MCP endpoint
75+ schema-validated tools. Any MCP-compatible agent connects immediately — Claude, GPT, n8n, or your own. Same approval gates as a human.
Ledger Layer is the lease and revenue accounting infrastructure AI agents connect to — and that humans govern. Three endpoints. One deterministic engine. Full audit trail. Run IFRS 16 / ASC 842 leases and IFRS 15 / ASC 606 revenue contracts on the same engine. Connect your agent via MCP, upload from Excel, or integrate your ERP — your accounting data becomes structured, trusted, and queryable. Same audit controls. Zero spreadsheet risk.
The average lease and revenue accounting system costs $25,000/year — per module. Ledger Layer bundles both, starting at $49/month.
Start with an Excel upload → or connect via MCP in under 5 minutes →
Two ways in
Upload your Excel, CSV, or PDF
AI extracts lease and revenue contract terms. You review and confirm. Engine runs IFRS 16 / ASC 842 and IFRS 15 / ASC 606 side by side. Audit-ready output in minutes — no implementation project.
Get startedConnect Claude, GPT, or any MCP client
Query your accounting data in under 5 minutes. Generate an API token, point your MCP client at Ledger Layer, and your agent has structured, role-gated access to the engine.
View MCP setupBoth paths use the same deterministic engine, the same audit trail, and the same approval gates.
Pricing
Same deterministic engine, every tier. Both lease and revenue modules included from day one. No per-seat pricing. No per-agent pricing. No implementation project. You pay for how many legal entities you run — not how many users you add. Professional automatically receives every new module added to the roadmap, free.
Most teams spend 30+ person-days per year on close mechanics. The first restatement costs more than a decade of Ledger Layer Professional.
Feature comparison
| Feature | Starter $49/mo | Professional $499/mo | Enterprise Custom |
|---|---|---|---|
| Core engine | |||
| Deterministic engine | ✓ | ✓ | ✓ |
| Hash-verified output | ✓ | ✓ | ✓ |
| PV tie-out $0.01 | ✓ | ✓ | ✓ |
| Standards | |||
| IFRS 16 + ASC 842 (lease accounting) | ✓ | ✓ | ✓ |
| IFRS 15 + ASC 606 (revenue recognition) | ✓ | ✓ | ✓ |
| Every future module included free (IFRS 9, ASC 326 / CECL, hedge, IFRS 17, share-based payment, taxes, business combinations, …) | — | ✓ | ✓ |
| Scale | |||
| Legal entities | 1 | Up to 50 | Unlimited |
| Leases | Up to 50 | Unlimited | Unlimited |
| Revenue contracts | Up to 50 | Unlimited | Unlimited |
| API rate limit | 100 req/min | 500 req/min | Custom |
| AI & agents | |||
| Inbound: Excel, CSV, PDF, ERP files | ✓ | ✓ | ✓ |
| REST API (inbound + outbound) | ✓ | ✓ | ✓ |
| MCP agent interface (75+ tools for Claude · GPT · Cursor · n8n) | — | ✓ | ✓ |
| Outbound webhooks (journal entries + close events) | — | ✓ | ✓ |
| iPaaS routing (Alteryx · Anaplan · Workato · Zapier · Airflow) | — | ✓ | ✓ |
| Governance | |||
| Preparer + Reviewer roles | ✓ | ✓ | ✓ |
| Full RBAC (Owner / Admin / Preparer / Reviewer) | ✓ | ✓ | ✓ |
| Monthly close automation (idempotent, per-entity) | — | ✓ | ✓ |
| Export | |||
| Journal entry export (CSV / XLSX / JSON) | ✓ | ✓ | ✓ |
| ERP-ready export schema (SAP · Oracle · NetSuite · Dynamics 365 format) | — | ✓ | ✓ |
| Lease disclosure packs (IFRS 16 para 53–58 · ASC 842-20-50) | ✓ | ✓ | ✓ |
| Revenue disclosure packs (IFRS 15 para 110–128 · ASC 606-10-50) | ✓ | ✓ | ✓ |
| Deployment | |||
| Cloud (SaaS) | ✓ | ✓ | ✓ |
| Self-hosted / Docker (Mode 3) | — | — | ✓ |
| SSO / SAML / SCIM | — | — | ✓ |
| Support | |||
| Support level | Priority | Dedicated + SLA | |
| Get started | Get started | Talk to the team | |
Upload your Excel or connect your agent. Audit-ready output in minutes — no implementation project.
