The AI Tool Stack Audit is for companies who have accumulated AI tooling faster than they've rationalized it. Most engagements start with a leadership team that's noticed the AI line item climbing and isn't sure whether the spend is justified.
In two weeks, we map every AI tool in use, model the cost vs. the value, talk to the people actually using them, and recommend the leaner stack that does what you need. You leave with a clear before/after picture and a prioritized migration plan.
What this isn't
It's not a procurement audit. We don't renegotiate contracts.
It's not a transformation engagement. We don't try to remake how your company uses AI; we just rationalize what you're already doing.
It's not a sales pitch in disguise. We don't sell tools, and we don't take vendor referral fees.
What you walk away with
A two-page executive summary your CFO can read in five minutes. A stack diagram showing what's in, what's out, and what's replacing what. A migration plan that respects your team's bandwidth. And a 30-day support window for the follow-up questions that always come up.
Engagement constraint
We run two of these per month, max. If the calendar is full, we'll tell you the next slot.
Who this is for
- Companies running 5+ AI SaaS tools and unsure which are actually pulling weight
- Teams whose AI spend is creeping up faster than the value they get from it
- Engineering or operations leaders who inherited an AI stack and want a clean reset
- Founders who said yes to too many AI vendor pitches in 2025 and need to rationalize
What's included
- Inventory of every AI tool, model, and integration currently in use
- Cost-vs-value model on every line item, with vendor pricing analysis
- Workflow review with the teams actually using the tools, not just the buyers
- Recommended stack with specific tool names, sizing, and integration paths
- Migration plan with priority order and effort estimates
- 30-day post-engagement support window for follow-up questions
Process
- 01 Discovery (Days 1–3)
Kickoff call, access to billing and tool admin panels, interviews with 4–8 actual users across teams. We map the current state without judgement.
- 02 Analysis (Days 4–8)
Cost modeling per tool, usage analysis, gap identification, redundancy detection. We benchmark against alternatives and current best-of-class options.
- 03 Recommendations (Days 9–12)
Draft of the recommended stack with pricing, integration paths, and migration order. Reviewed with you, adjusted based on constraints we missed.
- 04 Handover (Days 13–14)
Final deliverables, recorded handover walkthrough, written migration plan. Then a 30-day window for follow-up questions.
Deliverables
- Current-state stack diagram with cost-per-tool and usage signal
- Recommended-state stack diagram with vendor names and sizing
- Side-by-side cost comparison (current vs. recommended)
- Prioritized migration plan with effort estimates
- Recorded handover session for stakeholders not in the room
FAQ
- How much can we expect to save on AI spend?
- Most audits find 25–40% in either direct savings or capacity expansion at the same spend. Some find more. The gain comes from killing redundant tools, downgrading where you're paying for capability you don't use, and switching providers where cost-per-token has moved meaningfully.
- Will you recommend tools you have affiliate relationships with?
- We disclose every affiliate relationship in the deliverable. Recommendations are based on fit, not on which vendors pay us. If the right tool for you is one we don't have a relationship with, that's the one we recommend.
- What if our team doesn't want to migrate after the audit?
- Fine. The audit's value is the visibility, not the migration. Many clients act on a subset of recommendations and leave the rest. The deliverable is durable; you can revisit later.
- Is this a fit for very small teams (under 10 people)?
- Usually not. Below that scale, the audit costs more than the savings. We'd point you at the Best AI setup for your company engagement instead.