Prepare your data, import it into the system, and start tracking sales, analyzing margins, monitoring targets, and detecting anomalies — step by step.
The system works with your existing sales and finance data. Files are organized by usage: daily usage (customers, products, sales), monthly finance import (GL, invoices, bank), market intelligence (competitors, alerts), and system configuration. Download the sample CSV files below, adapt them to your data, and import them to get started immediately. Reference files (categories, channels, regions, reps) are linked by ID.
CSV files with realistic fictional data — ready to import or adapt
Download Sample CSVs (ZIP)Your customer directory. One row per customer with segment, region, and channel links.
| Column | Description | Example |
|---|---|---|
| name | Customer name | GEOROUTE CONSTRUCTION |
| segment | Customer segment | enterprise |
| region_id | Region ID (links to regions.csv) | reg-ci |
| channel_id | Channel ID (links to channels.csv) | ch-direct |
| contact_email | Contact email | contact@georoute.example |
| contact_phone | Contact phone | +225 27 10 00 01 00 |
| status | Customer status | active |
| currency | Currency code | XOF |
Your product catalog. One row per product with pricing, cost, and category link.
| Column | Description | Example |
|---|---|---|
| name | Product name | Ciment CEM II 42.5 |
| sku | Product SKU | CEM-II-42-5 |
| category_id | Category ID (links to product_categories.csv) | cat-cement |
| unit_price | Selling unit price | 85000 |
| cost_price | Cost unit price | 62000 |
| currency | Currency code | XOF |
| unit | Unit of measure | tonnes |
| status | Product status | active |
Your sales transactions. One row per transaction with customer, channel, rep, and margin details.
| Column | Description | Example |
|---|---|---|
| transaction_date | Transaction date (YYYY-MM-DD) | 2026-01-15 |
| customer_id | Customer ID (links to customers.csv) | cust-001 |
| channel_id | Channel ID (links to channels.csv) | ch-direct |
| sales_rep_id | Sales rep ID (links to sales_reps.csv) | rep-001 |
| region_id | Region ID (links to regions.csv) | reg-ci |
| currency | Currency code | XOF |
| gross_amount | Gross amount before discount | 42500000 |
| discount_amount | Discount amount | 1250000 |
| net_amount | Net amount after discount | 41250000 |
| cost_amount | Cost of goods sold | 31000000 |
| margin_amount | Margin amount | 10250000 |
Sales targets by period and dimension. One row per target with actual amounts for comparison.
| Column | Description | Example |
|---|---|---|
| period | Target period (e.g. 2026-Q1) | 2026-Q1 |
| metric | Metric being targeted | revenue |
| dimension_id | Dimension ID (rep, region, channel, etc.) | rep-001 |
| dimension_type | Type of dimension | sales_rep |
| target_amount | Target amount | 500000000 |
| actual_amount | Actual amount achieved | 412500000 |
| currency | Currency code | XOF |
Reference file for product categories with optional parent hierarchy. Linked by ID from products.
| Column | Description | Example |
|---|---|---|
| id | Category ID | cat-cement |
| name | Category name | Ciment |
| parent_id | Parent category ID (optional) | cat-construction |
Reference file for sales channels. Linked by ID from customers and transactions.
| Column | Description | Example |
|---|---|---|
| id | Channel ID | ch-direct |
| name | Channel name | Vente Directe |
| type | Channel type | direct |
Reference file for geographic regions. Linked by ID from customers, transactions, and reps.
| Column | Description | Example |
|---|---|---|
| id | Region ID | reg-ci |
| name | Region name | Abidjan |
| country | Country | CΓ΄te d'Ivoire |
Reference file for sales representatives. Linked by ID from transactions and targets.
| Column | Description | Example |
|---|---|---|
| id | Sales rep ID | rep-001 |
| name | Rep name | Bamba Kadriatou |
| Rep email | k.bamba@proxait.example | |
| region_id | Region ID (links to regions.csv) | reg-ci |
Line items for each sales transaction. One row per product line with quantity, price, and margin.
| Column | Description | Example |
|---|---|---|
| transaction_id | Transaction ID (links to sales_transactions.csv) | txn-2026-0001 |
| product_id | Product ID (links to products.csv) | prod-001 |
| quantity | Quantity sold | 500 |
| unit_price | Unit selling price | 85000 |
| discount_pct | Discount percentage | 3 |
| line_total | Line total after discount | 41250000 |
| cost_total | Line cost total | 31000000 |
| margin | Line margin | 10250000 |
Bank account movements. One row per transaction with credit/debit amounts and bank account reference.
