Kutta for Finance
Stay ahead of variance, AI-built FP&A dashboards from your actuals
Skip the planning-platform rollout. Upload actuals and budget from Excel or your accounting exports, and Kutta’s AI builds the variance and runway dashboards your board actually reads.
Enterprise FP&A platforms assume an implementation cycle and a finance team to match. Kutta serves the teams they price out: startups and small finance teams living in Excel and QuickBooks exports who need variance answers today.
No credit card required
The problem
Month-end shouldn’t mean rebuilding the workbook
Small finance teams spend the close crunching data instead of explaining it. The variance is in the spreadsheet, the narrative your stakeholders need is hours of manual work away.
Manual variance hunting
Actuals land, and the hunt begins: which line items are off pace, and why? Every month, the same formulas get rebuilt to find out.
Runway questions deserve instant answers
"How many months do we have?" shouldn’t require reopening the model. Burn moves, and the board wants scenarios, not a single stale number.
Priced out of FP&A platforms
Dedicated planning tools are built, and priced, for mid-market finance orgs. A two-person finance team needs answers, not a rollout.
How Kutta helps
Budget vs. actuals variance, automated
Upload actuals and budget, and Kutta builds the variance dashboard at the line-item level: side-by-side actuals, budget, and forecast with material variances surfaced instead of buried in a 40-tab workbook. When next month’s actuals land, the board updates.
Line-item variance vs. plan
Actuals, budget, and forecast side-by-side at any grain
Material variance flagging
See which line items are off pace without rebuilding the workbook
Period-over-period trends
Track variance direction across months, not just point-in-time
Works from Excel and exports
QuickBooks, Xero, or ERP exports: CSV and Excel in, dashboard out
Actuals vs Budget — OpEx YTD
Ask what drove the variance: in plain English
The number is easy; the narrative is the work. Ask Kutta "what drove the increase in OpEx last quarter" and drill from the topline miss to the vendor, department, or line item responsible. Root cause in seconds, grounded in real queries against your actuals.
Root-cause drill-downs
From topline variance to the exact line items behind it
Plain-English queries
No SQL, no DAX, no waiting on an analyst
Grounded answers
Every number comes from queries on your uploaded actuals
Board-ready output
Share a live dashboard instead of re-exporting the deck
Cash runway scenarios on your real forecast sets
Stress test burn against multiple growth paths. Upload forecast sets and Kutta lets you compare best, base, and worst-case runway side-by-side, so "how many months do we have" always has a current answer with the assumptions visible.
Runway scenario comparison
Best, base, and worst case from your own forecast sets
Burn rate tracking
Gross and net burn trends from your actuals, updated as data lands
Founder-friendly
No finance team required: upload, ask, decide
Free to start
Run your first variance analysis on the free tier
Cash Runway Scenarios
How it works
From raw data to answers in three steps
Connect your data
From spreadsheets to enterprise databases, Kutta connects to your data wherever it lives: CSV, Excel, Parquet, and more.
Visualize it
Simply describe your data or what you want to track. Kutta builds a dashboard in seconds.
Analyze & uncover
Query in plain English, filter with precision, and turn raw data into real decisions.
Compare
How Kutta compares for finance analytics
Finance teams typically weigh chat-based AI analysts, building dashboards in Power BI, or enterprise search-driven BI. Here’s where each fits a small finance team.
| Kutta | Julius AI | Power BI | |
|---|---|---|---|
| Setup required | Upload actuals and budget, done | Upload files per chat session | Data modeling + DAX learning curve |
| Output | Persistent variance dashboards | One-off chat answers | Reports built by trained analysts |
| AI usage limits | No per-message metering | Message caps on every tier | Copilot gated behind premium capacity |
| Who it serves | Founders and small finance teams | Individual analysts | Microsoft-stack enterprises |
| Price to start | Free tier · Pro $30/mo flat | Free tier capped at ~15 messages/mo | $14/user/mo + capacity costs for AI |
Competitor details as of June 2026; see full comparisons below for sources and where each tool wins.
Want the full picture?
If you need ad-hoc Python scripting and statistical modeling artifacts, Julius is genuinely good at that. If you need living dashboards your team checks weekly, unlimited questions, and big files that stay interactive, that’s what Kutta is built for.
