tieoutScan

Describe your business. Get a working financial model.

Upload your data and tell us what you’re modeling. Tieout generates a first-pass SaaS financial model in minutes — every formula visible, every assumption inspectable, Excel-compatible on export.

Not a six-month Anaplan implementation. Not a proprietary formula language. Not a $500K bill. A model you can defend to your CFO by Friday.

In development. Shaping with design partners now.

The interaction, data model, and outputs below are design work — not a live product you can sign up for today. I’m designing this in the open with a small group of SaaS FP&A leaders who want to shape the v1. The hygiene scan at usetieout.com is live and working — and it’s the foundation this sits on.

Built on the data the scan has already cleanedWhy scan + modeler is one product, not two

Every other planning tool assumes clean data walks in the door. It doesn’t. The reason Anaplan implementations take six months is most of that time is reconciling the inputs. Tieout flips the sequence: clean the pipeline first, then model on top of data you can defend.

Scan
Hygiene pass

Salesforce opportunity export goes in. Ghosts, duplicates, stale dates flagged and excluded. Clean weighted pipeline comes out.

Handoff
Reconciled data

The weighted pipeline number the scan produces flows into the model as the bookings assumption — no re-reconciling, no second source of truth.

Model
Forecast on clean inputs

The 24-month forecast you build uses pipeline already vetted. When your CFO asks how you got to the number, the audit trail goes back to the original CSV.

This is the thing Pigment and Mosaic structurally can’t match. They assume someone else owns data quality. Tieout owns both steps.

How it worksThree steps, end to end under 5 minutes
01

Describe your business

One paragraph, plain English. Tell us what kind of SaaS company you run, where you are, and what you’re modeling.

Sales-led mid-market SaaS, $12M ARR, 4,000 customers, average $250 ARPM, 2.8% monthly churn, 120% NDR. Want to model hiring 15 AEs across Q2–Q3 with a standard 12-month ramp. Horizon: 24 months. Use my Salesforce pipeline as the starting bookings assumption.
Parsed as
Archetypesales_led_midmarket
Horizon24 months
Current ARR$12.0M
Customer count4,000
ARPM$250
Monthly churn2.8%
NDR120%
New AEs15 over Q2–Q3
Ramp curve12-mo standard
Bookings sourceSF pipeline, hygiene-scanned

Cross-check: 4,000 × $250 × 12 = $12.0M ✓ math holds. Review and edit before generating.

02

Upload your data

Drop in whatever you’ve got. Tieout maps each file to the right model inputs automatically.

SF
Salesforce opportunity export
From the hygiene scan, or fresh CSV
✓ Mapped
QB
QuickBooks P&L year-to-date
Last 12 months of actuals
✓ Mapped
HR
Current headcount list
Name, role, start date, loaded cost
✓ Mapped
BG
Last year’s budget (optional)
For comparison; imported as a prior version
✓ Mapped
03

Get a model

Tieout generates a 24-month model: driver tree, revenue waterfall, expense build, cash runway. Every cell is editable. Every formula is inspectable.

Driver treeYear 1 · auto-populated, editable
Revenue$14.2M
New ARR from pipelineƒ
$3.4M
Expansion (NDR 120%)ƒ
+$2.4M
Churn (2.8%/mo)ƒ
−$1.6M
Starting ARR roll-forwardƒ
$10.0M
Expense$11.8M
AE ramp (15 new Q2–Q3)ƒ
$1.8M
Non-AE headcountƒ
$8.4M
Non-people opexƒ
$1.6M
Burn+$2.4M
Runway on $8M cash40 months
Rule of 4038.2
24-month ARR forecast$10.0M → $17.2M
Month 1Month 12Month 24
Already have a model in Excel? Bring it over.Import · Audit · Rebuild

Drop your xlsx. Tieout reads the structure, walks the formula graph, and produces a plain-English audit of what you built — what’s solid, what’s fragile, and what would be safer as a driver. Then rebuilds the whole thing with versioning, clean driver trees, and connections to live data, preserving your intent.

Your original file stays untouched. The rebuild is a fresh Tieout model you can diff against the Excel source cell-by-cell.