| Column | Description | Example |
|---|---|---|
| date | Transaction date (YYYY-MM-DD) | 2026-03-01 |
| description | Transaction description | Client payment - Northwind Co |
| amount | Amount (positive for credit, negative for debit) | 53200 |
| type | Transaction type | credit |
| bank_account | Bank account identifier | BANK-EUR-001 |
| currency | Currency code | EUR |
Accounts payable invoices. One row per supplier invoice with amounts, tax, due date, and purchase order reference.
| Column | Description | Example |
|---|---|---|
| vendor_name | Supplier name | Acme Supplies SA |
| invoice_number | Supplier invoice number | FA-2026-0301 |
| amount_excl_tax | Amount excluding tax | 27000 |
| vat | VAT amount | 4860 |
| amount_incl_tax | Amount including tax | 31860 |
| currency | Currency code | EUR |
| due_date | Due date (YYYY-MM-DD) | 2026-04-15 |
| status | Invoice status | received |
| po_ref | Purchase order reference | PO-2026-031 |
Accounts receivable invoices. One row per customer invoice with amount, due date, and payment status.
| Column | Description | Example |
|---|---|---|
| customer_name | Customer name | Northwind Trading |
| invoice_number | Invoice number | FC-2026-0101 |
| amount | Invoice amount | 53200 |
| currency | Currency code | EUR |
| due_date | Due date (YYYY-MM-DD) | 2026-02-15 |
| status | Payment status | paid |
Accounting journal entries. One row per entry with type, status, description, and approval trail.
| Column | Description | Example |
|---|---|---|
| entry_type | Entry type (e.g. manual, automatic) | manual |
| status | Entry status | posted |
| description | Entry description | Monthly depreciation - Equipment March 2026 |
| created_by | Created by user | Controller |
| approved_by | Approved by user | CFO |
General ledger postings. One row per posting with account code, period, debit/credit amounts, and source reference.
| Column | Description | Example |
|---|---|---|
| account_code | Account code (links to chart_of_accounts.csv) | 4110 |
| period | Accounting period (YYYY-MM) | 2026-03 |
| debit | Debit amount | 0 |
| credit | Credit amount | 45000 |
| currency | Currency code | EUR |
| description | Entry description | Revenue - Product Sales March |
| source_ref | Source reference | SALES-2026-03 |
| posted_by | Posted by user | CFO |
The accounting chart of accounts. One row per account with type, hierarchy, and control account flag.
| Column | Description | Example |
|---|---|---|
| account_code | Account code | 1110 |
| name | Account name | Cash & Bank Accounts |
| type | Account type (asset, liability, equity, revenue, expense) | asset |
| parent_account_id | Parent account code (optional) | 1100 |
| is_control_account | Whether this is a control account | false |
| currency | Currency code | EUR |
| status | Account status | active |
Budget lines by account, department, and cost center. One row per budget line with committed and actual amounts.
| Column | Description | Example |
|---|---|---|
| account_code | Account code (links to chart_of_accounts.csv) | 4110 |
| department | Department name | Sales |
| cost_center | Cost center code | CC_SALES |
| amount | Budgeted amount | 150000 |
| committed | Committed amount | 0 |
| actual | Actual amount spent | 126000 |
| variance | Variance (actual - budget) | -24000 |
Purchase orders. One row per PO with vendor, total amount, status, and approver.
| Column | Description | Example |
|---|---|---|
| vendor_id | Vendor identifier | VND_ACME |
| po_number | Purchase order number | PO-2026-031 |
| total_amount | Total PO amount | 31860 |
| currency | Currency code | EUR |
| status | PO status | received |
| approved_by | Approved by user | CFO |
Competitor directory. One row per competitor with products, estimated market share, and notes.
| Column | Description | Example |
|---|---|---|
| name | Competitor name | GlobalTech Distribution |
| products | Products or services offered | IT equipment distribution |
| market_share_estimate | Estimated market share (percentage) | 18 |
| notes | Notes and observations | Strong partnerships with major OEMs. |
Market intelligence alerts. One row per alert with type, message, source, and severity.
