AI PLATFORMS AND INFRASTRUCTURE

Build a shared business context for AI agents

Define business terms, rules, data ownership and permitted sources in one governed context layer, so every agent interprets requests the same way, uses eligible evidence and avoids unnecessary processing cost.

Industry

Technology, Financial services, Retail and consumer goods, Manufacturing, Public sector

Business function

IT and engineering, Operations and delivery

Business goal

Improve decision quality, Plan cost and capacity

Solution category

AI platforms and infrastructure, Agents and orchestration, Assistants and knowledge

The opportunity

Agents misread requests when business terms, rules and data ownership are implicit or defined differently across systems. Each team then rebuilds context inside its own prompts, which increases cost, inconsistency and the risk of acting on ineligible information.

How it works

01
Identify the business terms, rules and sources that agents depend on.
02
Define each term with its owner, permitted sources and access conditions.
03
Serve scoped context to each agent request according to the user and task.
04
Review gaps, conflicts and changes, then version the context with its approvals.

What it needs

Business glossary and decision rules
Data ownership and access policies
Approved sources and system metadata

What it produces

Versioned, governed context layer
Scoped context for each agent request
Conflict and gap register with owners

Where people decide

Data and process owners approve definitions, rules and source eligibility before agents can use them, and review every change before release.

Example application

A retailer defines what counts as available stock, a priority customer and an approved discount, so service, pricing and replenishment agents apply the same rules.

What to measure

Evaluation measures to agree before release, not achieved results.

Agent outputs consistent with approved definitions
Processing cost per completed task

Next step

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