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?
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.
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 · LQMs02 · 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 synthesis03 · 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 TeamsInvestment & 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 & MarketsDevelopers & Fintechs
Build financial applications with FinanceGPT data, intelligence, workflows and governed Financial Actions.
Developers, fintech teams, solution architects and platform engineers
Explore the Developer PlatformEnterprise 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 GovernanceCONNECTED 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.
InterpretDefine resilience, valuation and earnings-quality conditions.
EvidenceResolve financial statements, market observations and historical context.
ComputeCalculate balance-sheet resilience, normalized valuation and quality measures.
GenerateWhere appropriate, governed LQMs generate conditional quantitative states or scenarios.
ExplainThe QLM composes an evidence-backed conclusion with model and source context.
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
Prepare with evidence
Translate treasury needs, collection intent, investment decisions or other finance work into a structured proposal with source and calculation context.
Apply controls and approval
Evaluate policy, limits, risk and required human approvals without treating AI recommendations as transaction authority.
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.
- Review cash & liquidity
- Understand forecast variance
- Prioritise exceptions
- Prepare finance work
- Review approvals
- Reconcile outcomes
Investment & Markets
Build an evidence-backed thematic portfolio
Take an investment concept through research, construction, risk, review and controlled execution.
- Define concept
- Build universe
- Research evidence
- Construct portfolio
- Assess risk
- Govern approved action
Developers & Fintechs
Build a governed treasury workflow
Compose financial data, AI, workflow and Financial Actions without giving an application unbounded financial authority.
- Create sandbox app
- Call FinanceGPT APIs
- Compose workflow
- Add human review
- Propose Financial Action
- Observe evidence
Enterprise Governance
Approve a new AI workflow for production
Review provider, model, workflow and financial-authority impact before production use.
- Review change
- Inspect evidence
- Check permissions
- Assess financial impact
- Approve or decline
- Monitor production state
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
Source, as-of time and freshness remain visible for observed financial and market information.
Portfolio construction, factors, risk and valuation remain linked to explicit methods and inputs.
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 intelligenceLarge 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 LQMsQuantitative 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 QLMsGoverned 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 governanceWORKFLOWS, 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.
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.
GET /api/v2/ai/models
Authorization: Bearer $FINANCEGPT_API_KEY
Scope: ai:models:readEVIDENCE & 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.
Trust CenterSecurity, governance, assurance, data handling and platform controls.
Enterprise evidenceAI routing, financial governance, execution, reconciliation and assurance evidence.
Evidence-grounded financial AIResearch on source evidence, computation, model context and governed decision support.
LQM specificationPublic quantitative-model definitions, evaluation and evidence architecture.
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.
RESEARCH, TOOLS & INSIGHTS
Go deeper into financial intelligence, quantitative finance and governance.
Explore original research, product comparisons and practical tools spanning Large Quantitative Models, generative AI, evidence, governance and financial analysis.
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.