AI for operations, across 7 workflow patterns.

Reads structured and semi-structured documents that arrive in unstructured formats — invoices, purchase orders, bills of lading, claim forms, contracts, scanned paperwork — and extracts the fields the business cares about into structured records. Routes each extracted record through validation (does it match what we expected, do the totals add up, is the supplier known), then delivers to the system of record. High-confidence extractions land directly; low-confidence ones route to a human reviewer with the source document and the proposed values shown side by side. The pattern absorbs the data-entry work that currently consumes hours of skilled time every day in operations-heavy SMBs.

Sits between an inbound stream of work items — orders, service tickets, requests, repair jobs — and the teams that handle them. For each item, the pattern reads the content, classifies it against the firm's working categories, predicts urgency and skill required, identifies any special handling needed (VIP customer, regulatory case, known-difficult product), and assigns to the right queue or person. The pattern's value is taking the manual triage step — usually done by a dispatcher or team lead — and making it instant and consistent. Different from A6 (which triages messages) because this pattern handles operational work items that drive downstream activity, not just communication.

Looks at images or video of physical items moving through a production, packing, or fulfillment process, and flags items that fail the firm's quality criteria: damaged packaging, missing components, incorrect labels, manufacturing defects. Sits alongside human QC rather than replacing it: the pattern handles the high-volume routine cases so humans can focus on the genuinely ambiguous ones. Different shape from the other D patterns because it processes images, not text or structured records, and because the kill metrics are different (false negatives let bad product through; false positives slow throughput). Used in light manufacturing, fulfillment, and food production.

For firms with field workers, technicians, or mobile service teams, optimizes the daily schedule: which jobs go to which workers, in which order, accounting for skills, travel time, customer windows, priority, and any constraints (e.g. some jobs need two people, some require specific equipment). Replans during the day as new jobs come in, jobs run long, or workers become unavailable. The pattern's value is replacing a dispatcher's manual scheduling — which works fine for a few jobs but breaks under volume — with continuous optimization. Different from D13 (which classifies and routes inbound work) because this pattern actively constructs and modifies schedules.

Predicts demand for inventory items at a useful granularity — per SKU, per location, per week or per day depending on the business — and surfaces reorder recommendations: what to buy, how much, when. Accounts for seasonality, trend, promotions, weather, known disruptions. The pattern's value is replacing the rule-of-thumb reordering most SMBs use (which over-stocks slow movers and under-stocks fast movers) with something that learns from actual sales patterns. Output is a recommendation, not an automated purchase: humans approve buying decisions and the pattern improves over time as it sees what's bought and what sells.

Continuously checks activity across systems against the firm's compliance and policy rules: are expense claims within policy, are PR submissions following the approval workflow, are customer communications meeting regulatory requirements, are access grants getting proper review. Flags potential violations as they happen rather than waiting for periodic audits. Routes flagged items to the right reviewer with the evidence. The pattern's value is shifting compliance from a quarterly cleanup exercise to an always-on signal: violations get caught and fixed within hours, not months, and the audit story becomes much simpler.

Continuously watches signals about the firm's vendors and suppliers — financial news, public filings, security incidents, certification expirations, delivery performance, payment behavior on their side — and flags rising risks before they become operational problems. Different from B5 (which monitors customer churn risk) in that it watches the supply side and the risks are different: supplier going bankrupt, security cert expiring, key vendor being acquired, delivery quality degrading. The pattern's value is moving vendor risk from an annual review exercise to a continuous signal, so issues get addressed during the relationship rather than discovered when they cause downstream impact.