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RECOGNITION · PROGRAMMES · ECOSYSTEM · TRUST FinanceGPT Labs
QUANTITATIVE GENERATIVE AI

Make quantitative intelligence programmable through language.

FinanceGPT combines Large Quantitative Models, deterministic quantitative engines, financial data, Quantitative Language Models, evidence and governed financial workflows in one platform.

Language interprets the question. Quantitative systems own the numbers.

Financial intelligence and governed action for modern finance.

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4,9k enterprise accounts Financial analysis · investment intelligence · quantitative finance · workflows · governed AI · Financial Actions

The background transaction activity animation retains the governed money-movement lifecycle while the primary hero visual explains how language, evidence and quantitative systems work together.

ASK IN LANGUAGE What happens to this portfolio if rates stay higher and volatility rises?
01 · QLM Interpret & decompose Intent, portfolio context and quantitative tasks.
02 · EVIDENCE Assemble trusted context Observed data, holdings, assumptions and provenance.
03 · QUANTITATIVE SYSTEMS Calculate & generate states Deterministic models, statistical methods and governed LQMs.
04 · GOVERNED RESULT Explain the evidence-backed conclusion Language synthesizes the result without becoming numerical authority.
NUMERICAL AUTHORITY Quantitative systems
ACTION AUTHORITY Separate policy, approval & Financial Actions controls
EVIDENCE · RECOGNITION · GOVERNANCE

Financial intelligence with evidence, governance and an ecosystem behind it.

FinanceGPT Labs brings quantitative finance, governed intelligence, workflows and Financial Actions together with visible evidence, review boundaries and public trust resources.

Explore the Trust Center Verify NVIDIA Marketplace listing
Listed on NVIDIA MarketplaceEnterprise Applications · Verify listing
NVIDIA Inception logo Ecobank Fintech Challenge logo Fintech Sandbox logo Global FinTech Hackcelerator logo AI in Finance Global Challenge logo Startup Battlefield 200 logo
Trust CenterSecurity, evidence, governance and assurance. Evidence & provenanceObserved, calculated, synthetic and governed output stay distinct. Research & quantitative modelsPublic definitions, methods and financial intelligence research.
THE FINANCEGPT ARCHITECTURE

Compute. Reason. Act.

FinanceGPT keeps quantitative computation, language reasoning and financial authority distinct but composable. Natural language can program and interrogate quantitative systems without becoming the numerical source of truth.

01Intent
02Evidence
03Quantitative computation
04Quantitative model
05Governed interpretation
06Action
01 · COMPUTE

Quantitative Intelligence

Calculate, simulate, forecast, optimize and generate quantitative states using deterministic methods, statistical models and governed LQMs.

Quant Kernel · forecasting · risk · optimization · scenarios · LQMs
02 · REASON

Quantitative Language Intelligence

Interpret intent, retrieve evidence, decompose quantitative tasks, invoke the appropriate models and synthesize the result through governed QLM orchestration.

Intent · evidence · task decomposition · model invocation · grounded synthesis
03 · ACT

Quantitative Action

Convert governed analysis into workflows, review, approvals and Financial Actions while keeping execution authority separate from model output.

Workflows · human review · approvals · Financial Actions · reconciliation
This is language-programmable quantitative computing. Language helps formulate and explain the work. Quantitative systems remain responsible for the calculations, and Financial Actions require separate authority.
01Investment research & portfolio intelligence 02Scenario generation & stress testing 03Risk & exposure intelligence 04Financial modelling through natural language 05Financial document & structured-data reasoning
START WITH YOUR WORK

One FinanceGPT platform. Clear entry paths for the work you do.

FinanceGPT spans finance operations, investment management, application development and enterprise governance. Start with the responsibilities closest to you; shared data, intelligence, workflow, action and evidence capabilities remain connected underneath.

Finance Teams

Run finance with connected intelligence and controlled automation.

CFOs, finance directors, FP&A, treasury, controllers and finance operations

Explore Finance for Teams
Investment & Markets

Research markets, construct portfolios, manage risk and move approved decisions through governed execution.

CIOs, portfolio managers, analysts, quants, risk and investment operations

Explore Investment & Markets
Developers & Fintechs

Build financial applications with FinanceGPT data, intelligence, workflows and governed Financial Actions.

Developers, fintech teams, solution architects and platform engineers

Explore the Developer Platform
Enterprise Governance

Govern AI, models, workflows, approvals and financial authority across the organisation.

CIO, CTO, CRO, model risk, security, compliance, audit and platform teams

Explore Enterprise Governance
CONNECTED FINANCIAL WORK

From a financial question to an evidence-backed quantitative conclusion.

The buyer story is deliberately simple: language formulates the problem, evidence establishes context, quantitative systems calculate and generate states, and governance determines what can happen next.

