FendraTalk to us

The platform

Fendra platform.

Illustrative workspaceDemo

Ask

Ask the business question. Get the evidence behind the answer.

↑

Answer

Every answer shows the evidence it rests on.

Approved price increases averaged 4.0 percent. Only 2.6 percent reached the invoice.

Long-tail and mid-market customers explain 68 percent of the gap.

Long-tail customers realized 1.7 percent, 2.3 points below the approved increase.

1.6 M invoice linesJan to Dec 2025price_realization

Realized price, 12 months

+0.0%

Evidence

Every finding traces back to the underlying transactions.

Customer groupTransactionsApprovedRealizedGap
Strategic accounts182 K+4.0%+3.6%−0.4 pp
Key accounts410 K+4.0%+2.9%−1.1 pp
Mid-market650 K+4.0%+2.5%−1.5 pp
Export230 K+4.0%+3.1%−0.9 pp
Long tail95 K+4.0%+1.7%−2.3 pp

Trend

The realization gap widened after March while the approved increase stayed fixed.

JanAprAugDecTolerance

Largest gap since March

+0.0 pp

Nine of twelve months exceeded the tolerance line.

Comparison

Long-tail customers received the same approved increase, but retained 1.9 points less than strategic accounts.

Strategic accounts
0.0%
Long tail
0.0%
Export
0.0%
Key accounts
0.0%
Mid-market
0.0%
Other
0.0%

Source: 1.6 M invoice lines, Jan to Dec 2025. Realized against the approved increase.

Setup

Connect the systems that already hold the commercial truth.

SfSnowflake340 M rows
DbDatabricks1,2 B rows
BqBigQuery87 M rows
AzAzure Synapse58 M rows
PgPostgreSQL12 M rows
SaSAP31 M rows

Works with the data stack you already run.

Fendra connects directly to your existing cloud warehouse and data environment.

SnowflakeDatabricksMicrosoft AzureGoogle BigQueryAmazon RedshiftSAPMicrosoft Dynamics

How it works

One foundation for every analytical question.

Fendra connects to the data, builds a working model of how the business operates and uses AI to run analyses across the full dataset.

01

Connected data

Read directly from the systems and cloud warehouse you already operate.

SnowflakeDatabricksAzureBigQueryRead

02

Working model

Customers, products, suppliers, contracts and transactions are connected through shared business definitions.

CustomersProductsSuppliersContractsTransactionsDefinitions

03

AI processing at scale

Analyses run in parallel across the full dataset, not a sample.

04

Decision-ready outputs

Findings, visualisations and decision material come from the same analytical model.

Finding1.8 MSEKprice realization

Built for real analytical work

Built for questions that do not fit a dashboard.

Created by data scientists and former analytics experts, the Fendra platform is designed for messy business data, changing definitions and questions that cannot be reduced to fixed reports.

Where a sample stopsFull data, not samplesAnalyse the complete dataset, including the long tail and the exceptions.Flexible analysis, not fixed dashboardsDevelop new analyses as priorities and business conditions change.

Security

The platform comes to the data.

Fendra runs inside your environment with read-only access. Your data stays where it already lives.

Runs in your environment

Deployed inside the infrastructure and security model you already operate.

Read-only access

Fendra reads the required transaction and master data without changing the source.

Nothing copied out

The analysis runs where the data already lives.

No new data estate

Start with the systems and pipelines already in place.

Bring us the question your dashboard cannot answer.

Talk to us