AI Automations That Actually Save Time (Not Just Look Cool)

Most "AI-powered" features are demos. They look impressive in a pitch deck but fall apart in production. Here's how we approach AI automation differently.

Start with the workflow, not the tech

The first question isn't "how can we use AI?" - it's "what's eating your team's time?" AI is a tool, not a goal. If a simple script or integration solves the problem, we build that instead.

The 3 types of AI automation that actually work

1. Structured data extraction Taking unstructured inputs (documents, emails, forms) and pulling out structured data your systems can use. This is the highest-ROI AI automation for most businesses.

2. Intent routing Understanding what someone wants and routing them to the right place - whether that's a knowledge base article, a specific team member, or an automated workflow. Our healthcare Teams bot is a good example.

3. Decision support Not replacing human decisions, but giving humans better information faster. Summarizing data, flagging anomalies, generating drafts for review.

What doesn't work (yet)

• •Fully autonomous customer-facing AI without guardrails - hallucination risk is still real
• •AI replacing domain expertise - it augments experts, it doesn't replace them
• •AI on bad data - garbage in, garbage out applies even more with AI

Our approach

Every AI automation we build has: explicit guardrails, human escalation paths, comprehensive logging, and a clear ROI metric tied to actual time or cost savings.