Framework
Is Your Problem Ready for an AI Agent? (Quick Read)
A concise RADAR guide for evaluating if a workflow is ready for agent-based AI in production.
4 min read · 2025-01-22
Read ?I help mid-market financial services firms build AI on top of their existing CRM — so their teams move faster, stay consistent, and stay audit-ready. I embed with your team, build the thing, and leave it working in production.
No retainer. No roadmap decks. A working system.
Most AI projects in financial services do not fail because of the technology.
The decision logic was inconsistent before the agent was built. The agent inherited and scaled the inconsistency.
Policy records in spreadsheets. Duplicate client records. No single source of truth. The agent could not be smarter than what it was given.
The AI made a pricing recommendation. The client asked why. Nobody could answer. The deal paused. Trust was damaged.
These are solvable problems — if you diagnose them before you build, not after.
WHAT I DO
2 WEEKS
Before you build anything, understand what is actually ready. I run your CRM workflows through the RADAR framework — a diagnostic that tells you which processes are agent-ready and which need work first.
You leave with a prioritised build plan and a clear business case.
4 TO 6 WEEKS
I embed with your team, understand your CRM setup and data state, and build a specific AI agent or automation. I leave it running in production with your team trained on it.
You leave with a working system, not a recommendation.
ONGOING / MONTHLY
For firms that want a thinking partner on their broader AI and CRM strategy. One day per month, available for design reviews, vendor evaluation, and architecture decisions.
Architect-level thinking without the full-time hire.
THE FRAMEWORK
Most companies ask whether AI can do something. The better question is whether the problem is ready for AI to do it well. RADAR is a diagnostic framework for exactly that, built from real implementations, not theory.
RADAR readiness score
Score each dimension 1 to 5
Total: 0 / 25
Process clarity
Is the decision consistent and explainable today?
Revenue risk: pricing exceptions handled differently by every rep
Data readiness
Are inputs clean, structured, and accessible?
Revenue risk: duplicate CRM data, no golden record
Decision boundary
Can you define where reasoning starts, stops, escalates?
Revenue risk: contract exceptions with no defined edge cases
Recovery tolerance
If wrong, what breaks and how fast do you find out?
Revenue risk: agent ran 100x credits with no guardrails or circuit breaker
Explainability
Can the agent show its reasoning in business language?
Revenue risk: pricing recommendation disputed and nobody could explain why
WHY THIS WORKS
I have spent years working across CRM implementations — seeing where they succeed and more importantly where they fail. The failure patterns are consistent. The solutions are architectural, not technical.
I am also building a financial services practice of my own — which means I am not a consultant looking into your industry from the outside. I operate in it. I understand the compliance requirements, the advisor workflows, and the client relationship dynamics that make or break any technology implementation.
I work on contract, embedded with your team. No large firm overhead. No junior staff on your account. You get the person you spoke to doing the work.
LATEST THINKING
Framework
A concise RADAR guide for evaluating if a workflow is ready for agent-based AI in production.
4 min read · 2025-01-22
Read ?Framework
Most companies ask whether AI can do something. The better question is whether the problem is ready for AI to do it well. Introducing the RADAR framework.
8 min read · 2025-01-15
Read ?That is exactly the right question to start with. Book a 30-minute call and we will work through it together — no pitch, no proposal, just an honest conversation about what makes sense.
Book a 30-Minute CallOr email directly: hello@decisionlayer.ca