Commercial Decision Intelligence

The Decision Intelligence platform for commercial teams.

Forecasting, simulation and optimization, a natural-language interface over them, specialist agents that carry the work, and your business and the market connected underneath — for the teams who own price, promotion, portfolio and growth.

See a platform demo See it on a price decision

Scenario comparison 500ml pack Grocery P07 FY27

Gross profit vs accepted plan FY27 expected value and range

Two price options drawn as filled ranges against the accepted FY27 plan at zero. The plus four percent list option runs from plus 1.8 to plus 3.1 percent of gross profit with an expected value of plus 2.4 percent, and costs 3.1 percent of units and 0.4 points of share. The plus 2.5 percent option with promotion depth held runs from plus 2.2 to plus 3.7 percent with an expected value of plus 2.9 percent, and costs 1.4 percent of units and 0.2 points of share. Revenue rises 0.7 and 1.0 percent respectively.

Owner · Revenue Growth Management Confirm before this changes the plan 4 sources · as at P06 FY27

Why this is hard

Close the gap between insight and action.

  • 15%

    of consumer products organisations report fully integrated commercial data used to routinely drive cross-functional decisions.

    EY, The EY State of Consumer Products, May 2026

  • 61%

    prioritise human judgement over fully automated AI decision making.

    EY, The EY State of Consumer Products, May 2026

  • 1 in 5

    companies has a mature model for governance of autonomous AI agents.

    Deloitte, State of AI in the Enterprise, 2026

Molsaro is built for the 61%: the platform does the analysis, a named person makes the call.

One platform, four capabilities

Collaborative decision making for the modern enterprise

A price decision is made by Revenue Growth Management, checked by Finance, and lived with by Sales. Molsaro puts the analysis, the discussion and the approval in one place, with the same definitions underneath all three.

Eight commercial teams sit at the centre of the platform. Two rings surround them. The inner ring, labelled ask and model, carries Decision Intelligence and Molsaro AI. The outer ring, labelled connect and keep running, carries Agents and Automation and Enterprise and Market Intelligence. The rings carry no direction: work can start at any capability. To the right, a Revenue Growth Management manager and a Finance colleague discuss the four percent price option and dispatch a planner agent to run the alternative.

Ask and model

Connect and keep running

Your teams

  • Revenue Growth Management
  • Marketing
  • Product Management
  • Sales
  • Commerce
  • Strategy
  • Finance
  • Insights & Market Research

Decision Intelligence

forecast, simulate, decompose

Molsaro AI

ask, assemble, answer

Agents & Automation

research, monitor, report

Enterprise & Market Intelligence

your data, your definitions, the market

  • Decision Intelligence

    Forecasts the market, models how demand responds, simulates the options and decomposes the change into named factors.

  • Molsaro AI

    Reads the question, assembles the context, calls the right engines and writes the analysis.

  • Agents & Automation

    Researches, monitors, reports and keeps work moving between reviews.

  • Enterprise & Market Intelligence

    Holds your operational data, your definitions and hierarchy, your documents, and what is happening in the market.

AI you can trust

Decisions you can trust, explain, and control.

Every recommendation shows the sources it used, the definition it applied, the model run behind it and the range around it. Nothing changes a plan until a named person confirms it.

  • Definitions are resolved once and reused everywhere, so two teams asking the same question work from the same definition.
  • Ranges, not single points. A forecast that hides its uncertainty is not a forecast.
  • Quantitative work comes from a trained, accepted model — never from an assumed value.

4 sources checked

Why did gross profit fall in Grocery last period?

−3.4%

range −3.9% to −2.8%

Gross profit fell 3.4% in Grocery in P06. Most of the decline is in promotion depth on the 500ml pack, not in category demand. Sell-out · Snowflake

Category volume was flat at −0.2%. Category study · knowledge base

How this was produced

Definition
Gross profit, your organisation’s definition
Period
P06 FY27 · monthly · 4-4-5 fiscal calendar
Scope
Grocery · own brands and competitors
Sources
4 named
Model
Demand model · accepted · trained P05 FY27
Range
−3.9% to −2.8%

You asked for SKU level. This is brand level — SKU coverage for this account starts P03 FY27.

Reviewed by Revenue Growth Management

Decision Intelligence

Connect every commercial decision to your P&L.