Your upload
XLSX
financial_model_FY26.xlsx
6 sheets · 47 formulas · 4.2 MB
├─Revenue Build— ARR waterfall, cohort retention
├─Expense Build— Headcount × loaded cost, opex
├─Headcount— Role, start date, fully-loaded cost
├─Assumptions— Drivers, pricing, growth
├─Monthly CF— P&L roll-up, cash position
├─Dashboard— KPIs, charts
Tieout audit
Detected
  • Sales-led mid-market SaaS archetype (high confidence)
  • 24-month revenue waterfall with expansion and churn drivers
  • Headcount-driven expense build, loaded cost from a separate sheet
  • 12-month historical actuals tab for variance comparison
Flagged
  • 12 hardcoded values in Revenue Build that should be drivers (pricing, churn rate, NDR)
  • 3 broken references on the Assumptions sheet pointing to a deleted cohort tab
  • Mixed ARR and MRRin Revenue Build without a clear conversion — quarter totals may be overstated by ~$400K
  • 2 sheets appear unused (Archive_FY25, Sandbox) — safe to exclude from rebuild
Improvements available
  • Extract 12 hardcoded values into a clean driver tree
  • Reconcile ARR/MRR convention across Revenue Build and P&L
  • Connect actuals sheet to live QuickBooks data for ongoing variance
  • Add version-controlled scenario branches (none currently exist)
Review each suggestion before rebuild. You accept or reject line-by-line.
Versioning that matches how FP&A actually worksBudget, Forecast, Scenario, Actuals — as real objects

Every finance team has the same folder problem. Budget_FY26_v3_FINAL.xlsx. Budget_FY26_v3_FINAL_JK.xlsx. Budget_FY26_Scenario_Bear_v2.xlsx. You know which one is real because you remember — not because the file system does.

Tieout treats each version as a named object with explicit relationships: this Forecast is a branch of the Budget, this Scenario is a branch of Q2 Forecast, and Actuals override forecast cells through the latest complete month. Every re-cut is a named object, not a filename convention. Every change is diffable against any prior version.

If you write code, it’s the git model applied to financial models. If you don’t, think of it as SharePoint version history that actually knows the difference between a budget, a forecast, a scenario, and actuals — and can show you what changed.

  1. Budget FY26frozen

    Approved by board, Feb 2026. Immutable baseline.

  2. Q1 Forecastlive

    Branched from budget. Revised new-logo assumption down 8% after weak Feb. Runway impact: −2 months.

  3. Q2 Forecastcurrent

    Branched from Q1. AE ramp pushed back 6 weeks. Churn trending better than plan.

  4. Scenario: hire 15 AEs in Q2 instead of Q3what-if

    Branched from Q2 Forecast. $1.8M additional burn Y1, $3.4M incremental ARR Y2. Payback: month 22.

  5. Scenario: bear casewhat-if

    Branched from Q2 Forecast. 50% new-logo miss, 4% monthly churn. Runway collapses to 18 months by Q4.

Track how your forecast movesHow you see what changed

Versioning is how we store models. This is how we showyou what moved. Other tools show scenarios inside a single model; Tieout shows how each output variable has drifted across every version of every model you’ve built — with an AI-written narrative explaining why.

Q4 ARR forecast — history
Budget (Feb)
$20.0M
Q1 re-cut (Apr)
$19.2M−$800K
Q2 re-cut (Jul)
$18.4M−$800K
Current (Oct)
$18.1M−$300K
Drivers of change, budget → current
Churn worse than plan−$1.2M
New logo miss Q2−$500K
Expansion better than plan+$400K
AE ramp delayed 6 weeks−$600K
AI commentary, auto-generated

Your Q4 ARR forecast has moved from $20.0M at budget to $18.1M today — a $1.9M reduction driven primarily by higher-than-planned churn (−$1.2M) and the AE ramp slipping by 6 weeks (−$600K). Expansion is running ahead of plan (+$400K), partially offsetting. The remaining −$500Kis a single new-logo miss in Q2 that hasn’t recovered.

Copy-paste-ready for your investor update or board deck.

Built different, on purposeCompared to legacy EPM
Six to sixteen months to real value
vs
A working model in minutes
Proprietary formula language to learn
vs
Plain formulas you can read in any spreadsheet
Certified implementation partners required
vs
Describe your business, upload your data, done
Models live inside the platform forever
vs
Own your models. Export to Excel at any time.
Scenario comparison within one model
vs
Output tracking across every version over time
Shape v1 with me

I’m designing this in the open with a small cohort of SaaS FP&A leaders.

Early access isn’t a signup form — it’s a conversation. You tell me what you’re modeling and the shape of your pipeline. I build the first version of the model with you, by hand if needed, and use what we learn to harden the product. In exchange you get a working model (free during the design phase), direct input on the roadmap, and first access when the paid product ships.

If that sounds worth fifteen minutes on a call, drop your email below or write to me at hello@usetieout.com.

Your email goes to a founder inbox, not a marketing funnel.