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Context Engine

Agents don't operate in a vacuum. Every decision happens within an organizational context that lives outside the transactional system. The Context Engine absorbs that context through three channels — documents, natural language directives, and email signals, and writes it into the shared world model so every agent, at every tier, reads from the same truth.

Why Context Matters

Industry research consistently shows that AI value comes from grounding decisions in organizational context, not just transactional data.

BCG, September 2025

70%

of AI value is concentrated in core business functions: sales, supply chain, and pricing

McKinsey, 2025

88%

of organizations report regular AI use in at least one business function

Gartner, August 2025

40%

of enterprise apps will include task-specific AI agents by 2026 (up from <5%)

"Respondents most often report using AI to capture information as well as processing and delivering it, such as through a conversational interface."

Three Input Channels

Each channel captures a different type of organizational signal, processes it through language understanding, and routes context to the appropriate decision layer.

Documents & RAG Strategy docs, annual reports, operating models, market analysis Embed · Retrieve · Inject Azirella Assistant Text or voice directives from executives and planners Parse · Classify · Route Email Signals Automated inbox monitoring for supply chain signals Detect · Extract · Route Context Engine CONTINUOUS · MULTI-CHANNEL · CONFIDENCE-GATED Strategic (S&OP) VP / C-suite directives Tactical (Planning) Director-level context Operational (Site) Manager adjustments Execution (Agent Hive) Analyst context + email signals Input channel Context Engine Decision layer

Documents & RAG

Passive strategic context

Annual reports, strategy documents, operating models, market analysis, and executive memos are ingested, chunked, embedded, and retrieved at decision time via RAG. This gives agents the strategic backdrop they need without explicit human intervention.

Change-triggered re-indexing
Time-decay weighting for freshness
Routes context to all decision layers

Azirella Assistant

Active human directives

Users issue directives by typing or speaking. The system parses intent, classifies urgency, asks smart clarifying questions when needed, and routes the directive to the correct decision layer based on the user's organizational role.

Role-based routing (VP, Director, Manager, Analyst)
Auto-apply when confidence is high enough
Smart clarification when intent is ambiguous

Email Signals

Automated signal intelligence

Automated inbox monitoring classifies inbound emails into signal types - demand changes, supply disruptions, lead time shifts, price changes, quality issues - and routes each signal to the appropriate execution agent for immediate action.

12 signal types with auto-classification
Routes directly to specific execution agents
Privacy-safe - extracts signals, not content

Azirella Assistant - Natural Language Directives

Supply chain decisions are shaped by context that lives in people's heads - a VP who just left a board meeting, a category manager who heard pricing rumors, a plant director managing a labor constraint. Azirella Assistant gives these stakeholders a direct channel to influence agent behavior without writing rules or filing tickets. With voice mode activated, you can have a full spoken conversation, issue directives and receive verbal feedback in real-time.

1. USER DIRECTIVE "Prioritize margin over volume for Q2" Text, voice, or chat 2. PARSE & CLASSIFY Intent extraction type: policy_override | urgency: high scope: network | horizon: Q2 2026 3. CONFIDENCE GATE 0.92 Auto-apply 4. ROUTE Strategic Layer Policy parameters updated across entire network ROLE-BASED ROUTING Role Routes To Scope VP / C-suite Strategic (S&OP) Network-wide policies Director Tactical (Planning) BU / regional parameters Manager Operational (Site) Shift / cross-function Analyst Execution (Agent Hive) Individual orders / SKUs Bayesian effectiveness tracking learns which directive patterns produce good outcomes and adjusts confidence thresholds over time
"AI is no longer just an instrument for human use - it is also an actor."

Email Signal Intelligence

Critical supply chain signals arrive by email hours or days before they appear in transactional systems. A supplier mentions lead time extension in a reply. A customer hints at a large order. A logistics provider flags port congestion. Email Signal Intelligence captures these signals automatically so agents can act before the data hits ERP.

INBOUND EMAIL From: Supplier ABC "Lead times extended to 8 weeks..." From: Customer XYZ "Expecting 40% volume increase..." From: Quality Dept. "Batch 2847 failed inspection..." From: Logistics Co. "Port congestion, 5-day delay..." From: Raw Materials "Steel price up 12% effective..." + more signals... SIGNAL CLASSIFIER Language Understanding lead_time_change (0.94) demand_increase (0.88) quality_issue (0.91) supply_disruption (0.86) price_change (0.79) Confidence Gate High: auto-route Low: human review EXECUTION AGENTS FORAGER PO SCOUT ATP GUARD Quality BUILDER TO FORAGER PO Lead time Demand Quality Logistics Pricing Privacy by Design Signals extracted, content never stored. Opt-in, revocable consent. Original emails untouched.

