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SpendSide

SpendSide reads every signal across spend, suppliers, contracts, and risk, then proposes the procurement action with the evidence to defend it, all the way to finance-approved savings.

A Cognistone product · grounded AI · every metric traces to evidence

app.spendside.com/spend
Spend / Overview

Total spend

$2.41B

4.2%

Categories

9

0

Suppliers

1,284

3.1%

Maverick spend

9.1%

1.7%

September spike: $11M one-time freight from an Asia-Pacific port event. Underlying run-rate is flat.

Spend by category

treemap · FY24
Tires$420M
Electrical$312M
Steel$268M
Logistics$201M
Plastics$176M
Packaging$143M
MRO$98M
Chemicals$72M
High confidenceFX normalizedUOM normalized

Tire pricing arbitrage: $4.2M across 14 suppliers.

  • Region price spread of 18% on identical compounds.
  • Consolidate to 3 suppliers at regional best price.

Evidence

LPP model 847 invoices
Create opportunity Explain

Live preview. Click the left rail to move through the workspace.

Sits on top of the systems you already run

SAPOracleCoupaAribaIvaluaJAGGAERWorkdayNetSuiteExcelSnowflakeSAPOracleCoupaAribaIvaluaJAGGAERWorkdayNetSuiteExcelSnowflake
the operating loop

One loop, from raw signal to realized savings.

Every module serves the same loop. Each step produces evidence the next step can trust, so nothing is a black box and nothing gets lost between teams.

  1. 01

    Sense

    Ingest spend, suppliers, contracts, and market signals into one canonical model.

  2. 02

    Reason

    Run procurement-native analytics: LPP, similar-part, arbitrage, leakage.

  3. 03

    Recommend

    Surface an opportunity with evidence, confidence, and methodology attached.

  4. 04

    Act

    Open a sourcing event, prep the negotiation, route the approval.

  5. 05

    Verify

    Track to finance-approved, realized savings. Then keep watching.

explore the product

One workspace. Switch the lens, not the tool.

Every surface reads from the same canonical store. Move between spend, savings, suppliers, contracts, and the copilot, and the same dollar keeps the same meaning.

Spend Intelligence

See every dollar, not just every invoice.

A live spend cube across categories, suppliers, and geographies. Classified, normalized, and traceable to the source line.

  • Category and supplier workbenches
  • FX and UOM normalized
  • Drilldown to invoice evidence
Learn more
app.spendside.com/spend

Total spend

$2.41B

4.2%

Realized savings

$78.4M

12.1%

Contract coverage

86.3%

2.4%

Maverick spend

9.1%

1.7%

Spend by category

treemap · FY24
Tires$420M
Electrical$312M
Steel$268M
Logistics$201M
Plastics$176M
Packaging$143M
MRO$98M
Chemicals$72M
seventeen modules

One brain. Seventeen modules. One source of truth.

SpendSide is not a bundle of point tools. Every module writes to and reads from one canonical procurement model, so insight in one place becomes action in another without losing its evidence.

System of intelligence8 modules
See, model, and explain every dollar.
System of action6 modules
Turn insight into sourced, realized savings.
System of record & governance3 modules
Trustworthy data, lineage, and audit.
Explore all seventeen modules
One canonical data store

Every module reads from one source of truth. Hover a node to see what it does, or explore all 17.

trust by construction

Decisions a CFO will sign and an auditor will accept.

Every number can be defended. Select a guarantee to see what it looks like inside the product.

Evidence on every answer
High confidenceFX normalized

Tire pricing arbitrage: $4.2M across 14 suppliers.

LPP model 847 invoices Contract C-2291
FX normalizedUOM normalizedSame FYIndex adjustedContract-linkedHigh data qualityRolling 12M

17

integrated modules

<100ms

perceived page transitions

Field-level

lineage on every metric

12+

savings analytics engines

Built for every seat in procurement

CPOCategory managerSourcing managerFinance partnerLegalSupplier managerData steward

See SpendSide on your spend.

Request a guided demo and we will load a working environment with a category of your choice: opportunities, evidence, and all.

Private preview · onboarding our first design partners · figures shown are an illustrative dataset