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A catalog mismatch should become a review task.
In this TechFoundry IMS demo, an unmatched part on a purchase order is flagged as a conflict. The team can review it and link the correct catalog part before fulfillment continues.
A practical example of automation that makes exceptions visible and keeps people in control.
Watch the PO conflicts demo:
https://www.youtube.com/watch?v=xgQzqUZ1Hjw
#AI #Automation #SoftwareDevelopment #Procurement
Great breakdown! Love the practical approach - flagging unmatched parts as a conflict and turning it into a review task before fulfillment is such a smart automation. Prevents so many costly errors down the line. This is exactly how IMS should work: real workflows, connected. Nice demo!
It’s all about use the intelligence where it needed to be, either the intelligence comes from an agent or a human. Ultimately, humans are still responsible for the business outcome and impact.
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From a packing-slip PDF to a shipment your team can track.
This TechFoundry IMS demo matches boxes, parts, and weights from the vendor document and connects courier tracking to the shipment record. A practical example of the AI and automation workflows we build into business software.
Watch the vendor shipment demo:
https://www.youtube.com/watch?v=FmjdRRfUZh8
#AI #Automation #SoftwareDevelopment #SupplyChain
Small automations like these can save teams so much manual work and reduce errors.
Email Triage Automation
The Challenge
Growing companies often struggle with overflowing shared inboxes (sales@, support@, info@). Manual sorting, categorizing, and assigning emails to different departments causes response delays. Even worse, high-priority issues—such as urgent billing complaints or system failures—frequently get buried in the noise, leading to missed deadlines and unhappy clients.
The Solution & Architecture
I engineered an enterprise-grade inbox management and automation architecture using n8n, Gmail API, and OpenAI.
The system workflow functions as follows:
Ingestion & AI Classification: The workflow triggers instantly upon receiving a new message (Gmail Trigger), sanitizes the payload, and passes the text to an OpenAI Chat Model for sentiment analysis and intent classification.
Smart Categorization & Labeling: Based on the AI's output, a routing node assigns the email to the correct department (Finance, Sales, Technical Support, Partnerships) and automatically applies matching Gmail labels in real time.
Priority Escalation Routing: If the system flags an email as high-priority, it immediately triggers a secondary logic line. This packages the case details and shoots an urgent alert card directly into a dedicated Discord channel, complete with a summary and recommended actions.
AI-Assisted Contextual Response: Simultaneously, the system evaluates if an instant acknowledgement is needed, generates a contextual, brand-aligned draft reply using LLMs, and sends it directly within the original Gmail thread to reassure the client.
Business Results
Zero Sorting Overhead: Fully eliminated the manual labor required to filter, read, and forward inbound corporate emails.
Accelerated Escalation: Critical, high-priority issues (like duplicate billing charges) are delivered to managers' chat screens within seconds.
Improved Client Retention: Automated contextual auto-replies ensure clients receive an immediate confirmation that their issue is prioritized and routed to the correct desk.
I'd test calm messages about a service outage alongside angry messages about a routine request, so sentiment doesn't become a proxy for urgency. When the model is unsure of the department or priority, does the email go to a human review queue rather than being silently assigned?
AI Revenue Ops Mesh: Multi-Agent System Design
A system design for a multi-agent revenue operations workflow, built by UI Trax.
The problem: when several AI agents handle research, sales and support, leads get lost in the handoffs. Duplicate messages, unverified bookings, and risky actions with no human check.
The design:
• One shared customer record, deduplicated with idempotency keys
• An orchestrator that assigns one owner at a time, with step and budget limits
• Four specialist agents: Research, Qualify, Sales and Support
• A tool layer for CRM, calendar, WhatsApp API, payments, email and docs
• Guardrails: policy engine, human approval gate and audit log
• A supervisor for loops, tool errors and customer replies
• An eval gate, so no update ships if it breaks a case that used to pass
Deliverable: architecture, workflow logic and a 64-second animated explainer.
Report figures in the video are example data.
