AI Integration
AI integration adds practical automation to an existing workflow without custom models. It is best for summarization, drafting, classification, and decision support.
Typical use cases include AI assistants, content drafting, document extraction, and internal knowledge workflows.
AI Assistants
Custom AI trained on your docs to answer customer questions instantly.
Content Generation
Auto-generate emails, reports, and social posts with AI drafting.
Data Analysis
AI-powered extraction, classification, and summarization of documents.
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By the numbers
McKinsey research finds that roughly 60% of occupations have at least 30% of activities that could be automated with current technology — knowledge work such as summarizing, classifying, and drafting sits at the top of that list. Source: McKinsey - Jobs Lost, Jobs Gained
Best for
Existing workflows with a repetitive text step — triage, summarization, classification, or drafting — where a human still reviews the output.
Not for
Decisions requiring guaranteed correctness with no human in the loop, such as pricing, compliance, or payouts.
Frequently asked questions
- Do I need a custom AI model?
- Almost never. Existing models connected to a well-designed workflow outperform custom training for the vast majority of business use cases.
- How do you handle wrong AI output?
- Every AI step has a confidence threshold and a human review path. Low-confidence items are queued rather than actioned.
- What does AI integration cost to run?
- Model usage is typically the smallest line item — most workflows run for a few dollars a day at small-team volumes.
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