AI Agent Readiness & Process Mapping for Agentic Workflows | ClearWork (Part 1)

Agents fail when they don’t understand the business. Fix that first.

ClearWork maps real workflows, exceptions, and handoffs using AI-led discovery—then turns it into machine-readable requirements and delivery-ready artifacts so your agents launch with context, guardrails, and clarity.

Real workflows (not the happy path)
Define decision points + exceptions
Evidence-linked outputs
Start in days (no complex integrations to begin)
ClearWork prepares agent deployments by mapping workflows, exceptions, and handoffs.

Why agent deployments stall (or go sideways) after the demo

Most agent pilots look great in a sandbox. Production is different: messy workflows, edge cases, unclear permissions, and “wait… who approves this?” moments.

  • Missing context

    The agent doesn’t know how work actually happens across teams.

  • No exception handling

    Real work is full of edge cases and workarounds.

  • Undefined handoffs

    The “agent vs human” boundary is fuzzy until something breaks.

  • Unclear action space

    Agents need tightly scoped tools and permissions to reduce risk.

  • Hard to measure readiness

    Without eval criteria and tracing, you can’t confidently launch.

"If your agent needs tribal knowledge to succeed… it’s not 'agent-ready' yet."

Outcomes

What changes in the first 30 days

Faster path to agent readiness

  • Capture process truth asynchronously (without the scheduling nightmare)
  • Move from “idea” to a scoped agent plan in days

Clear guardrails + safe scope

  • Define decision points, exceptions, and human-in-the-loop checkpoints
  • Reduce risk by scoping what the agent can do (and what it can’t)

Requirements your builders can actually use

  • Translate discovery into structured, machine-readable requirements
  • Create consistent artifacts your team can test, evaluate, and iterate on

Fewer surprises in production

  • Align business + IT before build begins (handoffs, approvals, exceptions)
  • Improve traceability for debugging and governance
ClearWork Agent Readiness Collage

ClearWork dashboard showing generated artifacts & collaboration capabilities

How It Works

How ClearWork makes you agent-ready

STEP 01

Discover the real workflow

Assign AI-led interviews to the people who do the work. Collect text, voice, and screen walkthroughs. Upload SOPs, tickets, and docs. ClearWork turns scattered inputs into a structured view of the workflow—across roles, systems, and variations.

Interview UI
Process Map with decision points
STEP 02

Define decision points, exceptions, and handoffs

ClearWork maps the workflow with the details agents need: decision points, edge cases, and where a human should review or approve. This is where you draw the line between agent actions and human oversight.

STEP 03

Translate into build-ready requirements

ClearWork converts discovery into structured outputs your teams can build and test: machine-readable requirements, task lists, artifacts, and documentation—ready to export into delivery workflows and use as the foundation for evaluation and monitoring plans.

Requirements View

Your Agent Readiness Pack (generated from discovery)

This is the stuff teams scramble to create after a pilot breaks. ClearWork helps you generate it up front—grounded in real inputs.

Workflow map

How work actually happens, including variations.

Decision points & exceptions

Where the workflow branches and why.

Human/agent handoff map

Where humans review, approve, or take over.

Machine-readable reqs

Structured requirements your builders can implement.

Agent scope draft

What the agent does, doesn’t do, and escalation rules.

Acceptance criteria

Scenarios that represent real process variations.

Policy & guardrail checklist

Draft guardrails aligned to the workflow’s risk points.

Artifact repository

Living docs: SOPs, diagrams, and narratives.

Risk & gap register

What’s unclear, missing, or disputed—flagged early.

Stakeholder alignment

Who confirmed what (and where input conflicts exist).

clearwork_agent_pack.app
Gallery carousel
Traceability

Outputs you can defend (because you can trace them)

ClearWork doesn’t create “agent plans” from assumptions. Every requirement, decision point, and workflow step can be traced back to source inputs—interview answers, screen walkthroughs, or uploaded documents—so teams can validate scope and reduce risk before deployment.

  • Trace outputs back to source evidence
  • Spot missing context early
  • Reduce rework and scope churn
Artifact with evidence links
AI Agent Readiness & Process Mapping for Agentic Workflows | ClearWork (Part 2)
Handoff map with HITL markers

Governance starts with clarity
(not after the incident)

Enterprise teams are building governance around agents: approvals, scoped permissions, human review checkpoints, and auditability. ClearWork gives you the process truth needed to put those controls in the right places—before you deploy.

Scoped action space

Define where the agent can act, which tools it can use, and what requires escalation.

Human-in-the-loop

Identify the exact steps where a human should review, approve, or override.

Least privilege access

Document what access is required for each step so security can enforce least privilege.

Readiness criteria

Create a shared checklist for “ready to launch” based on workflow scenarios.

Hand it to delivery without losing the plot

ClearWork turns discovery into structured outputs your builders can actually use. Export epics, stories, and tasks into Jira, and keep supporting artifacts connected to the same project context.

Jira Export

  • Export epics, stories, and tasks with consistent hierarchy
  • Reduce rework caused by missed or assumed requirements
  • Keep artifacts linked to discovery context for quick validation
Jira Config

Great for the workflows agents actually touch

If the workflow has handoffs, exceptions, and approvals… it needs process truth before automation.

Customer support triage

Define escalation rules and exception handling

IT service workflows

Scope actions, approvals, and safe tool usage

Finance operations

Approvals, controls, and auditability

Sales ops & CRM workflows

Handoffs across teams and systems

Procurement

Decision points and policy-aligned actions

HR operations

Sensitive steps with clear human review points

FAQ

No. ClearWork is the discovery + process intelligence layer that prepares workflows and requirements so agents can be deployed safely and successfully.

Because production workflows include exceptions, handoffs, approvals, and constraints that aren’t captured in a demo.

It means you have mapped real workflows, defined decision points and exceptions, and translated them into structured requirements with clear human/agent boundaries.

Text, voice, screen walkthroughs, and uploaded docs (SOPs, slides, PDFs, and more).

Workflow maps, decision points, handoffs, machine-readable requirements, and delivery-ready artifacts.

ClearWork helps you identify scope boundaries, HITL checkpoints, and least-privilege requirements based on the real process.

You can start in days because you can begin with interviews and documents before deep integrations.

Yes—export epics, stories, and tasks to your delivery workflow.

No. Data sent to third-party AI providers is NOT used for model training. We enforce zero client-side AI API exposure and complete encryption.

Ready to deploy agents that actually work in the real world?

Start with process truth. Then build with guardrails.
Book a demo and we’ll map how ClearWork fits your next agent deployment.