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Agent_EyeQ

Agentic AI

Agent EyeQ

Goal-driven AI engine that reasons, acts, and learns — executing real work across MES, APS, and SIOP with auditable governance.

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What is Agent EyeQ

Agentic AI built for manufacturing operations

Agent EyeQ brings autonomous reasoning, action, and learning to the Eyelit platform. Unlike conventional AI tools that generate text or run scripted workflows, Agent EyeQ operates inside the manufacturing system of record — planning, releasing, dispatching, and scheduling with the same vocabulary MES, APS, and SIOP were built on.

It spans the full platform in a single agent loop, discovers the right capability from a registry of over 1,700 Eyelit operations, and executes with complete auditability — every action logged, approved, and replayable.

The result: a coworker that helps operators move faster, and an autonomous employee that can own jobs outright — 24/7, against assigned KPIs and constraints.

Reasons

Intent-aware planning

ReAct loop decides each next step from live observations — not a scripted workflow.

Acts

1,700+ operations

Full Eyelit platform as callable tools — MES, APS, and SIOP in one unified loop.

Learns

Knowledge base

Every quality-gated run feeds a vector store the agent draws on in future sessions.

Governs

HITL + full audit

Approval gates, read/write separation, multi-channel notifications before any change.

Two Modes

Caddy of Employee

The only thing that changes is who’s holding the steering wheel. Same tools. Same governance. Deployed to match the task at hand.

Caddy Mode

Helps you do your job better

Sits next to the operator. Suggests, drafts, recommends, and executes on request. The user stays in charge at every step.

Drafts dispositions, RCAs, and schedule changes for review

Surfaces relevant operational data on demand — no dashboards to build

Walks junior engineers through unfamiliar tasks

Accelerates routine work for experienced operators

Employee Mode

Owns the job outright

Given a goal, not a script. Plans, executes, and escalates by exception. Reports to a human manager.

Runs 24/7 against assigned KPIs and operational constraints

Acts autonomously within human-in-the-loop guardrails

Learns from every run via quality-gated transcripts

Full audit trail — every action traceable and replayable

Same engine. Same tools. Same governance. — Whether Agent EyeQ is assisting or acting, it operates on the same platform infrastructure with identical auditability.

What It Can Do

Operating the plant through conversation and autonomy

Conversational platform

Ask in plain language across MES, APS, and SIOP — get answers and actions, not navigation menus or empty screens.

Autonomous workflows

Multi-step jobs — plan, release, dispatch, hold, schedule — executed end-to-end with human-in-the-loop approval gates.

Live operational insight

Charts, tables, and structured cards built on the fly from real platform data — no dashboard required, no pre-built reports needed.

Faster decisions

Diagnose deviations, suggest dispositions, and draft RCAs and CCAs in seconds using real lot and process data.

Process authoring

Generate flows, scenarios, and task schedules from intent — no XML, no scripting, no scenario UI required.

Full audit and traceability

Every action logged, approved, and replayable — meeting the regulatory and quality requirements of complex manufacturing.

Inside Eyelit

Compressing delivery, support, and engineering cycles

Agent EyeQ also works inside Eyelit — accelerating how we build, support, and onboard across the platform.

JIRA Triage and Bitbucket Dig

Reads tickets, locates relevant code, proposes fixes, and drafts patches from a unified knowledge base of the codebase.

Source-aware diagnostics

Traces issues from Angular through to backend events using a deep code knowledge base — from symptom to root cause.

Faster onboarding

New engineers learn the platform by talking to it — backed by a curated, quality-gated knowledge base of the platform.

In Progress

Headless QA Loop

Set scientifically calculated safety stock targets at every supply chain tier — raw material, WIP, sub-assembly, finished goods, and distributor — using multi-echelon inventory optimization (MEIO) to minimize total pipeline cost while meeting service level objectives. 

Customer support copilot

Answers product questions grounded in real customer configuration and live system state — not generic documentation.

In Progress

Scenario authoring

Authors Eyelit scenarios directly from user instructions — without anyone touching the scenario UI.

Why it qualifies as agentic AI

Beyond chatbots and scripted workflows

Autonomous, tool-using, and grounded in the system of record — Agent EyeQ meets the bar for true agentic AI in manufacturing.

Reasons and acts in a loop

Decides each next step from live observations. Not a scripted workflow — a reasoning engine that adapts to what it finds.

Human-in-the-loop governance

Approval gates, read/write separation, and multi-channel notifications before any change reaches the production system.

Discovers tools at runtime

Finds the right capability from a registry of 1,700+ operations by meaning — not hardcoded calls or fixed integrations.

Pairs with the no-code engine

Domain experts shape agent behavior with scenarios — no engineering required to extend or constrain how the agent works.

Spans all Eyelit Solutions

Reasons across MES, APS, and SIOP in a single agent loop via a common protocol — no system switching, no data gaps.

Acts on the system of record

Executes real operations on real lots — not text generation. Real manufacturing outcomes, with full traceability.

The Eyelit moat: deep manufacturing domain semantics

Agent EyeQ operates inside the Eyelit platform with the plan, lot, equipment, recipe, and scenario vocabulary that MES, APS, and SIOP were built on. This domain depth — two decades of semiconductor, medical device, aerospace, and automotive expertise — is what separates Agent EyeQ from general-purpose AI agents applied to manufacturing.

Key Capabilities

What Agent EyeQ brings to the platform

Built for complex manufacturing environments with the governance, depth, and integration that production operations require.

Model agnostic architecture: Not locked to any single LLM provider. The reasoning layer is swappable as the model landscape evolves.
1,700+ callable Eyelit operations: MES, APS, and SIOP operations exposed as MCP tools — the full platform available to the agent at runtime.
ReAct loop with intent-aware planning: Observe, reason, act, repeat — adapting to live results rather than executing a predetermined script.
Quality-gated learning: Approved agent runs feed a vector knowledge base that improves performance and consistency over time.
Multi-tenant tenancy: Isolation and permission boundaries that meet the IP and data requirements of multi-customer environments.
Humain-in-the-loop (HITL) approval workflow: Configurable human checkpoints before consequential actions — with multi-channel notification and full logging.
No-code scenario integration: Domain experts define agent constraints and behaviors using Eyelit’s scenario engine — no engineering required.
Complete audit trail: Every action, approval, and outcome is logged and replayable — meeting regulatory and quality requirements.

GET IN TOUCH

Ready to meet your next coworker?

See Agent EyeQ reason, act, and deliver outcomes across your manufacturing platform — in a live demo tailored to your environment.

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