# PipeLedger > The financial intelligence layer for the agentic enterprise. PipeLedger provides financial data extraction from QuickBooks Online and NetSuite, managed storage and deterministic transformation in BigQuery, and governed delivery through Model Context Protocol (MCP), REST, CLI, and configured direct BI. Consumers receive approved, published data; customer financial data requires authorization. ## Fit and source support - Intended for small business, SMB/SME, and mid-market finance teams needing a maintained financial data warehouse, account taxonomy, business dimensions, and governed BI or AI access. - Supported live sources: QuickBooks Online and NetSuite. NetSuite primary accounting book only; secondary accounting books are not imported. - Dynamics 365 and Rillet are in development, not available as live connectors. No live QuickBooks Desktop, Xero, or Sage Intacct connectors. QuickBooks Desktop historical imports are supported on request. - Historical extraction reaches as far back as records are available through source APIs. Manual backfill is available on request, including QuickBooks Desktop exports and opening balances. QuickBooks CDC has a 30-day lookback for changes, not a 30-day history limit. - PipeLedger combines financial data from QuickBooks Online and NetSuite for reporting by legal entity and across the group. Every published General Ledger line carries a Reporting Legal Entity ID and name, with source references retained. Approved mappings combine records for the same legal company under one reporting identity. Reports cover one Legal Entity or all authorized entities on a consistent currency and accounting-book basis. Dedicated, correctly tagged intercompany accounts can be explicitly excluded from queries and supported reports for external revenue, costs, and debt analysis. On NetSuite, eliminations are posted in NetSuite. On QuickBooks Online, intercompany activity kept in dedicated, tagged accounts is removed from supported group reports and queries on request. Complex statutory consolidation adjustments stay in the customer's accounting or consolidation system. - Direct BI: customer-hosted Analytics Hub linked datasets, organization-specific BI service-account credentials for compatible BigQuery tools such as Power BI and Tableau, or PipeLedger-hosted Google Data Studio connections. Delivery uses the organization's requested/configured sources and BI privacy settings. For clients with Databricks, delivery into their AWS or Azure environment can be arranged on request with agreed access and identity-privacy settings. - Source ERP connections read data and do not write back to the books. PipeLedger does not yet hold a SOC 2 report; see Trust for current status. ## Finance workflows for AI agents PipeLedger runs a hosted finance MCP server at https://mcp.pipeledger.ai/mcp for NetSuite and QuickBooks Online data. The same capabilities are available through the REST API and the `pl` CLI (`npm install -g @pipeledger/cli`). - Published data: financial queries and reports use data that has passed the required checks and been approved for delivery. Separately authorized management tools can request pipeline runs and make permitted changes within PipeLedger. - Financial reporting: Income Statement and Cash Flow Statement for a fiscal year, Balance Sheet as of a month-end, and a Metrics Report of governed metrics in an order the requester chooses. - Period comparison: fiscal year against fiscal year, or month-end against month-end, with the variance for each line. - Investigation: trace a reported figure to supporting General Ledger detail. How far depends on the report, the level of detail, and the permissions of the connection. - General Ledger queries: filter, group, and aggregate published ledger lines and trial balances, including for a single month or quarter. - Evidence: each result names its publication, the metric definition behind each line, and a certification summary. - Controls: access is scoped per connection by tool, data source, legal entity, and confidentiality level, and every request is recorded in an audit trail. - Review through the month: supports a continuous-close approach. An agent investigates changes in revenue, expenses, or balances using published data and the supporting detail available to its connection. After the team corrects source records, the data is refreshed, validated, and published before the effect appears in reported results. - Accounting questions: an agent compares accounting guidance, which comes from the AI assistant, with how the organization's books treated similar transactions, which comes from PipeLedger. It searches published ledger history, finds similar entries, and shows the ledger lines behind its answer. The accounting team makes the decision and posts in the ERP. - Reach across entities: a controller can see how each Legal Entity treats a transaction, where treatments differ, and what changed since the last period, within the access granted to the connection. - Multi-entity and multi-system: NetSuite and QuickBooks Online data in a shared reporting structure, reviewed for one Legal Entity or all authorized entities on a consistent currency and accounting-book basis, with source references