The automation glossary, in plain English.

AI agent

An AI agent uses a model to decide and carry out steps — calling tools, reading data, escalating when unsure — in pursuit of an objective. In business operations, a well-built agent has clear boundaries, grounding in your data, and a path to hand off to a human on low-confidence cases.

See: Respond to GoHighLevel leads instantly with an AI first-touch.

API (Application Programming Interface)

An API lets systems exchange data and trigger actions through a stable contract, rather than through a screen a human reads. Integrating at the API layer is more reliable than screen-scraping because the contract changes less often than the interface. Most modern SaaS tools expose an API for exactly this purpose.

Batch processing

Batch processing collects work and runs it together on a schedule — nightly reconciliation, a weekly report. It's efficient for work that doesn't need to be instant, and contrasts with real-time processing.

Business process automation (BPA)

BPA targets a complete process — order-to-cash, employee onboarding, month-end close — rather than a single step. It usually spans multiple systems and departments and includes the exception handling and approvals a real process needs. It is the broader discipline that individual workflow automations serve.

Churn

Churn measures lost customers over a period. Automation touches it indirectly — faster response, consistent follow-up, and reliable service all reduce the friction that drives customers away.

CRM (Customer Relationship Management)

A CRM is the system of record for customer relationships — who they are, where they are in the pipeline, and the history of interactions. Its value depends on the data being current, which is why CRM sync and enrichment are common automation targets.

See: Dedupe CRM contacts on a schedule, Enrich HubSpot contacts on create.

Data pipeline

A data pipeline carries data through a sequence of steps — collection, cleaning, transformation, delivery — on a schedule or in real time. Reliable pipelines are what let teams trust the numbers in their dashboards without manual assembly.

Data silo

A data silo is information locked inside a single tool or team, invisible to others who need it. Silos force manual copying between systems and prevent a unified view; breaking them is a core aim of integration work.

See: Systems that don't talk to each other.

Document AI

Document AI extracts fields from mixed layouts (different suppliers, scanned forms) and validates them, so information doesn't have to be re-keyed by hand. Good implementations flag low-confidence extractions for human review rather than guessing.

See: Re-keying the same data between tools, Capture supplier invoices from Gmail into Google Sheets, Extract data from Drive PDFs into a Sheet.

ERP (Enterprise Resource Planning)

An ERP centralises back-office processes — accounting, procurement, inventory, and more — in one system. Mid-market companies often need to integrate the ERP with their CRM and other tools, and that integration layer is a frequent source of manual work.

ETL (Extract, Transform, Load)

ETL pulls data out of one or more systems (extract), reshapes and cleans it (transform), and writes it somewhere useful like a warehouse or report (load). It's the backbone of automated reporting and analytics pipelines.

Exception handling

Exception handling routes the messy cases — an unfamiliar document, a low-confidence result, a mismatch — to a human or a defined fallback instead of forcing a guess through. It's the feature that separates automations that survive production from ones that quietly corrupt data.

See: Re-keying the same data between tools.

Human in the loop

Human-in-the-loop design has a person check or approve results at the points that need judgment, while the automation handles the repetitive work. Over time, as trust grows, that review can shift from gatekeeping to spot-checking.

Idempotency

Idempotency protects automations from duplicate processing — if a webhook fires twice or a job retries, the outcome stays correct. It's a small technical detail with big consequences for data integrity in unattended systems.

Integration

An integration wires one tool to another so information flows between them automatically. Integrations can be point-to-point (one link between two apps) or hub-based (many apps through a central layer); the second scales better as the number of tools grows.

See: Systems that don't talk to each other.

iPaaS (Integration Platform as a Service)

iPaaS provides pre-built connectors and a hosted runtime for integrations, so teams can sync data between SaaS tools without standing up their own infrastructure. It handles the well-behaved connections well; complex logic, edge cases, and reconciliation often still need custom work on top.

See: Systems that don't talk to each other.

Lead routing

Lead routing assigns incoming enquiries based on rules — territory, product, value, availability — so they reach the right owner fast instead of sitting unassigned. Paired with real-time alerts, it's how teams keep first response quick.

See: Leads that go cold before anyone follows up, Push form submissions into HubSpot with owner assignment, Route new HubSpot leads to Slack in real time.

Lead scoring

Lead scoring assigns a value to each lead based on signals like budget, intent, and source, so a team can prioritise its fastest attention on the most promising ones. It can be rule-based or model-based.

Lead-to-cash

Lead-to-cash spans marketing, sales, fulfilment, and finance — capturing a lead, closing it, delivering, invoicing, and getting paid. Because it crosses so many systems, the handoffs between them are a rich source of manual work and automation opportunity.

LLM (Large Language Model)

An LLM is trained on large amounts of text to predict and produce language, which lets it summarize, classify, extract, and draft. In operations it's the engine behind document understanding, drafting replies, and routing — but it needs guardrails and grounding to be reliable on real data.