AI can read your data. It cannot produce audit-grade accounting on its own.
Ledger Layer enforces the rules in between. Making accounting data usable for both.
The architecture
Three layers. Three API endpoints. One immutable data contract. AI extraction → deterministic engine → human approval. The architecture that makes accounting data trustworthy for AI — without compromising the controls auditors require.
Reads your Excel, PDF, or plain-language description. Extracts and normalises relevant data. Proposes data for your review. Never computes a single accounting number.
proposals onlyAI reads structure — not your numbers. Only structural metadata is passed to AI models. No financial data, no cell values, no PII. All accounting computation runs in the deterministic engine.
AI proposals are never authoritative. They require engine validation and human approval before any value is recorded.
Version-pinned IFRS and US GAAP logic. Accounting calculations, schedules, Journal entries, and Disclosures — computed deterministically. Same inputs always produce the same hash-verified output.
Trusted math · hash-verifiedThis is the only layer permitted to compute accounting output.
You review the journal entry. You approve it. Once approved, it is immutable — no delete, no edit, reversal only. Nothing exports to your ERP until this step is complete. This is where your company's sign-off authority lives — not with the software.
Approval-gated · immutableAI can propose. Only humans can approve.
The problem
Excel is not a system. It's a file. AI tools can't query it safely. Manual pipelines break under audit. The data your AI needs is locked in a format it can't trust.
Not another SaaS app. Accounting infrastructure.
Supported standards
Every quarter, your team spends 3–5 days per entity reconciling lease and revenue workbooks, rebuilding disclosures, and chasing versions. For a 10-entity group, that is 30–50 person-days a year on close mechanics. On Ledger Layer, a close takes hours — across leases and revenue contracts.
Move off Excel. Get hash-verified output. Keep the controls auditors require — no implementation project.
A — Agent & API surface
75+ schema-validated tools. Any MCP-compatible agent connects immediately — Claude, GPT, n8n, or your own. Same approval gates as a human.
Upload Excel, CSV, or PDF. AI reads the workbook structure and extracts lease and contract terms. You confirm. Engine runs. 200 leases in under 60 seconds.
Full OpenAPI 3.1 spec. Every engine operation is API-addressable — lease runs, journal approvals, disclosures, structured journal export. Webhooks for event-driven automation.
Raw lease and contract data structured into a clean, queryable schema. The same schema your AI agent, ERP, and CRM all read from — consistently.
Approved journal entries in structured CSV, XLSX, and JSON — ready to feed into SAP, Oracle, NetSuite, or any iPaaS (Alteryx, n8n, Workato, Zapier, Airflow) via the tool of your choice. Full posting_reference lifecycle.
Owner, Admin, Approver, Preparer, Reviewer. Role-gated at the API layer. Same permissions for agents and humans. Complete tenant isolation on every call.
B — Deterministic compute
IFRS 16, ASC 842, IFRS 15, ASC 606 — version-pinned. Present value, amortisation, revenue recognition. Hash-verified on every run. Same inputs always produce the same output.
Role-gated approval. Approved JEs are immutable — reversal only. Full audit trail on every write: actor, timestamp, request ID.
IFRS 16 para 53–58 and ASC 842-20-50 compliant packs, auto-generated. ROU movements, maturity analysis, weighted average IBR. PV tie-out validated to $0.01.
IBR rates by currency × term × effective date. Every rate traces to a persisted source row. Full FX traceability across unlimited currencies.
Close your entire portfolio in one operation. Idempotent, concurrency-safe, re-runnable. Every close produces a complete, reviewable audit record.
Docker image, your infrastructure, your local AI provider. The deterministic engine runs identically in all three deployment modes. No data leaves your network.
Use cases
Your AI assistant can query every lease, every schedule, every modification — on data the engine has made trustworthy. Finance teams that were drowning in spreadsheets run AI-powered portfolio reviews in minutes.
Apply the five-step model across your contract portfolio without manual spreadsheet maintenance. AI can draft disclosures, flag contract changes, and surface exceptions — on engine-verified data.