EXAMPLE INVESTMENT QUESTION
Find companies able to withstand a 20% revenue contraction, trading below a normalized valuation range, with improving earnings quality.
Language does not estimate the answer.It decomposes the request into measurable quantitative work.
01
InterpretDefine resilience, valuation and earnings-quality conditions.
02
EvidenceResolve financial statements, market observations and historical context.
03
ComputeCalculate balance-sheet resilience, normalized valuation and quality measures.
04
GenerateWhere appropriate, governed LQMs generate conditional quantitative states or scenarios.
05
ExplainThe QLM composes an evidence-backed conclusion with model and source context.
06
ReviewAny workflow or Financial Action remains subject to separate policy and authority.
FINANCIAL ACTIONS

Finance does not end with an answer.

FinanceGPT can turn intelligence into a governed Financial Action: structure the proposal, apply controls, route human approval, issue scoped authority, submit through the configured provider or integration and reconcile what happened.

Understand Decide Propose Control Approve Authorize Submit Reconcile
01

Prepare with evidence

Translate treasury needs, collection intent, investment decisions or other finance work into a structured proposal with source and calculation context.

02

Apply controls and approval

Evaluate policy, limits, risk and required human approvals without treating AI recommendations as transaction authority.

03

Submit and reconcile

Where separately authorized, approved actions move through configured providers or integrations and return status, outcome and reconciliation evidence.

PRODUCT JOURNEYS

See FinanceGPT through complete financial workflows, not a feature catalogue.

Each journey begins with a different responsibility and converges on the same evidence, workflow, governance and action foundations.

Finance Teams

Monday morning finance review

Move from financial position and exceptions into planning, workflow and governed action.

  1. Review cash & liquidity
  2. Understand forecast variance
  3. Prioritise exceptions
  4. Prepare finance work
  5. Review approvals
  6. Reconcile outcomes
Explore this path
Investment & Markets

Build an evidence-backed thematic portfolio

Take an investment concept through research, construction, risk, review and controlled execution.

  1. Define concept
  2. Build universe
  3. Research evidence
  4. Construct portfolio
  5. Assess risk
  6. Govern approved action
Explore this path
Developers & Fintechs

Build a governed treasury workflow

Compose financial data, AI, workflow and Financial Actions without giving an application unbounded financial authority.

  1. Create sandbox app
  2. Call FinanceGPT APIs
  3. Compose workflow
  4. Add human review
  5. Propose Financial Action
  6. Observe evidence
Explore this path
Enterprise Governance

Approve a new AI workflow for production

Review provider, model, workflow and financial-authority impact before production use.

  1. Review change
  2. Inspect evidence
  3. Check permissions
  4. Assess financial impact
  5. Approve or decline
  6. Monitor production state
Explore this path
FINANCE TEAMS

Understand financial position, plan forward and manage the work that needs attention.

Use financial statement analysis, cash and liquidity views, forecasts, budgets, variance analysis, accounting workflows, receivables, payables and Financial Actions without losing the evidence behind the decision.

Balance Sheet Analysis
Cash Flow Analysis
Credit Analysis
Financial Forecasting
Financial Planning
Liquidity Analysis
Profit and Loss Analysis
Scenario Analysis
Treasury Management
Accounts Receivable
Accounts Payable
Financial Reporting
Valuation Analysis
Reconciliation
Management Reporting
Financial Actions
INVESTMENT & MARKETS

From investment concept to evidence-backed portfolio decision.

Research companies and themes, build investable universes, construct portfolios, evaluate risk and derivatives, explore generative scenarios and move approved investment decisions into controlled execution and reconciliation.

Concept2UniverseDynamic Industry OntologyTheme WatchPortfolio ConstructionInstitutional RiskInvestment Book
ObservedMarket and provider evidence

Source, as-of time and freshness remain visible for observed financial and market information.

DerivedQuantitative analysis

Portfolio construction, factors, risk and valuation remain linked to explicit methods and inputs.

FinanceGPT SyntheticCounterfactual research

LQM-generated synthetic options and generative market scenarios remain distinct from observed data. Execution eligible: NO.

AI & QUANTITATIVE INTELLIGENCE

Build intelligence for the quantitative world, then make it accessible through language.

FinanceGPT does not ask a language model to approximate every financial answer. It composes deterministic methods, statistical models, LQMs, language reasoning and evidence according to the task.

Quantitative engines

Core calculations remain explicit.

Deterministic, statistical, econometric, forecasting, simulation and optimization methods operate with defined inputs, methods and evidence.

Explore quantitative intelligence
Large Quantitative Models

LQMs model structured quantitative state.

An LQM is defined by the quantitative world it represents: relationships, distributions, regimes, scenarios and other numerical states that can generalize across quantitative tasks.

Explore LQMs
Quantitative Language Models

QLMs connect language to quantitative systems.

A QLM interprets intent, finds evidence, decomposes the request into quantitative tasks, invokes the appropriate systems and explains the evidence-backed result.

Explore QLMs
Governed composition

Model output is not financial authority.