Model how demand responds to price, promotion and distribution for that pack, in that channel, against the competitors it actually faces. Then see where it lands in gross profit, with the accepted plan still on the chart.

  • The forecast sets the market baseline. Demand allocates share within it, so the two never disagree.
  • Cross-effects across the portfolio are included, not assumed away.
  • Eleven named factors decompose the change, and the balancing factor is labelled as one.
  • Every comparison names its reference case.

500ml pack Grocery P07 FY27 vs accepted plan FY27

Left panel: as the list price of the 500ml pack rises from $1.79 to $2.09, modelled units per period fall from an index of 104 to 90.5. The current price of $1.89 sits at an index of 100. Two candidate prices are marked: $1.96, a rise of four percent, at an index of 96.9; and $2.03, a rise of seven point four percent, at an index of 93.5. The expected range widens the further the price moves from the observed price. Competitors price the same pack size between $1.92 and $2.05, so both candidates sit inside the competitive band. Right panel: the gross profit bridge for the four percent option against the accepted FY27 plan. Price adds 5.9 points, volume removes 3.6, promotion adds 0.6, distribution adds 0.3, market adds 0.2, competitive removes 1.1, and the residual balancing factor adds 0.1, giving a net gross profit change of plus 2.4 percent with a range of plus 1.8 to plus 3.1 percent.

Price response

Units per period, indexed

Competitor price band

−3.1% units

−6.5% units

Gross profit bridge +4.0% option

Accepted plan

Percentage points of gross profit vs the accepted plan

+2.4%

gross profit range +1.8 to +3.1

Accepted plan FY27 is the dashed baseline. Residual is the balancing factor.

Across one week, three specialist agents work in parallel. Competitive intelligence watches the competitor set in Grocery and produces a monitor finding on competitor price moves for week 24. Brand performance monitors the growth gap and raises that share loss is concentrated in two accounts. Executive reporting assembles the commercial review for P06 FY27. All three arrive at one person: the Revenue Growth Management owner, with three items of which one needs a decision.

Competitive intelligence

watch the competitor set in Grocery

  1. scan
  2. 2 moves found
  3. price change
  4. verified vs sell-out
Monitor finding Competitor price moves, wk 24

Brand performance

monitor the growth gap

  1. read
  2. gap opens −1.4pp
  3. isolated to 2 accounts
Headline Share loss concentrated in two accounts

Executive reporting

assemble the monthly commercial review

  1. gather
  2. compose
  3. check figures
Report Commercial review, P06 FY27

For your decision

Owner Revenue Growth Management

3 items · 1 needs a decision

Confirm Open

Agents & Automation

AI that accelerates your workflows

Specialist agents research, monitor, analyse and report on a schedule you set. Work that used to take a week arrives before the meeting — and lands with a named owner.

  • Eight categories of specialist, from competitive intelligence and pricing to brand performance and executive reporting.
  • Each has an assignment, a schedule, and finished work you can open.
  • Nothing an agent produces changes a plan on its own.
Consumer Goods
price architecture, promotion planning and portfolio decisions across brands, packs and accounts
Pharma & Life Sciences
demand understanding, market development tracking and launch planning
Retail
category growth and own-brand price and portfolio decisions
Manufacturing
price and portfolio decisions across product lines and channels

What sits under it

The building blocks

What every recommendation on this page rests on.

  • 12

    source-system types, from Snowflake and Databricks to SAP S/4HANA and Oracle Fusion.

  • 11

    named factors decompose every forecast change, with the balancing factor labelled as one.

  • A model tournament per series

    statistical, machine-learning, intermittent and naive families, selected on a held-out period.

  • 8

    categories of specialist agent.

  • Day, week and month

    data granularity, and 4-4-5 fiscal calendars.

  • Row-level security

    on every organisation-scoped table.

Data governance Integrations and connectors

Let’s see what Molsaro can do for you.

See the whole platform, or go straight to the part you need first.

See a platform demo

  • Decision Intelligence

    You have a price, promotion, portfolio or forecast decision to make.

    Explore Analytics & Insights

  • Molsaro AI

    You want your team to ask questions in their own words and check the working.

    Explore Molsaro AI

  • Agents & Automation

    You need specialist work to keep running without adding headcount.

    Explore Agents

  • Enterprise & Market Intelligence

    Your business context and the market are in different places, and neither is connected to the decision.

    Explore Enterprise Intelligence