Agentic financial analysis for mid-market finance teams Agentic financial analysis

Supercharge your finance team to outperform an enterprise FP&A department

Scenario plans, variance analysis, cash forecasts, delivered in minutes, verifiable line by line, at a third the cost of an analyst hire.

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your.datawyse.app
Scenario Planning2m ago
Q3 Revenue Breakdown1h ago
Vendor Contract Review3h ago
Headcount PlanningYesterday
Cash Flow Forecast2d ago
Analytical Chat Ask anything about your business
DFinancial Analyst
Queried current headcount and fully-loaded costs
Modeled monthly burn with 8 additional engineers
Projected 12-month cash runway under both scenarios
Eight engineers at your fully-loaded cost of $185K adds $123K/month to burn. Runway drops from 18.2 to 16.4 months. Here's both scenarios side by side.
$1.80M/mo
Adding 8 engineers increases monthly burn by $123K. Runway drops from 18.2 to 16.4 months.
Current Burn$1.68M
+8 Hires$1.80M
Runway Now18.2mo
After Hire16.4mo
DataInsightsLogicAssumptionsExports

12-Month Cash Runway Projection

JanAprJulOctDec
Current (18.2mo)+8 Hires (16.4mo)
DFinancial Analyst
Modeled staggered hiring: 5 in Q1, 3 in Q2
Projected runway and milestone timeline
Good call. Staggering preserves 17.1 months runway and still hits the March product milestone. I've added it as a third scenario.
17.1mo
Staggering to 5 in Q1 + 3 in Q2 preserves 17.1 months runway and still hits March milestone.
Current18.2mo
+8 Q116.4mo
Staggered17.1mo
DataInsightsLogicAssumptionsExports

Scenario Comparison: Cash Position

Current+8 Q15+3 Staggered
DFinancial Analyst
Layered $400K MRR pipeline into cash model
Recalculated break-even for all three scenarios
With that pipeline converting, break-even moves from month 14 to month 11. The staggered plan gets there fastest. I'd go with that one.
Month 11
With $400K MRR pipeline, break-even moves from month 14 to month 11. Staggered plan breaks even earliest.
Break-evenMo. 11
Pipeline$400K
Runway17.1mo
DataInsightsLogicAssumptionsExports

Cash Flow with Revenue Ramp

Break-even Mo.11
Revenue RampStaggered Burn
DFinancial Analyst
Pulled Q2 and Q3 P&L line by line
Identified cost drivers: infra migration + bonus payroll
Built margin bridge from 34% to 19%
Revenue was flat. This is entirely cost-side. Two things hit at once: a $1.2M unplanned infra migration and the semi-annual bonus payroll run. Here's the full bridge.
-15pts
EBITDA margin fell from 34% to 19% between Q2 and Q3. Revenue was flat; the entire drop is cost-side.
Q2 EBITDA34%
Q3 EBITDA19%
Delta-15pts
RevenueFlat
DataInsightsLogicAssumptionsExports

EBITDA Margin Bridge: Q2 to Q3

34%Q2 +2%Revenue -3%COGS -8%Bonus Payroll -6%Infra Mig. 19%Q3
DFinancial Analyst
Pulled original FY budget for infrastructure
Compared budget vs actual spend
Budget was $200K, actual came in at $1.4M. 600% over. It was a board-approved emergency after the March outage, not in the original FY plan.
600%
Infrastructure migration was budgeted at $200K. Actual spend hit $1.4M after the board-approved emergency cloud migration.
Budget$200K
Actual$1.4M
Variance$1.2M
DataInsightsLogicAssumptionsExports

Infra Migration: Budget vs Actual

$200KBudget $1.4MActual
Board-approved emergency migration post-March outage. Not in original FY budget.
DFinancial Analyst
Stripped infra migration and bonus timing
Recalculated trailing 4-quarter margins
Stripping the infra migration and bonus timing, run-rate margin is 26%. Underlying business has been stable at 26-28% all year. Q3 just looks ugly on paper.
26%
Stripping one-time items, run-rate EBITDA margin is 26%. Underlying business stable at 26-28% all year.
Reported19%
Adjusted26%
Gap7pts
DataInsightsLogicAssumptionsExports

