simulation, optimisation and approved learned numerical layer.

Quantitative Language ModelsQLMs compose promoted LQMs with an eligible language runtime, evidence, tools and governance rather than asking a language model to become the calculator.

THE 2.0 INTELLIGENCE STACK

Use the cheapest governed engine capable of the task.

FinanceGPT 2.0 is designed as compound intelligence. Generative AI is important, but it is not the only computation layer and it is not automatically the first one.

0Deterministic financeCalculations, SQL, rules, policies, workflow state and Financial Action controls.

1FinanceGPT NLPBounded classical NLP, dictionaries and finance-specific extraction/classification.

2Semantic IntelligenceLocal embeddings, retrieval, reranking and extractive answers where sufficient.

3Local LanguagePrivate open-weight generation when a certified runtime is active and suitable.

4Managed / Premium / BYOKGoverned generative escalation and explicit user/provider choice.

PLATFORM LAYERS

One governed operating model across intelligence, evidence and action.

Area	Financial foundation	Governed platform layer
Primary outcome	Financial analysis, research, quantitative insight and finance AI tools.	Analysis and research plus governed workflows, actions, evidence and reconciliation.
AI architecture	Deterministic, quantitative and language intelligence remain distinct computation layers.	One Native-first routing architecture decides when deterministic, NLP, semantic, local or managed language intelligence is appropriate.
Quantitative finance	LQMs and quantitative tooling provide a finance-specific numerical layer.	LQMs remain first-class and are composed with language runtimes through governed QLMs.
Knowledge	Documents, governed Knowledge and retrieval support evidence-backed analysis workflows.	Knowledge Intelligence provides governed, permission-aware evidence with exact source lineage and local semantic retrieval.
Execution	Automation and finance workflows prepare and coordinate financial work within explicit permissions.	Financial Actions introduces explicit authority, risk, approval, execution handoff and reconciliation checkpoints.
Model choice	Multiple AI providers and models are available through governed model choice and workspace policy.	Universal Model Switching gives one governed request-level contract with Auto — FinanceGPT Native as the default.

FINANCIAL ACTIONS

FinanceGPT 2.0 is built around Financial Actions.

Start with evidence and quantitative finance, use the right intelligence layer, then govern the authority required to carry an approved decision into execution.

Explore Financial Actions