Choose Kutta if…
- You ask a lot of questions, message caps change how you work, and Kutta has none
- Your files are big: multi-million-row CSVs and Parquet stay interactive in the browser
- You want dashboards that persist: a board the team checks weekly, not a chat to re-run
- You’re a team: flat pricing and shareable boards instead of a $375/mo workspace tier
Choose Julius AI if…
- You need arbitrary Python: custom statistical tests, model fitting, bespoke transforms
- You want generated artifacts like Excel files and slide decks from your analysis
- You work alone on one-off analyses where a chat transcript is enough
- You’re a student, Julius offers an aggressive 50% educational discount on paid tiers
Pricing — Kutta: Pro $30/mo. Julius AI: Free $0 · Plus/Lite ~$20–35/mo · Pro ~$45/mo · Business ~$375/mo.
Julius AI pricing as reported by third-party teardowns as of June 2026, tier names and prices have varied across sources; check julius.ai/pricing for current figures. Kutta pricing is current.
Kutta inverts those assumptions: plain English is the primary interface rather than a bolt-on, it runs fully in the browser on any OS, AI is included rather than capacity-gated, and pricing is a flat $30/month. For small teams whose alternative to Power BI was "no BI," that’s the actual comparison.
Choose Kutta if…
- Nobody on the team knows DAX, and nobody should have to learn it to see revenue by month
- You’re on Macs or Chromebooks: Kutta is fully browser-based
- You want AI querying without doing capacity-SKU math first
- You need a dashboard this week, not after a modeling project
Choose Power BI if…
- Your org is standardized on Microsoft 365 and Azure, the integration is unmatched
- You employ BI developers who know DAX and want deep modeling control
- You mostly need cheap viewer seats at scale, $14/user is hard to beat for consumption
- You need paginated, pixel-perfect operational reports
Pricing — Kutta: Pro $30/mo flat. Power BI: Pro $14/user/mo · Premium Per User $24/user/mo · Fabric capacity $262–$21K+/mo.
Power BI pricing per Microsoft published list prices as of June 2026 (Pro rose to $14/user/mo in April 2025). Fabric capacity costs vary by SKU and region; Copilot availability depends on capacity tier.
FAQ
Frequently asked questions
AI handles the mechanical layer of financial analysis well: computing variances, building dashboards, surfacing trends, and answering questions against your actuals. It replaces tasks, not judgment, Kutta finds and explains the variance in seconds, and your finance brain decides what it means for the plan.
Keep budget and actuals in a consistent export format, upload both to Kutta, and ask for a variance dashboard at the grain you report on: department, category, or line item. The AI builds it once; each month you upload fresh actuals and the same board updates, replacing the manual rebuild.
Cash runway equals current cash divided by net monthly burn. If you hold $1.2M and net burn is $100K/month, runway is 12 months. Because burn fluctuates, use a 3-month average and refresh monthly, in Kutta, upload your cash and burn data and the runway view stays current as actuals land.
Gross burn is total monthly cash outflow: everything you spend. Net burn subtracts cash inflows like revenue, showing how much cash you actually lose per month. Net burn drives runway; gross burn shows your cost structure. Tracking both reveals whether runway problems come from spending or from revenue.
Yes, this is where AI-driven analysis earns its keep. In Kutta, ask "what drove the OpEx variance in Q2" and the AI drills from the topline number into the departments, vendors, and line items responsible, computed from your uploaded actuals. You get the root cause and the supporting detail in one pass.
Build two or three forecast sets, conservative, base, aggressive, varying revenue growth and hiring assumptions. Upload them to Kutta and compare runway side-by-side under each path. Stress testing burn against multiple growth paths shows the decision points before you reach them, which is exactly what boards ask for.
Start with the three views that matter: budget vs. actuals variance, burn and runway, and a rolling cash forecast. Kutta builds all three from your accounting exports, no FP&A platform rollout, no analyst hire. Founders upload monthly exports, ask questions in plain English, and walk into board meetings with current numbers.
Explore more
Kutta works across your whole team
Your data story starts now
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