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Trusted Financial Intelligence for AI

Turn fragmented AI spend into trusted financial intelligence
for finance leaders.

AI billing is scattered across vendors, cloud platforms, and teams. LedgerShift brings it together into one trusted financial view.

Spend Estimator

Configure your AI stack

4
1 vendor8 vendors
OpenAIAnthropicAWS BedrockAzure OpenAI
$12k
$1k / mo$100k / mo
18

illustrative

4

Vendors Normalized

estimated

~12

Hours Saved / Mo

estimated

78%

Visibility Score

No credit card · 4 vendors · $12k/mo · early access

Live Preview

AI Economics Ledger

normalizing
VendorCategoryAmountCost CenterStatus
F

FOCUS 1.4-aligned categorization

Every line item normalized to the FinOps Open Cost & Usage Specification

Spend by vendor — normalized

Immutable audit trail✓ Every entry locked
CFOs & Finance Leaders/FP&A & Controllers/AI-Native SaaS/Board-Ready Reporting/AI Margin Intelligence/CFOs & Finance Leaders/FP&A & Controllers/AI-Native SaaS/Board-Ready Reporting/AI Margin Intelligence/CFOs & Finance Leaders/FP&A & Controllers/AI-Native SaaS/Board-Ready Reporting/AI Margin Intelligence/CFOs & Finance Leaders/FP&A & Controllers/AI-Native SaaS/Board-Ready Reporting/AI Margin Intelligence/CFOs & Finance Leaders/FP&A & Controllers/AI-Native SaaS/Board-Ready Reporting/AI Margin Intelligence/CFOs & Finance Leaders/FP&A & Controllers/AI-Native SaaS/Board-Ready Reporting/AI Margin Intelligence/

The Problem

Finance has visibility into invoices.
It doesn't have visibility into AI economics.

Every finance system records AI vendor invoices. What those systems cannot do is classify AI costs, attribute them to business context, or produce the financial reporting executives actually need.

The questions finance cannot answer today:

  • Which business units and products are driving AI spend?
  • How do AI costs map to revenue, margin, and customers?
  • What belongs in Cost of Revenue versus Operating Expense?
  • How do we report AI costs to the executive team and board?
  • What is AI actually doing to our unit economics?

The data exists. The financial intelligence does not.

AI vendor invoices sit in your ERP unclassified, unattributed, and unreported. Finance cannot build trusted financial data for AI without a structured process to classify costs, map them to business context, and surface them in executive reporting.

That is the financial foundation LedgerShift builds.

The Product

From raw vendor data to trusted financial intelligence.

Five capabilities that build the financial foundation finance needs before any strategic AI decision can be made with confidence.

The question

“How do we get AI vendor invoices into a structured format?”

How LedgerShift helps

Upload AI vendor invoices directly into LedgerShift. Every line item is normalized to a consistent schema — vendor, cost type, and period — so finance has a clean, structured record of AI spend.

Invoice upload · Data normalization · Vendor consolidation

The question

“How do we classify AI costs for financial reporting?”

How LedgerShift helps

LedgerShift classifies AI costs by type — inference, embeddings, fine-tuning, storage — using FOCUS 1.4-aligned categorization. Finance gets a structured cost taxonomy that supports accurate financial reporting.

Cost classification · FOCUS 1.4 alignment · Taxonomy structure

The question

“How do we attribute AI costs to the business?”

How LedgerShift helps

Business mapping connects classified AI costs to the products, teams, and cost centers that generate them. Finance can understand AI spend in business context — not just as a vendor line item.

Business mapping · Cost attribution · Organizational context

The question

“What does the executive team need to see?”

How LedgerShift helps

The Executive Dashboard surfaces classified, attributed AI costs in a format built for finance leaders. Spend by vendor, by category, by business unit — organized for financial review, not infrastructure monitoring.

Executive dashboard · Financial visibility · Spend reporting

The question

“How do we communicate AI financials to leadership?”

How LedgerShift helps

The Executive Summary translates structured AI financial data into a narrative format suitable for CFO review, board reporting, and investor conversations — sourced from verified classifications and attributions.

Executive summary · Board reporting · Auditable narrative
Every classification and attribution is traceable. Trusted financial data, not a black box.