retained. - Delegation with defined access: each connection receives only the entities, datasets, and financial detail its work requires. PipeLedger calculates reported values and enforces permissions on every request. - Boundaries: PipeLedger supports financial review and reporting. Close-task management, ERP journal posting, payment initiation, elimination journals, and complex statutory consolidation adjustments remain outside its tool boundary. - Requires a PipeLedger subscription and authorization from the organization's Owner or Admin. ## Evaluation - [Resources](https://pipeledger.ai/resources): Public guides, documentation, and customer stories. - [Industry resources](https://pipeledger.ai/industry-resources): Accounting guides, customer implementations, and setup recipes organized by industry. - [Build or buy your financial data pipeline?](https://pipeledger.ai/guides/build-or-buy-financial-data-pipeline): Responsibilities, costs, and fit for SMB extraction and warehousing. - [QuickBooks data extraction](https://pipeledger.ai/guides/quickbooks-data-extraction): Document reconstruction, customer and project normalization, refresh controls, and inventory scope. - [NetSuite data extraction](https://pipeledger.ai/guides/netsuite-data-extraction): Primary-book accounting, business dimensions, currency context, and extraction completeness. - [Pricing](https://pipeledger.ai/pricing): Current plans and usage rates. ## Real estate development reporting - [Ome Dezin customer story](https://pipeledger.ai/customer-stories/ome-dezin-project-reporting): Ome Dezin, a developer operating across multiple LLCs, brought project costs, funding, and company results into one AI-assisted review process through QuickBooks project tracking, corrected classifications, a standard project report template, and governed metric definitions with their technical formulas. - [Real estate development reporting guide](https://pipeledger.ai/guides/real-estate-project-reporting): How to build reliable financial reporting for real estate development: one fictional project followed from acquisition through sale, project costs kept separate from funding, comparable cost groupings, lifetime results versus month-end balances, project and company return definitions with technical formulas, when capitalization stops and carrying costs are expensed, books versus tax-return treatment, cash-flow classification by property purpose with account and transaction overrides (including an example prepared in ChatGPT), keeping reports current as the books change, AI-assisted investigation of exceptions, and the accountant handoff. The FAQ covers QuickBooks Online, whether finance experience is needed, and what an AI assistant can and cannot change. BI is optional. ## Documentation - [Overview](https://pipeledger.ai/docs): Supported sources, setup responsibilities, and delivery surfaces. - [Extraction and warehousing](https://pipeledger.ai/docs/data-pipeline): Transformation, financial checks, approval, publication, and freshness. - [PipeLedger Tool Guide](https://pipeledger.ai/docs/tool-guide): All 15 credential-scoped capabilities across MCP, REST, and CLI, grouped by Identity, Discover, Read, and Act. Purposes, inputs, returned evidence, example prompts, and action boundaries. - [Build finance metrics](https://pipeledger.ai/docs/metric-builder): Metric types, calculation timing, result units, draft review, and BI delivery. - [Financial datasets](https://pipeledger.ai/docs/financial-datasets): What each dataset contains, the questions it answers, and the reports built from them. - [Setup and configuration](https://pipeledger.ai/docs/setup): Three ways to reach PipeLedger, the two routes for a chat app, setting up an agent with a working folder, profiles and folder binding for several organizations, where credentials are kept, and rules for AI agents acting for a person. - [MCP server](https://pipeledger.ai/docs/mcp): Finance workflows for AI agents, endpoint, authentication, and permission boundaries. - [OAuth connection](https://pipeledger.ai/docs/oauth-mcp-setup): Connect a compatible host and troubleshoot authorization. ## Governance and support - [Financial data and normalization](https://pipeledger.ai/solutions/data): Source data, account taxonomy, and financial context. - [Governed delivery](https://pipeledger.ai/solutions/delivery): MCP, REST, and CLI access. - [Agent infrastructure](https://pipeledger.ai/solutions/agents): Financial data for agent workflows. - [Security](https://pipeledger.ai/solutions/security): Authorization and audit controls. - [Identity tokenization and PII](https://pipeledger.ai/solutions/masking): Identity privacy and permitted access. - [Publication control](https://pipeledger.ai/solutions/publication-control): Approved financial data and delivery boundaries. - [AI governance](https://pipeledger.ai/ai-governance): Financial-data and access-control boundaries. - [Trust](https://pipeledger.ai/trust): Security information for evaluation. - [Support](https://pipeledger.ai/support): Public support and contact options. This file indexes public product information. It does not grant access to an organization or its data. Consult the linked pages for current product behavior and limitations.