Inteq Agentic AI Consulting - Stage 3

What must the agent do - what decisions can it make - and what knowledge can it access?

Inteq works with your team to identify and define agent reasoning, responsibilities, decision boundaries, and enterprise knowledge access so agents are explainable, controllable, and trusted - enabling reliable performance in real operational environments.

A short exploratory conversation to confirm fit, scope, and what should happen next.

Stage 3 — requirements Analysis

Agents fail in production when responsibilities are vague, knowledge is unreliable, or decision rights are unclear. This engagement defines what the agent is accountable for, how it reasons, and how it accesses enterprise knowledge - with controls that leadership can defend.

 

What we define: the agent’s role, responsibilities, and operating boundaries - including what it can decide, recommend, or execute.

What we design: enterprise knowledge access using techniques such as Retrieval-Augmented Generation (RAG) - including sources, context rules, grounding, and explainability.

What you get: requirements and knowledge design artifacts that enable reliable development and governance - reducing ambiguity, hallucination risk, and operational failure.

• ✓Agent role definition (responsibilities, triggers, outcomes)
• ✓Decision-rights & control design (approve, execute, escalate)
• ✓Requirements & interaction design (human-in-the-loop patterns)
• ✓Knowledge design (sources of data, retrieval rules, grounding)
• ✓Explainability, auditability, and guardrail requirements

• ✓Agent Responsibility Map (roles, tasks, reasoning, triggers, outputs)
• ✓Decision boundary & escalation model (controls and approvals)
• ✓Agent requirements package (functional + non-functional)
• ✓Data (structure and unstructured) blueprint (sources, retrieval rules, evaluation plan) 

• ✓Reduces ambiguity that causes rework, delays, and failed pilots
• ✓Improves trust with explainable behavior and grounded answers
• ✓Enables governance by defining decision rights and controls early
• ✓Reduces hallucination risk via intentional knowledge access design
• ✓Creates a repeatable pattern for scaling multiple agents reliably

• ✓You have an agent idea but cannot clearly define its responsibilities
• ✓You need decision boundaries, approvals, and escalation paths
• ✓You are concerned about hallucinations or unreliable knowledge access
• ✓You need requirements that your team or partners can build from
• ✓You want a trusted RAG design pattern you can reuse at scale

Trusted agents require more than good prompts. This engagement defines responsibilities, decision boundaries, and grounded knowledge access - so your agents are reliable, governable, and ready for enterprise adoption.