What leaders see
Promising pilots that do not change daily work.
Teams test tools, get useful output, and still copy results into spreadsheets, tickets, emails, or ERP screens by hand.
Services
Business Workflows · AI
AI Agents & Agentic Platforms
Use AI to remove repetitive work without losing control. The goal is not autonomy for its own sake. It is to help people clear routine work faster, surface the right information, and focus their judgment where it matters. We design AI around trusted records, explicit permissions, exception rules, and human review.
01
The Problem
Manual work grows faster than the team can absorb.
The problem is rarely that the model cannot generate an answer. The real problem is that the data, permissions, exception rules, and action boundaries are not governed well enough for AI to affect production work.
What is actually happening
The automation cannot reach the operating record.
Source data, permissions, business rules, exception handling, and audit trails are not clean enough for the system to take action.
What gets worse
Automation scales uncertainty.
Bad inputs move faster, decisions become harder to trace, and teams lose confidence before AI becomes operationally useful.
02
What Changes
What AI Agents & Agentic Platforms includes.
The goal is not autonomy for its own sake. It is to help people clear routine work faster, surface the right information, and focus their judgment where it matters. We design AI around trusted records, explicit permissions, exception rules, and human review.
01
Commerce Agent
Handles buyer-facing transactions — product configuration, pricing, quote generation, order entry, and confirmation. Buyers get instant, accurate responses. Your sales team handles relationships, not administration.
02
Pricing & Margin Agent
Monitors market signals, cost inputs, and margin thresholds in real time. Adjusts pricing dynamically, flags margin risk, and enforces pricing rules across every channel — without manual intervention.
03
Demand Forecasting Agent
Reads sales velocity, seasonal patterns, supplier lead times, and external demand signals. Generates reorder recommendations, flags stockout risk, and adjusts purchasing before the problem hits the warehouse floor.
Related service04
Fulfillment & Routing Agent
Monitors order status, carrier performance, and delivery windows in real time. Re-routes exceptions, triggers customer notifications, and resolves fulfillment issues without a human touching the queue.
Related service05
Exception Resolution Agent
Catches the edge cases — credit holds, substitution requests, freight changes, approval escalations — and resolves them through rules-based reasoning. Handles what used to fill inboxes.
06
Operations Intelligence Agent
Monitors your entire operation — order flow, inventory levels, fulfillment performance, margin trends — and surfaces anomalies, risks, and opportunities to leadership before they become problems.
03
How It Fits Your Operations
How AI Agents & Agentic Platforms fits your operation.
Intelligence layerWhich decisions can be automated, which need review, and which should stay human-owned.
Governance dependencyThe agent needs governed inputs, clear action boundaries, and audit logging before it can touch production workflows.
Data the model must trust
ERP history
exception queues
pricing rules
quality records
fulfillment events
What Launchpad defines before engineering begins
- What the business needs to change and why.
- Which systems, records, risks, and readiness gaps shape the work.
- What should be built, how it fits the architecture, and in what order.
Related Foundations
What to evaluate next.
Follow the dependencies behind this service instead of treating it as an isolated project.
01
Data engineering and integration
Build the governed records, pipelines, and definitions AI needs to produce reliable results.
Explore next step02
Cloud architecture and operations
Prepare secure infrastructure, access controls, monitoring, and recovery for production AI workloads.
Explore next step03
AI on Your Data readiness
Evaluate the use case, owned data, permissions, review model, and workflow outcome before implementation.
Explore next step04
Launchpad readiness and Roadmap
Assess readiness, dependencies, risk, architecture, and implementation order before engineering begins.
Explore next stepLaunchpad Before Engineering
Decide what to build and in what order.
Launchpad assesses the business and turns discovery into priorities, risks, readiness, architecture, and an implementation Roadmap. Metrotechs then engineers and supports the approved solution.
Metrotechs designs, builds, integrates, and supports the approved solution.
Launchpad keeps priorities, risks, owners, decisions, and delivery governance connected.
04
Delivery sequence
How Metrotechs delivers AI Agents & Agentic Platforms.
The goal is not autonomy for its own sake. It is to help people clear routine work faster, surface the right information, and focus their judgment where it matters. We design AI.
01
Workflow Audit
Map every manual workflow that represents a bottleneck — exceptions, approvals, data entry, routing decisions. Identify which ones are high-volume, rules-driven, and safe to automate.
02
Agent Design
Define the decision logic, data inputs, and action boundaries for each agent. Agents operate within governance rules — they do not make decisions outside their defined scope.
03
ERP Integration
Connect agents to your ERP, OMS, WMS, and pricing systems so they read and write live operational data. Agents that cannot access real data cannot make accurate decisions.
04
Controlled Deployment
Deploy agents in shadow mode first — they process real workflows but route outputs to a review queue before taking action. You validate accuracy before live autonomy is enabled.
05
Go-Live & Monitoring
Enable live operation with full audit logging. Every agent decision is recorded — what it saw, what it decided, what it did. Monitoring dashboards surface anomalies immediately.
06
Continuous Improvement
Agent logic improves over time as edge cases are identified and decision rules are refined. We operate the agents post-deployment and tune them against production outcomes.
05
FAQ
Questions that usually decide the scope.
Straight answers to what operators ask before committing budget to this work.
We build direct integrations to ERP through its integration API, and to legacy ERP systems through Python-based middleware in the cloud. Agents read and write live operational data without requiring an ERP replacement or upgrade.