Knowledge Engine for Finance

Get to one defensible view of performance faster.

Connect ERP, billing, CRM, banking, and operating data to speed reconciliation, explain variance, and support better decisions.

KEP

Monthly forecast review

Explain the largest forecast variances this month and prepare the executive summary.

I connected the forecast, actuals, bookings, billing, headcount, contracts, and department commentary. I’m preparing the variance brief now.

Monthly forecast variance briefReport

58%

lower token cost

when using Knowledge Engine

2x

more tasks

vs. frontier models

32%

more accurate with open source

vs frontier model

19 of 34

tacit-knowledge facts captured

vs. RAG’s 1

Source: “Knowledge Engine Platform for Long-Horizon Professional Agents” and “Context Graphs for Recovering Tacit Organizational Knowledge”, Accrete AI, August 2026.

The numbers only become useful when Finance can explain them.

Bookings, revenue, billing, cash, spend, headcount, and operating drivers live in different systems and close on different schedules. Finance teams reconcile the records, chase explanations, and rebuild reporting before they can advise the business.

Finance cognitive fabric

Connect the context behind the work.

Agents learn the language of the work, create the data flows that connect its systems, and build a living context graph for each request.

Agents learn your language

They learn your teams’ terms, shorthand, and ways of working, then create a shared understanding of what everything means.

Agents connect your systems

They create the data flows that bring the right information together for each task, without manual setup for every source.

Agents build the context graph

They connect people, records, decisions, and outcomes while preserving a clear path back to the source.

From domain language and source data to a context graphThe context model resolves jargon, synonyms, abbreviations, and intent into shared entities and relationships. Source mappings connect those concepts to tables and keys while agentic data pipelines prepare durable data. The resulting context graph can be virtualized over its sources or materialized.NATURAL-LANGUAGE REQUEST“What drove thismonth’s variance?”CONTEXT MODELDomain languageJARGON · SYNONYMS · INTENTACT→booked resultvar.→plan gapintent: explain varianceCanonical modelENTITIES · RELATIONSHIPSResultForecastDriverCOMPARESEXPLAINSSemantic bindingsCONCEPT → SOURCE DATAResult→NetSuiteForecast→SalesforceDriver→BigQuerytables · columns · keysAGENTIC DATA PIPELINESCONTEXT GRAPHNetSuiteSalesforceBigQueryActualsForecastsDriversJOINVariance contextEMEAREGIONQ2 planPLAN-$1.2MVARIANCEN. ShahOWNERVIRTUALIZEDquery sources in placeMATERIALIZEDpersist selected subgraphs
The context model interprets a domain’s vocabulary, synonyms, abbreviations, and intents, then resolves natural-language requests to shared entities and relationships. Source mappings connect those concepts to tables, columns, keys, dialects, and execution integrations. KEP can query the resulting context graph virtually over source data or materialize selected graph data.

Connected systems

Explore 1,000+ integrations →
  • NetSuite
  • QuickBooks
  • Stripe
  • Salesforce
  • Google Workspace
  • Microsoft 365

Workflows

Change the work, not just the interface.

01

Support close and reconciliation

Bring together ledger, billing, CRM, bank, contract, and operating records; identify exceptions; and prepare a reviewable reconciliation trail.

02

Explain forecast and variance

Compare plans, actuals, operational drivers, and owner commentary to surface material changes, open assumptions, and proposed follow-up.

03

Produce scenarios and reporting

Refresh leadership and board reporting, then model hiring, pricing, investment, or timing scenarios from explicit, reviewable assumptions.

One end-to-end example

From disconnected records to a reviewed forecast explanation.

  1. 01

    Connect

    Gather actuals, forecast, bookings, billing, cash, contracts, headcount, spend, operating metrics, and owner commentary.

  2. 02

    Analyze

    Reconcile definitions, trace material variances to source records and business drivers, and identify missing or conflicting evidence.

  3. 03

    Deliver

    Create the variance brief, exception table, updated scenario, executive summary, and review checklist.

  4. 04

    Control

    Keep journal entries, payments, forecast publication, and other consequential financial actions behind the organization’s approval process.

What the team gets

Outcomes people can inspect and use.

Reconciliation and exception brief

Matched records, unresolved differences, source evidence, owners, and the proposed resolution path.

Forecast and variance report

Material changes, business drivers, assumptions, confidence boundaries, and required follow-up.

Leadership scenario package

Auditable scenarios and executive-ready reporting produced from the same approved definitions and prepared data.

The Accrete product

Context, work, and control in one path.

The Knowledge Engine connects financial and operational context into reviewable analysis and finished reporting while leaving approvals and system-of-record changes under Finance control.

Review governance →Open the Trust Center →

Start with one workflow

Define the outcome before expanding the system.

Bring the workflow, its information sources, its approval requirements, and the result your team needs. We’ll map a focused first deployment and the path to reuse.

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