Phase 1 of 4: Discovery & Audit
We show up and
map the territory.
No kickoff theater. No alignment workshops. You tell us what you want to fix, change, or add. We find out what you actually have and how it actually works. Then we build a roadmap based on reality, not assumptions.
How Phase 1 works
Two tracks. Running at the same time.
Most discovery engagements are one thing: meetings. Ours are two things running in parallel. We map your technical environment with the same rigor we use to talk to your people. Both matter. Neither is optional.
Technical Discovery
AI agents assist. Humans verify.
We map everything that is running. Infrastructure, services, products, and how they connect. AI agents can automate a large portion of this work: scanning environments, cataloging services, tracing dependencies. We use them. But we also verify. Automated discovery finds what is there. It does not always find what matters or why.
- Infrastructure map: servers, cloud resources, on-prem systems, everything running
- Service map: what services exist, how they communicate, what they depend on
- Product map: the tools, platforms, and systems your organization runs on
- System and service topology: one artifact that shows the full technical lay of the land
- Data source inventory: where your data lives, what it is, who owns it
- Integration audit: what connects to what, how, and how reliably
Human Discovery
AI cannot do this part.
We sit with your people. Not to sell them on AI. To find out what they actually do and how they actually do it. The org chart is not the workflow. The documented process is not the real process. The tribal knowledge that lives in someone's head and never got written down is often the most important thing we find. This is why Phase 1 requires conversation.
- Workflow mapping: how work actually moves through the organization
- Process discovery: what gets done, by whom, in what sequence
- Tribal knowledge capture: undocumented processes, workarounds, and exceptions
- Pain point identification: what is slow, broken, manual, or error-prone
- Goal clarification: what you actually want from AI versus what you think you want
- Constraint inventory: compliance requirements, security boundaries, political realities
The key deliverable
Your topology is not a diagram.
It is a decision tool.
A lot of discovery engagements end with a PowerPoint that describes what everyone already knew. That is not what we produce. Your system and service topology is a precise, technical artifact that shows exactly what you have, how it connects, and where the gaps are. It tells us where your existing investment is working and where it is not.
We build on what you have wherever we can. This is how we find out what that is.
What this produces
Concrete deliverables. Not a deck.
Discovery closes with a set of artifacts that drive every decision we make from here. These are not recommendations. They are specifications.
- Infrastructure Map. Servers, cloud, on-prem. Every resource running, owned, and configured.
- Service Map. Every service, how they communicate, what they depend on.
- Product Map. CRM, ERP, internal tools, SaaS. The platforms you actually run on.
- System & Service Topology. The synthesized artifact. Infrastructure, services, and products as one map.
- Workflow Documentation. How work actually moves. Not the org chart. The real process.
- Gap Analysis. What to fix, uplift, or add. Versus what currently exists.
- Build Roadmap. Prioritized plan for Phases 2, 3, and 4. Built on what you already have.
Start with the assessment.
The AI Readiness Assessment tells you where you actually stand across infrastructure, data, systems, and AI. Free. 5 minutes. It is Phase 1 compressed into a score.