The Reasoning Engine

Every answer is traceable.

Every calculation is auditable. No black box.

  1. Connect

    Connect your AI vendors

    Link your billing APIs or drop in CSVs. LedgerShift normalizes every vendor to a single schema on ingest — no manual mapping required.

    OpenAI APIsupported
    AWS Bedrocksupported
    Azure OpenAIsupported
    Anthropicsupported
  2. Ask

    Ask the question that matters

    Type the question your CFO or board is asking. The reasoning engine works against your actual ledger data — not a generic model.

    “Why did gross margin drop 4 points last quarter?”
    Reasoning against verified ledger data...
  3. Model

    Trace the reasoning

    Every answer is decomposed into its components — which costs moved, by how much, and why. No black box. Every step is auditable.

    AI COGS
    +$82K+34%
    Inference (Copilot)
    +$61K+58%
    Gross Margin
    61.2%−4.1pp
  4. Report

    Report with confidence

    Generate board-ready narratives, CFO summaries, and investor-grade AI unit economics — all sourced from the same verified calculations.

    Executive Summary

    Gross margin declined 4.1pp driven by a 58% increase in Copilot inference costs. AI COGS grew $82K quarter-over-quarter. Recommended action: review inference model selection for Copilot tier 1 users.

    Traceable to verified calculation
Start Here

AI Financial
Intelligence Review

Understand how AI is really impacting your margins — before it impacts your growth.

LedgerShift helps AI-native SaaS companies uncover hidden AI costs, improve margin visibility, and build the financial foundation to scale AI profitably.

What you'll gain

✓

Know your true AI delivery costs

See where AI costs live across the business, and what belongs in COGS versus opex.

✓

See what's driving margin compression

Infrastructure, inference, platform, and support costs — ranked by impact on your margins.

✓

Leave with a roadmap

A practical plan to improve cost visibility, attribution, and margin performance.

Request a Review →See the full diagnostic →

Every review includes

✓AI Cost Inventory
✓COGS Waterfall
✓Gross Margin Review
✓Executive Findings Report

Designed for

→AI-native SaaS companies with growing inference or infrastructure costs
→Finance leaders who need better visibility into AI delivery economics
→Teams preparing for board reporting or investor diligence on AI unit economics
◎

Low commitment. High signal.

A structured engagement — not a sales call. You leave with a real deliverable regardless of whether you become a LedgerShift customer.

Built for finance teams

Financial intelligence for AI. Built for finance.

For CFOs & Controllers

Build the trusted financial data your team needs for AI.

AI vendor invoices are already in your ERP. What's missing is the classification, attribution, and reporting structure that turns raw spend into financial intelligence finance can stand behind.

  • Classify AI costs by type — inference, embeddings, fine-tuning, storage
  • Map AI spend to business units, products, and cost centers
  • Understand AI's contribution to cost structure before changing accounting policy
  • Produce executive-ready reporting from verified, auditable financial data
Request access →
For FP&A & Finance Leaders

Give leadership the AI financial visibility they're asking for.

Finance teams are being asked to explain AI spend without the tools to do it. LedgerShift provides the structured financial data and executive reporting that makes those conversations possible.

  • Structured AI cost data organized for financial review — not infrastructure monitoring
  • Business mapping that connects AI spend to the teams and products that generate it
  • Executive dashboard built for finance leaders, not DevOps or platform engineering
  • Executive summaries ready for CFO review, board reporting, and leadership conversations
Request access →

The Road Ahead

Building the financial intelligence platform for AI.

LedgerShift starts with trusted financial data — classification, business mapping, and executive reporting. From that foundation, we are building toward ROI measurement, benchmarking, and investment intelligence. Those capabilities require the financial data infrastructure we are building today.

Today: Trusted financial data for AI — classification, attribution, and executive reporting.

Roadmap: ROI measurement, customer benchmarking, and investment intelligence — built on the financial foundation we are establishing now.

Early Access

Finance teams navigating
the economics of AI.

We are working with a small group of CFOs, controllers, and finance leaders to build the financial intelligence layer for AI. If your team needs trusted financial data for AI, we'd like to hear from you.

No credit card. We'll follow up personally within 1–2 business days.

Built on SupabaseFOCUS 1.4-aligned categorizationYour data is never used for training