AI systems that take action, not just produce text. Unlike a chatbot that answers a question, an agentic system can run a workflow end-to-end — calling tools, querying data, making decisions within defined boundaries, and completing multi-step tasks without a human in the loop at every step.
An operating model where agentic AI systems run core business functions in production — finance, operations, marketing — rather than sit alongside the business as a tool or recommendation engine. This is the category WExIQ operates in.
A deployed application built around one or more AI agents. An agentic system has a defined scope, integrates with existing software, follows business rules, and produces auditable outcomes. It is infrastructure, not an app you use.
A 60-minute working session where WExIQ maps one process a client wants taken off their plate, identifies the highest-leverage point to apply an agentic system, and gives an honest go / no-go recommendation. No slide deck.
A neural network trained on very large text corpora to generate and understand language. LLMs are the core reasoning engine of most modern agentic systems, though a production agentic system is more than just an LLM — it includes tools, rules, integrations, and monitoring.
A software entity that perceives its environment, decides on actions, and takes them — typically using an LLM as its reasoning engine plus a set of tools it can call. An agent differs from a chatbot by being goal-directed rather than conversational.
The capability of an LLM to invoke external software functions — such as querying a database, sending an email, or updating a CRM record — as part of completing a task. Tool use is what turns a language model into a functional agent.
A technique where an AI system retrieves relevant documents or data from a knowledge source and includes that information in its reasoning. RAG grounds an agent's outputs in specific business data — customer records, contracts, policies — rather than relying only on the model's training.
A large, general-purpose AI model — such as Claude, GPT, or Gemini — trained once and then adapted to many downstream tasks. Agentic systems typically use a foundation model as the underlying reasoning engine.
The process of running a trained AI model to produce outputs from inputs. When an agentic system responds to a workflow event, it is running inference. Inference cost and latency are meaningful factors in production deployments.
An open standard for connecting AI systems to external tools, data sources, and applications. MCP lets agents plug into existing business software (ERPs, CRMs, internal tools) through a uniform interface, rather than a one-off integration per connection.
A senior finance professional who serves multiple businesses part-time as their chief financial officer, providing C-suite-level financial leadership without the cost or commitment of a full-time hire. Common at growth-stage small and mid-sized businesses.
The finance process of finalizing the prior month's books — reconciling accounts, posting adjustments, and producing financial statements. For many growth-stage companies, month-end close takes five to ten business days; agentic systems can compress it meaningfully.
The ability to see, in near-real time, how cash is moving through the business — receivables, payables, burn, runway, and projected balances. Poor cash flow visibility is one of the most common operating pains at growth-stage SMBs.
Paid marketing where spend is tied directly to measurable outcomes — clicks, leads, or customers — and optimized continuously against those outcomes. Distinct from brand marketing, which builds long-term recognition without per-unit accountability.
The function responsible for producing qualified prospects who enter the sales pipeline. Lead generation encompasses the channels, systems, and measurement that move a stranger toward becoming a customer.
The operational function that aligns marketing, sales, and customer success around shared systems, data, and processes. RevOps owns the revenue tech stack — typically CRM, automation, attribution — and the workflows that connect it.
The software system that runs a business's core operational and financial workflows — general ledger, accounts payable and receivable, procurement, inventory, and reporting. Examples include NetSuite, SAP, Microsoft Dynamics, and QuickBooks Enterprise.
The software system that tracks customer and prospect interactions — accounts, opportunities, tasks, email and call history. Examples include Salesforce, HubSpot, and Pipedrive.
Software that runs real work for real users in a live environment — as opposed to a prototype, demo, or sandbox. A production system is monitored, versioned, and subject to change management. WExIQ delivers production systems, not prototypes.
The practice of codifying a business process into rules a machine can execute end-to-end. Traditional workflow automation uses deterministic logic; agentic systems extend this by handling exceptions, unstructured inputs, and judgment calls that would otherwise require human review.