AI document data extraction: when to automate and when to involve a human
A practical guide to deciding which document fields can be extracted automatically, what to validate, and when to route exceptions to a person.
Practical AI ideas
Practical Nexarex guides on ai & agents, technology, and business process improvement.
A practical guide to deciding which document fields can be extracted automatically, what to validate, and when to route exceptions to a person.
A polished demo is not enough to approve an AI agent for production. Learn how to define its task and boundaries, test realistic failures, assign oversight, and roll it out in stages.
A practical guide to choosing AI, business rules, or a combination of both for SaaS features. Evaluate input variability, control, data quality, and maintenance before building.
A practical guide to letting an AI agent answer questions from internal documents without widening access to client data. Learn how to choose sources, enforce user-level permissions, verify references, and review answers.
A practical approach to controlling an online store AI agent: define trusted sources, verify product details and stock, hand uncertain questions to staff, and test before expanding the rollout.
A practical decision guide to handling restaurant reservation enquiries with a clear website, a form, staff, or an AI agent. Learn where the handoffs matter and why receiving a request is not the same as confirming a table.
A practical approach to gathering buyer requirements before routing a property enquiry: choose essential questions, set response limits, define sales handoffs and run a controlled pilot.
A practical approach to deploying an AI agent that helps a service business find internal procedures, with clear source ownership, access controls, testing, and a limited rollout.
A practical guide to deciding when a sales enquiry AI agent should answer, gather details for a colleague, or hand off immediately. Covers complexity, uncertainty, customer requests, and the context a receiving team needs.
Before launching an AI agent for product questions, check its information sources, price and stock handling, treatment of uncertainty, and route to a human team member.
A practical comparison of internal search and AI agents for professional firms, covering accuracy, permissions, traceability, content maintenance, scalability, human oversight, and the case for a hybrid approach.
A practical guide to defining response, quality, handoff and conversion metrics before expanding a real estate AI agent. It covers evaluation criteria, human controls and a measurable pilot approach.