| Column | Description | Example |
|---|---|---|
| type | Alert type (competitor, pricing, etc.) | competitor |
| title | Alert title | RetailMax launches e-commerce platform |
| message | Alert message | RetailMax announced a new B2B e-commerce platform targeting wholesale buyers. |
| source | Source name | Business Press |
| source_url | Source URL | https://business-press.example/story1 |
| severity | Severity level (low, medium, high) | high |
| acknowledged | Whether the alert has been acknowledged | false |
Regulatory and compliance alerts. One row per alert with type, message, source, and severity.
| Column | Description | Example |
|---|---|---|
| type | Alert type (tax, ohada, etc.) | tax |
| title | Alert title | VAT rate unchanged for 2026 |
| message | Alert message | Standard VAT rate remains at 20% for 2026. |
| source | Source name | Tax Authority Official |
| source_url | Source URL | https://tax-authority.example/notice1 |
| severity | Severity level (low, medium, high) | low |
| acknowledged | Whether the alert has been acknowledged | true |
System policy and compliance rules. One row per rule with conditions, action, and severity.
| Column | Description | Example |
|---|---|---|
| rule_type | Rule type (e.g. approval_threshold) | approval_threshold |
| name | Rule name | High-value transaction approval |
| conditions | Rule conditions (JSON) | {"max_amount": 5000} |
| action | Action when triggered (block, warn) | block |
| severity | Severity level (violation, warning) | violation |
| is_active | Whether the rule is active | true |
Once your CSV files are ready, importing them takes seconds. The system validates every file and shows you exactly what will be imported.
Launch the Sales & Finance Intelligence app. You'll see a chat interface — this is your command center.
Click the + button to attach a CSV file, or drag and drop it into the chat.
Describe what you want in plain language:
The system automatically checks your data and shows you:
• Number of rows detected and ready to import
• Data quality score (percentage)
• Any errors or warnings (missing columns, invalid dates, unknown IDs)
• A preview of the first rows
Once you're satisfied with the validation results, confirm the import. Your data is now available for analysis, targets, margins, and reporting.
Once your data is imported, here's what your team can do every day — just by asking in plain language.
Add or update your customer directory with segments, regions, and channels.
Result: Validated customer records with segment, region, channel, and contact details — ready for sales tracking.
π Dashboard: Dashboard β Data tab β import history and quality scores
Build your product catalog with selling prices, cost prices, and categories.
Result: Product records with SKU, unit price, cost price, and category links — ready for margin analysis.
π Dashboard: Dashboard β Data tab β import history and quality scores
Load historical or ongoing sales transactions with line items for full analysis.
Result: Transaction records with customer, channel, rep, gross, discount, net, cost, and margin amounts — ready for analysis.
π Dashboard: Dashboard β Data tab β import history and quality scores
Break down revenue by customer, product, channel, region, or sales rep.
Result: A performance breakdown with revenue, growth, and contribution by channel — with charts and trends.
π Dashboard: Dashboard β Sales tab β revenue, orders, margins, regional/product/rep performance
Monitor gross and net margins by product, customer, and channel over time.
Result: A margin analysis ranking products by margin percentage, with cost and revenue breakdowns.
π Dashboard: Dashboard β Sales tab β margin analysis by product, customer, and channel
Compare sales targets against actual results by rep, region, or channel.
Result: A target-vs-actual dashboard with attainment percentages, gaps, and trend indicators for each rep.
π Dashboard: Dashboard β Sales tab β target vs actual by rep, region, or channel
Rank customers and products by revenue, margin, or volume.
Result: A ranked list with revenue, margin, and contribution percentage — ready for account planning.
π Dashboard: Dashboard β Sales tab β ranked lists with revenue and margin
Identify unusual discounts, margin drops, or unexpected transaction patterns.
Result: A list of anomalies with transaction details, discount levels, and margin impact — ready for investigation.
π Dashboard: Dashboard β Sales/AP-AR tab β alerts prioritized by severity with risk amounts
Export any analysis, dashboard, or breakdown to PDF or CSV.
Result: A formatted PDF report ready for presentations, reviews, or sharing with stakeholders.
π Dashboard: Dashboard β any tab β export button for PDF or CSV
At month-end, import your finance data (GL, bank, invoices), run the closing process, and generate financial statements.
At month-end, import your GL entries, bank transactions, and AP/AR invoices for the period.
Result: Finance data validated and loaded — ready for closing, reconciliation, and statement generation.
π Dashboard: Dashboard β Data tab β import history, quality scores, data freshness
The AI drives your monthly closing with 19 built-in tasks and their dependencies. Track progress, late tasks, and blockers.
