LUNARI
Pricing
Tools We Replace
AI
Investor Relations

Finance runs on
14 broken tools.
We are fixing the foundation.

Every mid-market company between $10M and $500M in revenue is running their financial close on a patchwork of disconnected point solutions. AI cannot fix this. AI fails because the data is broken. Lunari is the first platform built to fix the foundation — one data model, one audit trail, one close cycle — so that AI in finance can finally work.

Download Pitch Deck [email protected]
The Problem

A mid-market finance team runs on 8–14 disconnected tools.
None of them talk to each other.

Enterprise tools like BlackLine cost $200K+ per year and require six-month implementations. SMB tools are too shallow. So 200,000 companies with $10M–$500M in revenue are stuck — running their financial close on spreadsheets, manually reconciling exports from a dozen systems, and spending 20–50 hours every month just assembling the data to close the books.

BlackLine$45K/yr
Reconciliation
FloQast$28K/yr
Close checklist
Tipalti$36K/yr
Accounts payable
Expensify$18K/yr
Expense management
Workiva$30K/yr
Reporting & disclosure
LeaseQuery$22K/yr
Lease accounting
NetSuite$20K/yr
ERP / GL
Coupa$15K/yr
Procurement
$207K+
Annual tool spend
Median mid-market company
20–50 hrs
Lost every month
Just assembling data to close
10–14 days
Average close cycle
Industry benchmark
The AI Problem

AI in finance keeps failing.
Not because the models are bad.

Every finance team has tried an AI pilot. Most have failed. The reason is never the model — it is the data. You cannot build intelligent finance on top of 14 disconnected exports. The foundation must be fixed first.

⚡
Fragmented data
8–14 tools with no shared schema. AI cannot reason across disconnected exports.
📅
Stale exports
Month-end CSVs are snapshots of the past. AI trained on them cannot act in real time.
🔗
No transaction context
Without the original transaction record, AI cannot explain why a number is what it is.
📋
No audit trail
AI decisions in finance require an immutable evidence chain. Fragmented stacks cannot provide one.
🏢
No entity awareness
Multi-entity companies need inter-company eliminations. No point solution understands the full structure.
The Lunari Fix
Fix the foundation. Then let AI do what it was built for.

Lunari captures every transaction at creation — not at export. Every journal entry, every approval, every reconciliation match lives in a single structured ledger with full entity context and an immutable audit trail. When AI reasons over Lunari data, it has everything it needs: real-time transactions, full history, entity relationships, and a complete evidence chain. This is not AI features bolted onto a broken stack. This is the stack that makes AI in finance possible for the first time.

Defensibility

Four compounding moats.
Each one stronger than the last.

The unified data model is not just a product advantage — it is the source of four structural moats that compound over time and make Lunari progressively harder to displace.

01Strongest — compounds with time
The Ledger Network Effect
Every transaction that flows through Lunari makes the ledger smarter. Coding rules improve. Anomaly detection sharpens. After 2 years, a customer's Lunari ledger is a trained, company-specific intelligence layer. No competitor can offer a migration path for it.
02Third-party reinforcement
Auditor & Acquirer Lock-In
Every transaction carries an auto-generated evidence chain. Over time, the customer's full financial history lives in Lunari's vault. Auditors who work through one cycle with Lunari's evidence packs advocate for staying. Acquirers in diligence price infrastructure maturity.
03Incumbents can't replicate
Architectural Impossibility
Ramp can't add an AI Controller without a ledger. NetSuite can't add an AI Bookkeeper without rebuilding their transaction layer. The unified data model requires starting from scratch — which incumbents cannot do without breaking their existing customer base.
04Switching cost builds every month
Institutional Configuration Lock-In
Every Head of Finance's close process — approval matrix, coding rules, reconciliation logic, entity structure — gets encoded into Lunari over 6–12 months. That configuration is institutional knowledge. Switching means rebuilding it from scratch.
The Raise

$1M to reach first revenue in 6 months.

Instrument Terms
InstrumentSAFE (Simple Agreement for Future Equity)
Raise amount$1,000,000
Valuation cap$8,000,000
Discount20%
MFN clauseYes
Round typePre-seed / Founding round

This is not a product-market fit raise. This is a founding-round raise to prove the beachhead: that a unified Finance OS can replace BlackLine for a mid-market company at a fraction of the cost, and close the books on Day 1 of the following month. We are going to market with one module — CloseIQ — not all 22.

Use of Proceeds
60%
AI-first engineering team
3 senior engineers + AI tooling
20%
Design partner programme
Onboarding, support, iteration
12%
Infrastructure & tooling
Cloud, security, compliance
8%
Operations & legal
Entity, contracts, IP
Milestone Timeline
Month 1–2
Complete CloseIQ — reconciliation, journal entries, close checklist, approval workflows
Month 3–4
Design partner onboarding — 3–5 companies, live close cycles, direct feedback loop
Month 5–6
GA launch — first paying customers, product-led growth, second module in build
Month 7–12
Expand to AP and AR modules, grow to 10+ customers, raise Series A on ARR
The Founder

Domain expert. Product architect. Solo founder.

Lunari is built by a founder who has lived the problem from both sides. A career spanning Visa and Schlumberger — two of the most operationally complex financial environments in the world — combined with deep practitioner expertise in IFRS, US GAAP, ASC 606, IFRS 15, and complex multi-entity contract structures.

This is not a technical founder who learned accounting. This is an accounting expert who learned to build. The product architecture, the module depth, the audit trail design, and the AI strategy all come from someone who has personally closed the books under IFRS and US GAAP at global scale. That is why the product is different.

The solo founder structure is intentional. Every architectural decision, every product tradeoff, every go-to-market choice is made by the person with the deepest domain knowledge. There is no translation layer between the problem and the solution.

VisaSchlumbergerIFRSUS GAAPASC 606 / IFRS 15Multi-entity structuresComplex contractsAudit readinessDomain expertProduct architect
Get in Touch

Interested in the round?

We are having conversations with pre-seed and seed-stage investors with conviction in B2B SaaS infrastructure and fintech. If that is you, we would like to talk.

All information shared is confidential and subject to NDA on request.