Finance · Planning · AI
Finplai (FIN + PL + AI) was born from the merger of the Plai planning platform and the SmartBI analytics product. It covers the full annual controlling cycle: data collection, planning, forecasting, variance analysis, dashboards and conversational analytics. AI is an extension for your controller, not a dependency.
Status quo
Traditional CPM tools focus on data administration. Reports are slow, anomalies arrive late, the forecast is obsolete the moment it's approved.
Controllers spend 30–40 hours a month mechanically consolidating data instead of analysing it.
An ad-hoc question like "why is margin falling in SK?" takes two days. By the time the manager is back, the decision is made without data.
A cost spike is discovered at month-end close. The reaction comes too late, losses can't be reversed.
The yearly forecast is updated quarterly, but the market moves in weeks. The plan is obsolete the moment it's signed off.
Three AI pillars
Finplai is a platform: data model, planning, reporting, audit. AI is at the core of the product, not a paid add-on. The SmartBI module delivers the analytics layer: dashboards and conversational querying.
Managers and consultants ask in plain language, Finplai returns a data-backed answer with a visualisation. No SQL, no waiting on controlling. The key differentiator against legacy MIS.
AI suggests plan adjustments, calculates what-if impacts, flags inconsistencies. Full control stays with the controller: AI always proposes, the user approves.
Runs in the background: watches data, surfaces anomalies, drafts executive summaries before you ask.
Why Finplai is different
Legacy MIS, BI tools and spreadsheets solve a different problem. Finplai targets the controller and CFO directly: the people who need to answer business questions fast.
Legacy MIS / BI / Excel
Finplai
In practice
Managers see the numbers they care about, refreshed every few minutes. For the detail they ask the AI chat in natural language. No Excel export, no waiting on controlling.
Dashboards & AI guide
AI guide
01Dashboards
02What-If analysis
03Planning methods
Finplai ships standard planning approaches ready to use. No month of model tuning, no formula writing. The controller just picks what they need.
Leadership sets the overall targets, AI breaks them down by division, customer and period. Full audit of the allocation.
Unit managers plan their numbers, Finplai aggregates them and checks consistency against the top-down brief.
A plan driven by business drivers (volume × price, capacity × utilisation). AI watches relationships and proposes adjustments.
The forecast refreshes continuously, not just quarterly. A new version can combine sources: actuals through June plus the plan for the rest of the year.
Multiple plan versions in parallel (base, bull, bear). What-if impacts on EBIT calculated live; save a simulation as a scenario.
Every plan version is auditable. You see who changed what, when and why. Including AI-proposed edits.
No developer needed
Finplai is built so that a senior controller or consultant can deploy and operate it: no developer, no data engineer, no vendor lock-in. The data model, dimensions, planning rules and the AI tool API are configured through the UI.
Define dimensions, measures and relationships in the app. No SQL or XML configuration.
Define what the AI can ask about and what it can return. The AI has no direct database access. It goes through validated typed calls.
Who sees what data, who approves the plan, who can access which module. No server-side admin console.
Once configured, you don't need Softim for changes. Your consultant adjusts Finplai for the new quarter themselves.
Use case
From two days of report preparation to a five-minute dialogue. 25× faster.
Before
Before: Friday–Sunday report preparation, controller as a data courier. Decisions rest on two-day-old data.
With Finplai
With Finplai: anomalies already identified, AI answers in plain language, forecast refreshes in seconds.
Finplai opens the Executive Summary Q3: drafted by the AI over the weekend.
"Why is margin falling in SK?" AI returns an answer and a top-3 root-cause chart.
Anomaly −24 % at the butter supplier. Suggested action: renegotiate the contract.
"What if we raise sandwich prices by 4 %?" What-if impact on EBIT, live.
Yearly forecast recalculated. Decision made, meeting ends 20 minutes early.
Measurable impact
Reference case for a mid-sized company with three controllers: 32 hours saved per month × 12 months × CZK 800 hourly rate = CZK 921,600 worth of freed capacity per year. Without hiring an extra team member.
Finplai is designed so your data stays under your control and the AI does nothing it shouldn't.
AI is an extension, not a dependency. You can disable it at any time and the system keeps working. Every AI feature has a manual alternative.
The AI only reads and suggests. Data changes are always made by the user after confirmation. No "AI surprises", no runaway agent.
Every query, every answer, every call logged with a trace ID. Compliance and GDPR-ready, fully traceable after the fact.
Finplai runs in the cloud or fully on-prem. The AI provider follows your rules: Azure OpenAI, or a local model inside your perimeter with no outbound calls.
The AI has no direct database access. It works through typed, validated calls: no SQL injection, no unbounded queries.
The AI respects user roles: a controller sees different answers than a sales rep. Isolation enforced at the API layer.
Cloud-native architecture with on-prem deployment support.
Pilot & rollout
Legacy CPM (SAP BPC, Anaplan) clients wait half a year for the first number. Finplai runs in parallel, doesn't touch your systems, fixed scope, fixed price. First pilot in 2–3 weeks, full production rollout in 6 weeks.
Week 1
One server / VM with Linux and Docker: 2 vCPU / 8 GB RAM / 50 GB SSD, up to 20 concurrent users.
Week 2
Docker Compose deployment, access configuration, sample data import, onboarding from the NK document.
Week 3
Live demo of every AI feature, acceptance testing, user training. Decision to proceed to full rollout.
Week 4–6
Remaining modules added, more roles, more planning methods. Handover to the client's controller. From now on they adjust Finplai themselves.
A Finplai showcase on your own data, no strings attached. We'll calculate the savings on your capacity and walk through your use case.