Language generation, quantitative output, workflow approval and Financial Actions remain separate control layers with explicit evidence and permissions.

Review governance
WORKFLOWS, AGENTS & INTEGRATIONS

Automate recurring financial work without hiding control points.

Build workflows that connect financial data, deterministic calculations, FinanceGPT intelligence, integrations and human review. Applications and agents may prepare Financial Actions, but authority remains governed separately.

Workflow StudioAgent SpaceIntegration HubHuman ReviewEvidenceFinancial Action Proposal
TriggerFetch DataDeterministic CalculationFinanceGPT IntelligenceHuman ReviewFinancial Action Proposal
ENTERPRISE GOVERNANCE

Adopt AI and automation without surrendering financial control.

Govern providers, models, workflows, credentials, approvals, limits and financial authority with evidence that helps security, risk, compliance and audit teams understand what happened and who was authorized.

What did the AI know?Data, documents, market observations and contextual evidence used for the conclusion.
What calculated it?Model, version, quantitative method, inputs, assumptions and evaluation lineage.
What supported it?Evidence, sources, provenance and the path from observation to derived conclusion.
What was authorized afterward?Workflow state, human approval, scoped Financial Actions authority, submission and reconciliation.
DEVELOPERS & FINTECHS

Build financial applications on FinanceGPT.

Use APIs, SDKs, financial intelligence, quantitative models, workflows, agents, event tooling and governed Financial Actions without rebuilding the underlying financial infrastructure.

SandboxFinanceGPT API v2
GET /api/v2/ai/models
Authorization: Bearer $FINANCEGPT_API_KEY

Scope: ai:models:read
EVIDENCE & TRUST

Know what is observed, what is calculated, what is synthetic and what was authorized.

FinanceGPT uses consistent information, freshness, action and evidence semantics so users can inspect sources, methods, model context, approvals and SHA-256 evidence where available.

InformationObserved / Derived / Synthetic
FreshnessLive / Fresh / Aging / Stale
Financial ActionPropose / Control / Approve / Authorize / Submit / Reconcile
EvidenceUnsealed / Sealed / Verified
PROGRAMMES, PARTNERS, ACCELERATORS & ECOSYSTEM

FinanceGPT in the global innovation ecosystem.

A selection of programmes, partners, accelerators and institutions across finance, technology and innovation.

FINANCIAL ANALYSIS

Transforming Complex Financial Data into Actionable Insights with AI.

Financial data becomes more useful when source, calculation and interpretation can be reviewed together. FinanceGPT turns complex financial information into analysis, charts, forecasts, research and decision support while preserving the evidence trail.

01Source evidenceStatements, market data, integrations and governed uploads.
02Financial methodsDeterministic calculations, models, scenarios and validations.
03Decision contextFinanceGPT interpretation, reports, workflows, approvals and auditability.
PRICING

Start with the level of FinanceGPT that fits the work.

Explore FinanceGPT free, add professional financial intelligence and workflows, or move into team, business and institutional capabilities as governance, integrations and Financial Actions requirements expand.

QUESTIONS

FinanceGPT Labs, clearly explained.

What is Quantitative Generative AI?

Quantitative Generative AI combines quantitative models, financial data, language reasoning, evidence and governance so people can program and interrogate quantitative systems through natural language without treating language as the numerical source of truth.

What is an LQM?

A Large Quantitative Model is a governed model whose primary domain is structured quantitative state. It can learn or generate relationships, distributions, regimes, scenarios and other numerical representations for quantitative financial tasks.

What is a QLM?

A Quantitative Language Model is the governed composition layer that interprets a request, identifies evidence and quantitative tasks, invokes the appropriate quantitative systems and explains the resulting evidence-backed conclusion.

What are FinanceGPT Financial Actions?

Financial Actions carry approved finance work through policy, controls, human approval, scoped authority, provider submission and reconciliation. Model output can inform an action, but execution authority remains separate.

What is the difference between Observed, Derived and Synthetic information?

Observed information comes from a source or provider. Derived information is calculated from explicit inputs and methods. FinanceGPT Synthetic information is generated for research or scenario use and remains visibly distinct from observed market data.

Can FinanceGPT connect to financial systems?

Yes. FinanceGPT includes governed integrations, APIs and developer tooling for connected financial workflows. Available integrations and execution permissions remain subject to workspace and commercial configuration.

Can FinanceGPT trade or move money?

Yes, through Financial Actions where the relevant commercial capability, connector, policy, approval and scoped execution authority are separately configured. FinanceGPT never treats analysis, AI output or a paid plan as authority to transact.

How much is Professional access?

Professional is $59 per month or $590 per year. Paid subscriptions include FinanceGPT AI Credits, with current usage and plan details shown on Pricing.

QUANTITATIVE GENERATIVE AI

Ask in language. Compute with quantitative systems. Act with governed authority.

Use FinanceGPT to move from evidence and quantitative intelligence to an explainable conclusion, then into workflows and Financial Actions only when the required review and authority are established.