Reported vs Adjusted EBITDA: Trailing 4 Quarters

19% 26% Q4 '24Q1 '25Q2 '25Q3 '25
ReportedAdjusted (excl. one-time)
DFinancial Analyst
Pulled GL entries and filtered to COGS and OpEx
Re-attributed 76% of mistagged Finance entries
Grouped by cost type and cost center
$20.2M total. G&A is your biggest cost type at 30%, and Tech is the biggest center. Heads up: 76% of the GL tags were pointing at Finance, so I re-attributed those to the actual teams.
$20.2M
FY2025-26 total spend. G&A is the biggest cost type at 30% and Tech is the biggest cost center.
Total$20.2M
Largest TypeG&A
Largest CenterTech
GL Fixes76%
DataInsightsLogicAssumptionsExports

Expenditure by Cost Type

G&A
$6.1M
COGS
$4.4M
Sales
$3.7M
DFinancial Analyst
Drilled into G&A by sub-category
Flagged quarter-over-quarter anomalies
Office & Facilities leads at $1.8M, but the real story is Professional Services. It spiked 40% in Q3 from the Series B legal and advisory fees. That's a one-time bump.
$6.1M
G&A breakdown. Office & Facilities leads at $1.8M. Professional Services spiked 40% in Q3 from Series B legal.
Office$1.8M
Prof. Svc$1.4M
Insurance$1.1M
Software$0.9M
DataInsightsLogicAssumptionsExports

G&A Line Item Breakdown

Office
$1.8M
Prof Svc
$1.4M +40%
Insurance
$1.1M
Software
$0.9M
Professional Services spiked 40% in Q3. One-time legal and advisory fees from Series B close.
DFinancial Analyst
Audited 8 enterprise subscriptions
Cross-referenced seat utilization and spend
Tableau is the worst. 12% seat utilization on a $180K contract. Snowflake is at 34% on $96K. Between those two you've got $276K in potential savings sitting on the table.
$276K
Three subscriptions have under 35% utilization. $276K in potential annual savings.
At Risk$276K
Lowest Util12%
Reviewed8 subs
DataInsightsLogicAssumptionsExports

Subscription Utilization Audit

ToolAnnual CostUtilization
Tableau$180K
12%
Snowflake$96K
34%
Salesforce$240K
67%
Slack$84K
92%
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Datawyse lets your finance team say "I'll have that for you in a few minutes" , instead of drowning in Excel for days.

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How a board question becomes a verified and traceable answer, in minutes

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Customized to how your business actually works

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DataWyse pulls directly from your business tools to generate reports and insights. Critically, the AI has no ability to modify or write back to your data it can only read it. This removes any scope for hallucination, since the output is always grounded in your actual source data. On top of that, every analysis shows you its full thought process along with the exact data queries used in both Excel and SQL format so you can trace exactly how any number or insight was arrived at, not just take it at face value.

When you're pulling from multiple sources your ERP, CRM, and accounting tools data cleaning and validation at every step adds up fast. Analysis that takes your team 5 hours is done in under 5 minutes with DataWyse. It connects to all your sources and generates your weekly cashflow forecasts, pipeline reports, P&L, and more without anyone having to stitch it together by hand. Every report also has a built-in chat where your team can ask follow-up questions about any finding and get an instant, data-backed answer so decisions get made with full context, not just the top-line numbers. With the repetitive, time-consuming work handled, your finance team can focus on the analysis and strategic work that actually moves the business forward.

DataWyse is tailor-made for US businesses generating between $1M and $50M in revenue, that are aiming to grow rapidly. We aim to help companies that need serious financial intelligence but aren't at the scale where hiring a full analytics team makes sense. The reports, dashboards, and cash flow monitoring modules are calibrated for SMBs. You don't need a data warehouse, a BI team, or any additional learning to use it.

We need about 45 minutes with your software admin to connect your tools via API. Within one to two business days after that, your first reports are ready. No lengthy implementation, no IT project.

Any ERP or CRM that has API Access.

Plain English is how it works. You can ask questions like "why did our travel spend spike in February?" or "what's our gross margin trend by product line over the last six months?", and DataWyse pulls from your connected data, reasons through it, and gives you a structured answer with charts and context. No SQL, no dashboards to configure, no technical background needed.

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