Services
AI & Intelligent Automation
Practical AI and automation, built for production, not demos.
We design and deploy AI-driven automation that holds up under real operating conditions — from intelligent document processing to agentic workflows that reduce manual work across enterprise and logistics operations.
Overview
Most enterprise AI initiatives fail at the boundary between a promising demo and a system someone is accountable for at 2 a.m. Our practice is built for that boundary: we design AI and automation as operational systems, with evaluation, guardrails, fallbacks, and ownership defined before anything touches production. We are enthusiastic about the technology and deliberately unsentimental about where it belongs.
What We Offer
Services within this practice.
Focused offerings that can stand alone or combine into an end-to-end program.
AI opportunity assessment
A structured evaluation of where AI genuinely earns its keep in your operation — and where a rules engine or a process fix is the honest answer. You get a ranked portfolio of candidates with the data, risk, and integration realities attached.
LLM application development
Production applications built on large language models — document processing, drafting, classification, conversational interfaces — with retrieval, evaluation harnesses, and human review designed in from the start.
Agentic workflow automation
Multi-step automations where AI agents execute bounded tasks across your systems — triage, matching, reconciliation, follow-up — under explicit permissions and audit trails. Designed so humans supervise outcomes rather than perform keystrokes.
Document and data extraction
Automated intake of invoices, contracts, bills of lading, purchase orders, and other operational documents into structured data your systems can act on. Built with confidence scoring and exception queues rather than blind trust.
Process automation engineering
Classic and intelligent automation across ERP, finance, and operations workflows, combining RPA, APIs, and event-driven design. We automate the process as it should run, not as it accidentally evolved.
AI governance and evaluation
Frameworks for testing, monitoring, and governing AI systems in production — accuracy baselines, drift detection, escalation paths, and clear accountability. Designed so leadership can approve AI use with their eyes open.
Outcomes
What good looks like.
- AI systems that carry real operational load, with defined behavior when they are wrong
- A team that understands, monitors, and can extend the automations it owns rather than fearing them
- Automation applied where the economics justify it, with an honest record of what was descoped and why
- A governance posture that lets you adopt new AI capability quickly because the evaluation discipline already exists
Our Approach
How we deliver this work.
- 1
Identify
We target automation where it removes real friction, not wherever AI sounds impressive.
- 2
Prototype
Fast, disciplined prototyping validates an approach before it's built into critical workflows.
- 3
Productionize
AI systems are engineered with monitoring, guardrails, and fallback paths from day one.
- 4
Govern
Automation is only valuable if it's trustworthy — we build in the oversight to keep it that way.
FAQ
Common questions.
Most stalled pilots fail for predictable reasons: no defined workflow owner, no evaluation standard, and no plan for the cases the model gets wrong. We start from the operational end — who acts on the output, what happens on failure, how success is measured — and only then choose models and tooling. A pilot designed to become a production system behaves very differently from one designed to impress.
Let's talk about ai & automation.
Tell us about the challenge you're solving for — we'll follow up to understand the fit before proposing anything.