Pharma & CPG · Commercial Excellence

Decision Ontology for Commercial Excellence

Every commercial decision, reading from the same truth.

Purpose-built for real-world commercial decisioning, not generic analytics.

Unified Context Causal Self-Learning

One Enterprise Brain

One brain, not six systems.

A pricing tool, a CRM, a media platform, and a trade system can each be excellent on their own, and still leave commercial teams reasoning from six different versions of the truth. The ontology is what replaces "six tools, six truths" with one.

Point Solutions Today

Each system holds its own definitions, tries to hand off to the next, and drops it at the edge.

vs

One Ontology

Same six layers, one shared state. Every decision, and every function, reads and writes the same record.

Same decision, two ways.

Three failure modes point solutions can't fix, and how a connected ontology fixes each one.

Causal Reasoning

Why did Northeast sales drop?

Point solution

The BI dashboard shows a regional decline. Pricing, trade, and competitive data sit in three separate tools, so nobody can trace why.

Connected ontology

The ontology traces the chain: a competitor price cut (Competitive) → a delayed trade counter-offer (Promotion & Compliance) → understocked shelves (Inventory & Supply). Full causality, not a flat number.

Grounded Applications

A next-best-action that can't be executed

Point solution

A next-best-action app sits on top of the CRM alone. It recommends outreach that ignores live inventory or an active MLR hold.

Connected ontology

Built on the ontology, the same app inherits inventory, pricing, and compliance state automatically. Every recommendation is executable, not just plausible.

Surfaced Blind Spots

A promotion failure nobody explained

Point solution

A trade promotion underperforms. Nobody connects it to a competitor's price cut that same week. The two datasets never sit side by side.

Connected ontology

The ontology surfaces the correlation on its own, flagging that ROI dropped specifically where a competitor moved price. The blind spot becomes a visible signal.

How It's Built

Built by agents, not a project.

The ontology isn't a one-time modeling project. Three kinds of agents build, maintain, and act on it continuously.

Always on, not a one-time build

1

Data Agents

Ingest & reconcile

Continuously ingest and reconcile data regardless of shape, ERP tables and EDI feeds as easily as trade contract PDFs, scanned deduction backup, call notes, and loyalty app clickstreams. They resolve mismatched SKU codes, duplicate accounts, and missing fields without a manual mapping project.

2

Ontology Agents

Model & maintain

Take what Data Agents reconcile and build the six layers themselves, inferring relationships, resolving the same account or SKU across systems, and flagging drift as source systems change, so the ontology stays current without a re-modeling cycle.

3

Decision & Application Agents

Act & orchestrate

Orchestrate the tools that act on the ontology, a pricing engine, a next-best-action app, a trade-spend optimizer. They can be schedule-triggered, event-triggered, or rule-triggered, and every trigger checks live ontology state first, so no action fires against stale or partial data.

Structured & unstructured data Data Agents reconcile Ontology Agents model Six living layers Decision & Application Agents orchestrate

The Ontology

All Commercial Relationships & Causality, Mapped.

Six functional layers, the full ontology stack behind every commercial decision, not a subset.

Data Foundation

Any format. Any mess.

Format comes first: tables or free text, clean or messy, Data Agents handle it. The systems below are just examples, not a checklist.

Structured

Tables & feeds

Tables, feeds, and structured records.

ERP master tables GS1 product feeds ERP shipment tables EDI 852/867 POS feeds CRM activity tables CDP profile tables Pricing engine tables Finance GL WMS/ERP inventory tables EDI 846 Media platform logs TPM/TPO records Syndicated competitive panels

Unstructured

Documents & free text

Documents, notes, scans, and free text.

Packaging spec PDFs Supplier spec sheets Forecast override emails Analyst adjustment notes Call notes Voice-to-text transcripts Business card scans Segmentation decks Survey verbatims Trade contract PDFs Deduction backup scans Exception emails Depot phone logs Agency PDF reports Creative briefs MLR review documents Claims review redlines Earnings call transcripts Shelf photos News articles

The Four Decisions

Different decisions. Same six layers.

Commercial Reasoning, Sales, Marketing Intelligence, and Portfolio & Pricing each draw a different combination from the same ontology, no decision waits on a separate data pull.

Decision 01

Commercial Reasoning

The synthesis layer, where demand signal, portfolio state, and competitive pressure combine into a single read on what's actually happening before a decision gets made anywhere downstream.

Reads from

Product & Portfolio Ontology

Demand Ontology

Competitive Ontology

Decision 02

Sales

Territory and call planning, next-best-action, and trade execution, reading from a single account definition instead of five inconsistent ones.

Reads from

Product & Portfolio Ontology

Account & Engagement Ontology

Customer & Segment Ontology

Promotion & Compliance Ontology

Decision 03

Marketing Intelligence

Mix and channel decisions grounded in who's being reached, what it costs, and what price and competitive pressure look like at the same moment.

Reads from

Product & Portfolio Ontology

Account & Engagement Ontology

Customer & Segment Ontology

Price & Margin Ontology

Spend & Channel Ontology

Competitive Ontology

Decision 04

Portfolio & Pricing

Price and assortment moves checked against real stock position, live deal status, and what competitors are doing before they ship.

Reads from

Product & Portfolio Ontology

Price & Margin Ontology

Inventory & Supply Ontology

Promotion & Compliance Ontology

Competitive Ontology

Agent Library

Decision & Application Agents, purpose-built for Commercial Excellence.

Pre-built agents that read directly from the six-layer ontology, ready to deploy, not built from scratch.

01Decision Agents

Reasoning primitives, reusable across every workflow.

02Application Agents

Purpose-built commercial workflows.

Architecture

From data to decision.

One flow, four tiers, agents run the first two so the ontology stays live without a manual pipeline.

Structured + Unstructured

ERP / EDI tables

CRM notes & calls

Trade PDFs & scans

Media & panel data

Data + Ontology Agents

Reconcile & resolve

Model six layers

Keep state current

Flag drift

Decision Layer

Commercial Reasoning

Sales

Marketing Intelligence

Portfolio & Pricing

Outcomes

Price & promo moves

Territory plans

Media allocation

Assortment calls

Governance & Trust

Built for regulated data.

Every layer, every agent action, and every recommendation is traceable, access-governed, and explainable by default.

01

Full data lineage

Every value traces back to its source system and timestamp, no black-box joins.

02

Role-based access

Field, brand, and finance teams see the layers relevant to them, governed at the ontology level.

03

Explainable outputs

Every recommendation, and every Data Agent or Ontology Agent action, shows which layers and records it drew from.

04

MLR & claims-aware

Promotion & Compliance Ontology keeps promotional-material approval status visible wherever it's used.

Decision Ontology for Commercial Excellence

See your commercial data here.

We'll walk through your current systems and show where the six layers slot in.

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