All field notes

Inventory decisions are made against stale data and rules nobody has revisited. This guide covers building an agent that watches demand and supply signals continuously, detects the exceptions that matter, proposes reorder actions with reasoning, and leaves purchase commitments under human control.

RFP responses consume specialist time reassembling answers the organisation has already written. This guide covers building a governed answer library, parsing requirements into answerable units, generating drafts that cite their sources, routing anything that constitutes a new commitment to a human owner, and measuring whether the thing actually saves time.

Most companies are AI-assisted—they use AI tools inside old processes. AI-native companies rebuild the process around AI. The difference decides who compounds.

Most legal teams negotiate the same clauses repeatedly without knowing what they have already agreed. This guide covers extracting clauses from executed contracts, classifying them consistently, separating approved language from historical language, tracking deviation from the standard, and building retrieval that answers what position the company has taken before.

Credit memos consume analyst weeks assembling financials, market context, and covenant terms into a document a committee reads in twenty minutes. This guide covers automating the assembly, spreading financial statements with verification, extracting terms from facility documents, drafting the factual sections, and keeping credit judgement, risk ratings, and recommendations with the analyst and the committee.

Lab results arrive faster than clinicians can read them in context. This guide covers extracting structured values reliably, presenting them against reference ranges and prior results, surfacing trends rather than isolated numbers, abstaining rather than interpreting, and keeping clinical interpretation with clinicians.

Policy questions are asked constantly across HR, compliance, finance, and operations, and answered inconsistently by whoever is available. This guide covers grounding an agent in authoritative, versioned policy, scoping answers by jurisdiction and role, citing the clause every time, handling questions the policy does not answer, and escalating interpretation to the people who own it.

Prior authorization consumes clinical staff time and delays care. This guide covers determining whether authorization is required, assembling the clinical documentation a payer's criteria demand, submitting through the right channel, tracking status to resolution, and the firm boundary that an agent assembles evidence while clinicians make clinical judgements.

Explanation of benefits documents arrive in dozens of payer formats and carry the information that determines whether a claim was paid correctly. This guide covers extracting line-level data reliably, matching to claims and remittances, classifying denials by reason, routing underpayments to follow-up, and why posting to the ledger stays under human control.

Quoting sits between a customer who wants a number and a rating engine that needs complete, accurate risk data. This guide covers capturing risk information conversationally, validating and enriching it, integrating with the rating engine rather than replacing it, handling eligibility and referral rules, and the regulatory boundary that keeps pricing inside filed rates.

KYC onboarding is where regulated firms lose customers to friction and lose examinations to weak evidence. This guide covers document capture and verification, extraction with confidence, screening integration, risk scoring that supports rather than replaces analyst judgement, the perpetual-KYC extension, and the audit evidence an examiner will ask for.

Resume screening is the most regulated AI use case most companies attempt, and the one most often built without knowing that. This guide covers the automated employment decision rules that apply, structuring screening around job-related criteria rather than resemblance to past hires, bias testing across protected groups, notice and human review requirements, and the audit evidence you will be asked for.

Returns are expensive, emotionally charged, and full of policy edge cases that customers experience as arbitrary. This guide covers encoding returns policy as testable rules, deciding eligibility with reasons customers accept, detecting abuse without penalising ordinary customers, automating labels and refunds within limits, and using the conversation to keep the sale where an exchange would serve better.

Transaction monitoring generates more alerts than any team can clear, and the genuine cases sit in the queue behind them. This guide covers using AI to triage and contextualise alerts rather than replace the detection layer, reducing false positives with governance regulators accept, supporting typology detection, building investigator workflow, and the model risk documentation an examination will require.

Booking looks simple and is full of rules: who can be seen by whom, for how long, with what preparation, and what happens when someone cancels at short notice. This guide covers integrating with calendars and scheduling systems, encoding availability and eligibility rules, handling the conversation across channels, confirmations and reminders that reduce no-shows, and rescheduling without creating gaps.

Where is my order is the highest-volume question in commerce support, and answering it well means more than reading a tracking number. This guide covers integrating order management and carrier data, detecting exceptions before the customer notices, communicating delays honestly, offering resolution actions within policy, and handling the cases where tracking data is wrong or missing.

AI-native engineering builds systems around AI capabilities from day one—directed by specifications, verified by humans, and measured in production outcomes.

Content moderation fails when policy is vague, automation is trusted too far, or reviewers are treated as a cost line. This guide covers turning policy into a testable specification, tiering decisions by confidence and severity, designing review queues that protect reviewer wellbeing, handling appeals, and measuring the errors in both directions that matter.

Forms are where organisations move information from one place to another by hand, thousands of times a day, and an agent that fills them from source documents and systems removes exactly that work. This guide covers field mapping from a form's schema, sourcing values from documents and records with per-field confidence, validating against rules, confirming with a person before submission, and keeping an audit trail of where every value came from.

Magento runs complex catalogues with attribute sets, configurable products, and multi-store scopes that make automation valuable and error-prone. This guide covers integration tokens and ACL scoping, catalogue enrichment within attribute sets and store views, order and customer service operations, cache and index behaviour that agents must respect, and the workflows worth building first.

A chatbot that works in English and is switched on for other languages usually fails quietly in all of them. This guide covers language detection and switching, whether to translate or generate natively per language, building retrieval and evaluation sets per language, handling mixed-language and code-switched input, and escalating to human agents who speak the customer's language.

Summarization is the most requested and least rigorously built AI capability in the enterprise, because a summary that reads well can still be wrong. This guide covers defining summary types by their use, structuring output for each, handling documents longer than a context window, evaluating faithfulness rather than fluency, and running summarization as a shared service at a cost that scales.

WooCommerce runs a vast number of small and mid-sized stores on WordPress, where the owner is also the merchandiser, the support team, and the operations manager. This guide covers REST API key scoping, product enrichment and inventory workflows, order and customer service support, the plugin and hosting realities of small stores, and keeping writes safe on a live shop.

Image generation is easy to demonstrate and hard to run as a production capability, because the outputs carry brand, legal, and reputational weight. This guide covers constraining generation to brand guidelines, templating prompts so marketers do not write them, review and approval workflows, rights and provenance labelling, safety filtering, and the caching and cost patterns that make generation at scale affordable.