Real-time view across all leases and contracts — by entity, currency, standard, or status. Query your portfolio in plain language through your AI assistant. Ledger Layer provides the structured, trusted data layer it needs to answer accurately.
Auto-generate your financial statement disclosure pack every period. Because Ledger Layer maintains a clean, structured data layer, your AI can assist in drafting, reviewing, and formatting disclosures — from data it can trust.
Ledger Layer is a category of one: the infrastructure layer that makes accounting data usable by AI — without removing the controls auditors require. No other tool does both.
| Capability | Ledger Layer | Excel / Sheets | ChatGPT / Claude | Lease SaaS |
|---|---|---|---|---|
AI-ready accounting data Structured, trusted, queryable by AI AI without a control layer cannot be trusted in accounting. | ✓ The category definition row. | ✕ Unstructured. AI can't use it safely. | ~ AI interprets, but doesn't verify. | ✕ Closed data. No AI interface. |
AI-safe accounting execution Deterministic engine + approval layer | ✓ Enforced via deterministic engine + approval gate | ✕ No enforcement | ✕ No control layer | ~ Partial, workflow-dependent |
Deterministic calculations Same inputs → same outputs | ✓ Version-pinned, hash-verified | ~ Manual. Silent formula drift. | ✕ AI computes. Not audit-grade. | ✓ Varies by vendor |
All four standards IFRS 16, ASC 842, IFRS 15, ASC 606 | ✓ All four, one engine | ✕ Build each manually | ~ Approximate only | ✕ Lease standards only |
Approval gate + immutability Nothing posts without sign-off | ✓ DB-enforced. JEs immutable. | ✕ Anyone can change any cell. | ✕ None. | ~ Workflow-dependent |
Full audit trail Actor, timestamp, request ID on every write | ✓ Every write logged | ✕ Change tracking optional | ✕ | ~ Partial |
AI agent interface (MCP) Plug into your AI assistant or workflow | ✓ 75+ schema-validated tools | ✕ | ✕ | ✕ |
Disclosure packs IFRS 16 para 53–58 / ASC 842-20-50 | ✓ Auto-generated, $0.01 tie-out | ✕ Manual. Transcription risk. | ~ Draft only | ~ Varies |
Self-hosted deployment On-prem or private cloud | ✓ Docker / Mode 3 | ✓ Local file | ✕ | ✕ SaaS only |
ERP / downstream integration Route approved JEs into SAP, Oracle, NetSuite, or any stack | ✓ Structured export (CSV/XLSX/JSON) + MCP + outbound webhooks — drive any ERP via Alteryx, n8n, Workato, Zapier, or your own middleware | ~ Manual or custom macro | ✕ | ~ Varies |
Ledger Layer is not another app to integrate. It is the protocol surface your accounting data needs to become usable — by AI, by your ERP, by your reporting stack. Three connection types. One deterministic layer.
One MCP connection replaces the ETL + AI wrapper + ERP mapping + disclosure tool stack most teams are currently maintaining manually.
Drive Ledger Layer from any MCP-compatible agent or iPaaS — and route journal entries, engine runs, and close events into SAP, Oracle, NetSuite, Salesforce, and any downstream via your tool of choice
Right-of-use assets, lease liabilities, modifications, disclosure requirements, exemptions.
Read guide →Operating and finance lease classification, transition methods, lessee and lessor accounting.
Read guide →Five-step revenue model, performance obligations, variable consideration, contract costs.
Read guide →US GAAP revenue recognition, principal vs agent, licensing, contract modifications.
Read guide →Full OpenAPI 3.1 documentation. Pagination, streaming, file upload, webhooks, error codes.
View docs →75+ schema-validated tools for Claude, GPT, and custom agents. Full tool catalog and examples.
View tools →Standards implementation pipeline
FAQ
Standards implementation guides, developer docs, and head-to-head comparisons below — or jump straight in.
Standards guides & comparisons
Upload your Excel or connect your agent. Ledger Layer structures lease and revenue contract data, runs the deterministic engine, and emits structured journal exports and webhook events — plug into any ERP, iPaaS, or agent stack with the audit controls intact.
Or talk to the team about enterprise deployment.