Finance analytics that doesn't live in a 14-tab spreadsheet
FP&A teams spend half their week stitching together exports from Stripe, NetSuite, and the CRM. AnalityQa AI joins them automatically and answers the actual question — with audit-grade SQL behind every number.
Where the day goes wrong
The model is a 14-tab spreadsheet that only one person can update
Cash flow projection, MRR roll-forward, expense breakdown, headcount plan, scenario comparisons. Each one is a tab with formulas the original analyst built. When that analyst goes on leave, nobody else can update it without breaking it.
Reconciling Stripe, the GL, and the CRM eats the first three days of every month
Each system reports a different revenue number. Some of the gap is real (deferred revenue, refunds, currency). Some is definition. The finance team rebuilds the reconciliation manually every month because no automated source of truth exists.
Scenario modelling is too painful to actually do
"What if churn rises 0.5pt?" "What if we hire 6 fewer engineers?" In theory the spreadsheet supports this. In practice changing one input cascades through 14 tabs and breaks half of them. So nobody runs the scenarios — and decisions get made on intuition.
Audit and board prep require numbers nobody has time to produce
Cohort revenue retention, magic number, burn multiple, gross margin by product line. Investors and auditors expect these on demand. Producing them on demand isn't possible with the current toolchain — so the team scrambles before each board meeting.
What you actually ask AnalityQa
Plain English in. Charts, tables, and live dashboards out.
Reconcile our Stripe revenue with our QuickBooks GL for the past 6 months — show me the gap month by month.
→ Reconciliation table with explained gaps and unmatched transactions.
Build the MRR roll-forward: opening MRR, new, expansion, contraction, churned, ending MRR — for the past 18 months.
→ Full waterfall view, exportable to CSV for the audit binder.
What's our gross margin by product line for Q1, including loaded COGS?
→ Bar chart of gross margin by product, with the COGS allocation logic visible.
If churn moves from 1.8% to 2.3%, what's the impact on 12-month projected ARR and on cash runway?
→ Two-line scenario chart with ARR and runway impact summarised.
Build a board-ready dashboard with NRR, GRR, magic number, burn multiple, and CAC payback.
→ Live dashboard URL — drop into the deck or share with the board directly.
Why was March operating expense 12% above budget?
→ Investigation report ranking the contributing line items, named vendors, and category-level variances.
How AnalityQa fits your workflow
Five capabilities — every persona uses all of them, in their own way.
Chat with your data
Ask reconciliation, variance, and scenario questions in plain English. The SQL behind every answer is shown so audit and accounting teams can review and reuse it.
Auto data prep
Stripe, NetSuite, QuickBooks, ERP exports, expense reports — AnalityQa AI auto-detects schemas, normalises currency, handles deferred revenue conventions, and proposes joins. The data prep is itself a control: anomalies (negative line items, dates outside the period, untagged GL accounts) are flagged before they hit a report.
Live shareable dashboards
Pin the MRR roll-forward, the cash flow projection, the gross-margin breakdown. Each refreshes against the live data on the schedule you set. Share with the CFO, the board, the investors — no per-seat BI license needed.
Investigation mode
Variance analysis becomes "why was X above budget?" — AnalityQa AI runs a structured investigation, ranks the drivers, and produces a written narrative finance can use in the monthly report.
Data-aware analyst agents
Finance-aware analyst agents understand revenue recognition concepts, cohort definitions, and accounting periods. They surface anomalies before the close — a customer whose recurring revenue silently dropped, a GL account with an unusual variance — so the finance team finds them first instead of in the audit.
What changes
Use cases relevant to your role
SaaS / Finance
An MRR forecast you can defend in front of the board
Finance / FP&A
AI-Powered Cash Flow Forecasting for Finance Teams
Finance / FP&A
Vendor Spend and Expense Analysis with AI
Finance / FP&A
Revenue Recognition and ARR/MRR Analysis with AI
Finance / FP&A
AI-Generated Financial KPI Dashboards for Finance Teams
Marketing / Finance
LTV and CAC numbers your CFO can actually trust
Frequently asked questions
Will AnalityQa AI's numbers reconcile with our GL?+
They will if the source data does. AnalityQa AI runs deterministic SQL — there's no estimation. When numbers diverge from the GL, it's almost always a definition mismatch (deferred revenue treatment, currency conversion timing, refund handling) that AnalityQa AI surfaces explicitly so you can resolve it once and for all.
Can it handle deferred revenue and revenue recognition rules?+
Yes. Tell the chat your recognition policy (e.g. "annual contracts amortise over 12 months, one-time fees recognised at invoice") and AnalityQa AI applies the policy consistently across every revenue query. Audit-friendly: the policy is explicit, not buried in a formula.
How does it handle multi-currency?+
Each transaction is normalised to your reporting currency using the rate convention you specify (point-in-time, period average, or fixed). The same rule applies across historical and forward-looking views so the trend doesn't artificially shift.
Is the data secure enough for finance use?+
Data is encrypted at rest and in transit, processed only to answer your queries, and never used to train AI models. You can connect a read-only DB user and restrict tables. SOC 2 Type II is in flight; we'll publish the report as soon as it's complete.
Can auditors use it?+
Yes — the SQL behind every chart is visible and exportable. Auditors typically request the query, the source connection, and the result. AnalityQa AI provides all three plus a timestamp. Many teams use AnalityQa AI to generate the audit binder itself.
Does this replace our FP&A team?+
No. It removes the mechanical work — reconciliations, roll-forwards, variance reports — so the FP&A team can spend their time on the parts that require business judgment: scenario design, capital allocation, partner negotiations. Most teams find their FP&A capacity effectively doubles.