Agentic AI
Multi-agent architectures, custom workflows, and AI decision pipelines. We build systems that act, not just respond. Evals first, models second.
Practice areas
Multi-agent Architectures
Orchestrated systems where specialized agents collaborate to handle complex, multi-step workflows.
Custom Workflow Automation
End-to-end automation of business processes using AI agents with human-in-the-loop checkpoints where needed.
AI Decision Pipelines
Production-grade decision systems with eval frameworks, fallback logic, and accuracy SLAs.
Business Process Automation
Replacing manual, repetitive work with intelligent automation that maintains auditability and control.
Common questions
What do you mean by agentic AI?
Systems that act instead of just responding. An agentic system reads its inputs, makes a decision against explicit criteria, and takes the action in your real systems, with guardrails and human checkpoints where the risk warrants them.
How do you keep AI agents from making expensive mistakes?
Evals before launch, explicit automation conditions, and staged rollouts. Work that matches the conditions runs touchless; everything else routes to a person unchanged. Every action is logged and reviewable, so trust is earned release by release.
Do our systems need APIs for this to work?
No. We integrate through whatever surface exists: APIs, EDI, file drops, or the application UI itself when nothing else is available. We process 200+ TMW invoices a day for a fuel carrier through a workflow that has no API at all.
How fast does the first automation reach production?
We start with structured discovery, then ship the safest slice of the workflow first and widen coverage release by release, so production value arrives early instead of after a big-bang launch.