12 Signal Types

Demand Increase
Forecast uplift, new orders
Demand Decrease
Order cancellation, downturn
Supply Disruption
Force majeure, shortages
Lead Time Change
Extension, compression
Price Change
Increases, surcharges, discounts
Quality Issue
Complaints, non-conformance
New Product
Launches, substitutions
Discontinuation
EOL notices, phase-outs
Order Exception
Delays, partial shipments
Capacity Change
Plant shifts, expansions
Regulatory
Compliance, tariffs, sanctions
General Inquiry
Status requests, information

The Shift to Autonomous Decisions

Industry research shows a clear trajectory toward AI agents that act on context, not just report on data.

BCG, September 2025

17%

of total AI value already comes from agents, rising to 29% by 2028

Deloitte, 2026

74%

of companies expect to use agentic AI at least moderately within two years

BCG, September 2025

5%

of companies are "future-built" for AI. 60% are laggards with minimal gains

Deloitte, 2026

21%

of companies have a mature governance model for autonomous agents

"If you just take your existing workflow and try to apply advanced AI to it, you're going to weaponize inefficiency."
"Future-built firms see double the revenue increase and 40% greater cost reductions than laggards."

Document Pipeline - From Text to Decisions

Unstructured knowledge flows through four stages before reaching agents as grounded, relevant context.

INGEST Annual Reports PDF, 10-K, Earnings Strategy Documents 3-year plan, OKRs, priorities Operating Model Org structure, RACI, policies Market Analysis Competitors, trends, risk Executive Directives Board decisions, memos CHUNK & EMBED Semantic chunking Metadata tagging Entity extraction Vector embeddings RETRIEVE Agent decision query Similarity search ★ Top match (0.94) ★ Match 2 (0.87) ★ Match 3 (0.81) Reranking + filtering Context window CONTEXT INJECTION Agent Decision Transactional state + policy parameters + guardrails + RAG Context Strategic priorities + org constraints = Grounded Decision Documents are re-indexed on change. Agents retrieve fresh context at decision time. Continuous pipeline - documents flow left to right, freshness guaranteed Decision outcomes inform future context relevance scoring 1 2 3 4

Collaboration & Approval Workflows

Context doesn't just flow one way. When agents make decisions that require human oversight, the Collaboration layer provides the channels for discussion, approval, and escalation.

Agent Decision PO #4821 - $142K Expedite recommended Threshold Check Below Auto-execute Above Approval Request Threaded discussion Context + rationale attached Escalation if no response Approve Override Activity Feed AGENT GOVERNANCE COLLABORATION HUMAN AUDIT Every decision, approval, override, and comment is logged. Full audit trail from agent recommendation to final action.

Threaded Conversations

Every agent decision supports threaded comments. Discuss forecast overrides, question sourcing, or flag anomalies - in context, attached to the specific decision.

Configurable Approvals

Approval rules match your governance structure. Configurable per decision type, value threshold, and risk level with automatic escalation paths.

Activity Feed

A unified stream of agent decisions, human overrides, approval requests, and context changes - the transparency autonomous systems need to earn trust.

"The real question for AI decisions isn't 'is it accurate?' It's 'who gets to disagree with it, and how fast?'"

What This Enables

With all three context channels active, agents make decisions that reflect current organizational reality across every input mode.

Azirella Assistant

A VP types "prioritize margin over volume for Q2" and the strategic layer adjusts cost-service trade-offs across the entire network within minutes.

Email Signals

A supplier email mentioning "extended lead times on component X" is classified and routed to the PO agent, triggering alternate sourcing before the delay hits MRP.

Documents & RAG

A board memo about a new market entry is ingested via RAG, and inventory agents begin pre-positioning stock in the target region.

Azirella Assistant

A plant manager says "we're losing shift 3 next week" and the operational layer redistributes production across remaining shifts and sister plants.

Email Signals

A quality complaint email auto-routes to the Quality agent, which tightens acceptance criteria and flags the supplier for inspection.

Collaboration

An expedite decision exceeding $100K triggers an approval workflow. The director inspects the agent's rationale, discusses in-thread, and approves in 4 minutes.

"AI can have insights into a container on a ship somewhere in the Atlantic and know in advance whether it will arrive on time. No human can do that at scale."
- Knut Alicke, McKinsey Partner, Supply Chain Practice

20-30%

Inventory reduction with AI-driven planning

McKinsey, 2024

15-45%

Cost reduction in procurement via GenAI

BCG, February 2025

2x

Revenue growth for AI-leading firms vs. laggards

BCG, September 2025

See the Context Engine

Watch agents incorporate real-time context from documents, directives, and email signals into live decisions.