Most mid-market companies exploring AI end up in the same place:
1. Proof of concept that never goes live
2. Vendor who disappears after delivery
3. A system that works in a demo but falls apart
The problem isn't AI. The problem is that the people who know AI don't know your operations, and the people who know your operations have never actually built a production AI system. That gap is where budgets go to die. We close that gap. We bring 20+ years of AI systems architecture and supply chain operations experience into the same engagement, and we don't leave until what we built is running in production, not sitting in a slide deck.
What We Build
Agentic AI Systems
We build multi-step autonomous workflows that take real action, not just generate output. Every system is built on production-grade agent frameworks with logging, guardrails, and failsafes designed for business-critical operations.
RAG Architecture
Retrieval-augmented generation systems that connect large language models to your internal knowledge: documents, databases, ERPs, and SOPs. The model answers based on your business context, not generic training data.
LLM Integration & Orchestration
We select, configure, and deploy the right model for the job, then integrate it into your existing tech stack. Not bolted on as an afterthought, but built in from the start, with the orchestration layer to keep it coordinated.
AI Infrastructure & Ops
The infrastructure that keeps AI systems running at the production level: monitoring, versioning, retraining pipelines, and performance management. We build for operations, not demos, which means the system has to keep working after launch.
Who This Is For
We work with founder-led mid-market companies, family-owned businesses modernizing their operations, and portfolio companies preparing for scale or exit. If you've tried AI tools off the shelf and hit a ceiling. Or, if you're ready to build something custom and want it done right the first time, this is the right conversation.
This is not for enterprise companies with dedicated ML teams. And it's not for anyone looking for a quick prototype.
How We Work
01
Discovery & Architecture
We assess your current stack, data, and operational workflows, then design an AI architecture that fits the way your business actually runs — not a generic blueprint.
02
Build & Integration
We build in your environment, connected to your real systems. No sandboxes, no simulated data.
03
Deploy & Stabilize
We stay through go-live, fix what breaks in production, and don't hand off until the system is stable and your team is confident.
04
Operate & Evolve
We provide ongoing support, monitoring, and iteration as your operations scale and your requirements change.
Proven Operational Impact
✓
Rebuilt the purchase order intake layer for a mid-market distributor — eliminated 20 minutes of manual processing per order and saved 11 hours of administrative labor per week.
✓
Deployed an agentic approval-routing workflow for a family-owned manufacturer — reduced procurement cycle time by 60% and removed four manual handoffs from the process.
✓
Integrated an LLM with an existing ERP for a portfolio company's operations team — automated routine data entry across three departments and cut error-related rework by nearly half.