Low-code

Low-code sits between no-code and full custom development: a visual builder for speed, with escape hatches to write real code where the logic demands it. It suits teams that want to move quickly but still need to handle non-standard cases properly.

No-code

No-code platforms use drag-and-drop builders and pre-made blocks so non-developers can assemble workflows. They're fast for standard, well-behaved processes. They can get brittle or expensive when a workflow grows complex, high-volume, or needs logic the platform wasn't designed for.

OCR (Optical Character Recognition)

OCR turns a scanned page or photo into characters a computer can process. It's often the first step in a document pipeline, with Document AI or an LLM interpreting the extracted text afterward.

Orchestration

Orchestration manages the order, timing, and dependencies of the steps in a workflow — including what happens when one fails. It's what turns a collection of individual automations into a dependable end-to-end process.

Quote-to-cash

Quote-to-cash covers pricing, quoting, contracting, invoicing, and collection. Automating the handoffs — quote approved to order created to invoice sent — removes re-keying and speeds up how fast a business gets paid.

RAG (Retrieval-Augmented Generation)

RAG retrieves relevant passages from your knowledge base and feeds them to the model as context, so answers are based on your actual policies, products, or records. It's how an AI support or knowledge assistant stays accurate to your business rather than making things up.

Real-time processing

Real-time processing acts on data as it arrives rather than waiting for a scheduled batch. It's the right choice when latency matters — routing a hot lead, alerting on a failed payment — and typically relies on webhooks or streaming.

Reconciliation

Reconciliation matches records across systems to confirm they line up and to surface the ones that don't. It's a major manual time sink in finance operations, and a common, high-return target for automation.

See: Month-end close stuck in spreadsheets, Reconcile Stripe payouts against Shopify orders, Reconcile Salesforce records against an external source nightly.

Retry logic

Retry logic handles the transient failures every integration hits — a rate limit, a brief outage — by trying again sensibly rather than dropping the work. Combined with alerting, it's the difference between a resilient automation and one that fails silently.

RPA (Robotic Process Automation)

RPA automates by driving the screen — moving the mouse, typing, reading fields — rather than calling an API. It's useful for legacy systems with no API, but it's fragile: a form redesign or layout change can break a bot. API-level integration is more durable where it's available.

See: Automations that break every time something changes.

Shadow IT

Shadow IT is the tools individuals or departments buy to get around a slow central process. It solves an immediate need but creates sprawl, security gaps, and data scattered across unmanaged systems.

Single source of truth

A single source of truth means a metric or record is defined and stored once, and everything else reads from it. Without one, teams reconcile conflicting numbers by hand and 'the same KPI' means different things on different dashboards.

See: Month-end close stuck in spreadsheets.

SLA (Service Level Agreement)

An SLA sets measurable expectations — uptime, response time, resolution time — that a provider commits to. For automations, monitoring against an SLA is how you know a system is actually meeting its promise rather than silently degrading.

Speed to lead

Speed to lead measures the time between an enquiry arriving and the first meaningful response. It's a strong driver of conversion — the first responder often wins — which is why fast, automated first-touch matters.

See: Leads that go cold before anyone follows up, Missed calls turning into lost customers.

Structured data

Structured data lives in a consistent shape — fields, types, tables — that software can process directly. Turning unstructured inputs (emails, PDFs) into structured data is often the first step that makes automation possible.

System of record

A system of record is the tool your business treats as the truth for something — the CRM for customers, the accounting system for finances. Clear systems of record prevent the 'which spreadsheet is real?' problem and make integrations far easier to reason about.

Technical debt

Technical debt accrues when systems are built fast or patched rather than built durably — brittle scripts, undocumented workarounds, tools bent out of shape. It shows up later as breakages and maintenance that crowd out new work.

See: Automations that break every time something changes.

Trigger

A trigger is the condition that kicks off a workflow — a new email, a form submission, a scheduled time, a status change. Every automation begins with one, and choosing the right trigger is half of designing a reliable workflow.

Unstructured data

Unstructured data is the messy majority of business information: emails, scanned invoices, chat logs. Extracting structure from it (via Document AI, OCR, or an LLM) is what lets it flow into automated systems.

Webhook

A webhook is a 'push' notification between systems: when something occurs (a form is submitted, a payment clears), the source system immediately calls a URL you control with the event data. It's the real-time alternative to repeatedly polling an API to ask 'has anything changed yet?'.

Workflow automation

Workflow automation chains together the steps of a recurring process — triggers, actions, and conditions — so it runs without manual effort. It covers everything from a single app-to-app trigger to a branching pipeline across many systems. The goal is to remove repetitive human handling from work that follows consistent rules.

See: Re-keying the same data between tools.