An AI data analyst for founders who can't afford one
Junior data analysts cost €60K/year. AnalityQa AI gives you the same capability — chat with your data, ship live dashboards, run investigations — for less than the price of a SaaS seat.
Where the day goes wrong
You don't have a data team and you can't justify hiring one yet
A junior analyst is €50–60K fully loaded. A senior is double that. Until you're €1M+ in revenue, the math doesn't work — but you still need to know your CAC, your retention, your unit economics. So you bash spreadsheets at 11pm or pay a fractional consultant who's slow and expensive.
Your data is in 4 different tools and nothing is reconciled
Stripe says one MRR number, your accounting tool another, your CRM has its own pipeline view, and Google Analytics shows traffic that nobody can tie to revenue. You spend half your monthly review reconciling instead of deciding.
You make decisions on gut feel because the data takes too long
Should you raise prices? Drop a plan? Double down on a channel? You'd love to look at the numbers — but the numbers take three days to assemble and the answer is no longer relevant by then.
Your investors and board want metrics you don't have ready
Cohort retention. Net revenue retention. Burn multiple. Payback period. These aren't optional anymore for fundraising — but producing them takes specialised work most founders haven't done before.
What you actually ask AnalityQa
Plain English in. Charts, tables, and live dashboards out.
What's our MRR by plan for the past 12 months, with new and churned MRR broken out?
→ Stacked MRR waterfall chart, ready to drop into the board deck.
Which of our customers are at high risk of churning in the next 60 days?
→ Ranked list of at-risk accounts with the supporting product-usage signals.
How does the unit economics on our Pro plan compare to Starter — LTV, CAC, payback?
→ Side-by-side LTV/CAC table with payback curves and a written diagnosis.
Build me a fundraising-ready dashboard with MRR, ARR, churn, NRR, and CAC payback.
→ Live dashboard URL you can share directly with prospective investors.
Why did revenue drop 8% last month?
→ Investigation report — drivers ranked by contribution, with the affected accounts and metrics named.
If we move pricing from €29 to €39 per seat, how does that affect projected ARR assuming a 12% conversion impact?
→ Two-line scenario chart with revenue delta and break-even sensitivity.
How AnalityQa fits your workflow
Five capabilities — every persona uses all of them, in their own way.
Chat with your data
Ask any question in plain English (or French) and get the answer with the supporting chart. Most founders use this to replace the 30-minute weekly back-and-forth with a fractional analyst — they ask the question themselves and have the answer in 30 seconds.
Auto data prep
Upload a Stripe export and a CSV from your CRM and AnalityQa AI auto-detects schemas, proposes joins, and flags messy columns (inconsistent dates, duplicates, missing values) before you query. No data engineering background required.
Live shareable dashboards
Pin every chart you care about to a dashboard that auto-refreshes — board pack, investor update, monthly review. Share a public URL with your board and they see live numbers without an account, a license, or a login.
Investigation mode
When a metric moves, ask why. AnalityQa AI runs an investigation across your connected data and returns a written diagnosis — not a chart you have to interpret. It's the equivalent of having a senior analyst spend an afternoon on the question.
Data-aware analyst agents
Once your data is connected, you get persona-aware analyst agents that know your schema and your business context. They suggest the questions a data analyst would ask, so you don't need to know what to look for to find what matters.
What changes
Use cases relevant to your role
SaaS / Finance
An MRR forecast you can defend in front of the board
Marketing / Finance
LTV and CAC numbers your CFO can actually trust
SaaS / Customer Success
Customer Churn Analysis Without the Spreadsheet Grind
SaaS / Customer Success
Cohort retention without the spreadsheet that nobody updates
Finance / FP&A
AI-Generated Financial KPI Dashboards for Finance Teams
SaaS / Product
Find the activation moment that converts trials
Frequently asked questions
I'm not technical. Can I really use this?+
Yes — that's the design point. There's no SQL to write, no pivot tables to build. You connect a CSV or paste your database connection string, and from there you ask questions in plain English. Most founders ship their first dashboard within 15 minutes of signup.
What if my data is messy — inconsistent dates, duplicates, weird column names?+
AnalityQa AI's data prep step runs automatically on every upload. It detects formatting issues, proposes fixes, and shows you a preview before applying anything. You confirm or override each fix in one click. For most CRM and billing exports, the cleanup takes under two minutes.
Can I share dashboards with my board or my accountant without paying for extra seats?+
Yes. Public dashboard share links are unlimited and don't require the recipient to have an AnalityQa AI account. Your board, your bookkeeper, your investors open the URL and see live data — no per-viewer cost.
How does this compare to hiring a fractional analyst?+
A fractional analyst typically costs €1.5–3K/month for 5–10 hours. AnalityQa AI starts at €14.99/month with unlimited questions. For most pre-Series A companies, AnalityQa AI covers 80% of what a fractional analyst would do; the rest is judgment work where having a human still helps. Many of our users keep a fractional analyst on call for the hard stuff and use AnalityQa AI for the daily work.
Will I get the same numbers I see in Stripe?+
AnalityQa AI runs deterministic SQL against your actual data — there's no guessing. Differences from Stripe's headline numbers are usually due to definition: Stripe's MRR includes pending charges and certain trials by default. AnalityQa AI lets you set the definition explicitly and shows the SQL behind every number, so you can audit.
What if I outgrow it and hire a real analyst?+
Your dashboards, queries, and data connections all stay the same — your new analyst can keep working with them and use AnalityQa AI as their query layer. Most teams keep AnalityQa AI even after hiring, because it does the repetitive work the analyst doesn't want to do anyway (stakeholder questions, dashboard refreshes, ad-hoc pulls).