Solutions Architect
Conduct a technical discovery session with a customer
What You Do Today
Interview their technical team, map current architecture, understand integration requirements, identify risks and dependencies
AI That Applies
AI generates discovery question frameworks, transcribes and summarizes sessions, maps discussed architecture in real time
Technologies
How It Works
The system ingests customer interaction data — transactions, communications, behavioral signals, and profile information. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — discovery question frameworks — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
Better-prepared discovery sessions with comprehensive question frameworks. Architecture captures in real time
What Stays
Reading the room for unspoken constraints, knowing which questions reveal the real architecture vs. the aspirational one
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for conduct a technical discovery session with a customer, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long conduct a technical discovery session with a customer takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your VP Operations or COO
“How would we know if AI actually improved conduct a technical discovery session with a customer — what would we measure before and after?”
They're prioritizing which operational processes to automate
your process improvement or lean lead
“If we automated the routine parts of conduct a technical discovery session with a customer, what would the team do with the freed-up time?”
They understand the workflow dependencies that AI tools need to respect
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.