Result: A progress gauge, task table, dependency analysis, and blocked items — guiding you through each closing step.
π Dashboard: Dashboard β Closing tab β progress gauge, task table, dependency analysis, blocked items
The AI prioritizes financial exceptions by severity Γ amount Γ age, and guides you step by step to resolve them.
Result: A prioritized list of exceptions with aging (current/30/60/90/90+ days), overdue invoices, and vendor/customer status.
π Dashboard: Dashboard β AP/AR tab β invoice aging, overdue invoices, vendor and customer status
Generate OHADA-formatted financial statements ready for presentation.
Result: OHADA-formatted statements with margin gauges and variance alerts — ready for the board.
π Dashboard: Dashboard β Budget/Closing tab β OHADA-formatted statements with margin gauges and variance alerts
Compare your budget to actuals to pilot variances across departments.
Result: A budget-vs-actual analysis with variance by department, cost center, and account.
π Dashboard: Dashboard β Budget tab β budget vs actual, variance analysis, performance by department
The AI runs control tests automatically, detects separation-of-duties violations, and generates audit evidence dossiers exportable as PDF.
Result: Control test results, separation-of-duties status, and audit evidence dossiers — ready for external auditors.
π Dashboard: Dashboard β Audit tab β control test results, separation of duties status, audit evidence dossiers
The AI monitors the market, your competitors, and regulatory changes in continuous cycles — and alerts you when something matters.
The AI watches your competitors via web research and alerts you when something deserves your attention.
Result: Competitor activity summaries with market alerts, tracked changes, and strategic implications.
π Dashboard: Dashboard β Watch tab β market alerts, competitor tracking, regulatory changes, exchange rates
View and acknowledge market intelligence alerts grouped by severity.
Result: Alert cards grouped by severity (high, medium, low) with source, message, and acknowledgement status.
π Dashboard: Dashboard β Watch tab β alerts grouped by severity, click to acknowledge
The AI watches OHADA regulations, tax rules, and exchange rates (BCEAO/BEAC) and alerts you on changes.
Result: Regulatory alerts and current exchange rates — keeping you compliant without manual monitoring.
π Dashboard: Dashboard β Watch tab β regulatory alerts and exchange rates (BCEAO/BEAC)
Your dashboard home page gives you an instant snapshot of all activity, with AI recommendations and forecasts.
Get an instant snapshot of your business: revenue, growth, orders, average basket, margin, and critical alerts.
Result: KPI cards (revenue, % change, orders, average basket, margin) + a trend chart showing daily revenue evolution.
π Dashboard: Dashboard β Executive tab β key sales & finance KPIs, critical alerts, company health indicators
The notification bell aggregates all critical events: exceptions, budget alerts, late tasks, AI recommendations, and regulatory news.
Result: A grouped list of notifications by type (exception, budget alert, delay, recommendation, info) — click to navigate to the relevant item.
π Dashboard: Click the bell icon at top β notification list β click to navigate β "Mark all as read" to clear
The AI uses your historical data to forecast revenue for upcoming periods, with a confidence level.
Result: Forecasted revenue with confidence level (based on RΒ²), detailed table by period, and a trend chart with historical + projected data.
π Dashboard: Dashboard β Forecasts tab β revenue forecasts, demand predictions, scenario comparisons, opportunity rankings
The AI generates prioritized recommendations from your latest insights, with estimated impact for each.
Result: Prioritized recommendation cards with estimated impact, effort, and urgency — ready to turn into action plans.
π Dashboard: Dashboard β Executive tab β prioritized recommendation cards with impact, effort, and urgency
Import categories, channels, regions, and reps before importing customers, products, and transactions. The system links records by ID, so reference files must exist first.
Use the exact same ID values across all files (e.g. region_id "reg-ci" in regions, customers, transactions, and reps). The system links data by these IDs.
Always use YYYY-MM-DD format for dates. This avoids ambiguity between regional formats and ensures accurate period analysis.
If you have thousands of rows, start by importing a small sample (50-100 rows) to validate the structure. Then import the full file.
After any analysis, you can ask follow-up questions like "Show me the details for the top customer" or "What's the margin trend for this product over 6 months?"
Every analysis can be exported to PDF or CSV. Use this to prepare management reviews, board presentations, and stakeholder reports.
Launch the app and import your data, or request a personalized demo.