The five questions every buyer asks before hiring us. Answered in public.
We publish the answers we would otherwise give you on the first call. If any of them are disqualifying, it is better to know now. If they are the ones that close the deal, you can send your team straight to a scheduled conversation.
Why you instead of a Big 4 consultancy?
Senior engineers own the work from first call to handoff. No layered pass-offs, no junior pyramid, no quarterly deck cycle.
Big 4 firms are strong on strategy decks and cross-functional change programs. They are expensive when your problem is shipping a single working workflow in weeks, not restructuring a department over a year.
Every engagement here is run by an engineer who has shipped the same class of work before. You are talking to the person writing the code, not the partner who writes the proposal.
If your project genuinely needs the Big 4 footprint (global rollout, multi-year transformation, heavy regulatory overhead), we will say so on the first call. Not everything fits our shape, and we are honest about that.
Why you instead of DIY with ChatGPT?
ChatGPT is the easy part. The hard parts are choosing what to automate, governing the data, measuring ROI, and keeping it running.
A single team member using ChatGPT is a productivity gain. A company relying on informal ChatGPT use is a risk register waiting to fire.
The work we do sits around the model: permission remediation before rollout, evals that prove the output is correct, observability that catches drift, and hour-saved measurement the board can read.
If your workflow is simple enough that one person with a ChatGPT subscription solves it, you do not need us. When it crosses into multi-user, multi-system, compliance-touching territory, that is where we ship value.
What happens if the automation does not save hours?
We baseline before we ship and measure after. If we do not hit the target, we fix it, not you.
Every engagement starts with a current-state baseline: hours spent, error rates, handoff latency, whatever matters. The number is agreed in writing, not inferred afterwards.
Post-launch, we measure the same metrics for the hypercare window. If we miss the target, remediation is our scope to run, at our cost, until the number lands or we mutually agree the workflow is not a fit for AI. We do not walk away from a missed target.
No work we ship leaves your team dependent on us. Every deliverable is documented so your operators can own it without us.
Who owns the work when you leave?
You do. Code, prompts, agents, evals, dashboards, and runbooks are yours from day one and documented for handoff.
There is no vendor-lock scaffolding in our deliverables. No proprietary workflow runtime, no proprietary model wrapper, no "only GlobalAdmins can maintain this" hooks.
Every engagement closes with a handoff package: runbook, eval suite, observability dashboards, and named owner on your side. A senior engineer of yours can take over the work without re-engaging us.
If you want us to stay on via managed services, that is a separate conversation with a clearly-scoped contract. Staying is a choice, not a dependency.
How do we know the proof on the site is real?
Our published case studies are composite examples. The specifics of any real engagement we can share only with a signed reference call.
We do not publish named client logos or testimonials without the client explicitly approving it for public use. Most of our clients prefer to keep the engagement private, and we respect that.
On the first call, we can share representative proof at the specific workflow level: "here is a similar Copilot rollout for a 120-person firm, here is what we measured, here is what the handoff package looked like." If fit looks strong and you want a reference call, we can arrange one with a client who has opted in.
The site is deliberately honest about this trade-off. Fake or anonymized testimonials are the single fastest way to burn trust with a mid-market buyer, so we do not use them.
When we are a fit
We work best with operators who want fewer vendors, not more.
If any of the points below sound off, that is useful information — for both of us.
Strong fit
- 5 to 500-person operations team with recurring work costing hours a week
- Microsoft 365 or Google Workspace as the primary backbone
- Fixed scope, fixed price preferred over hourly billing
- Willing to baseline the current process and measure the delta
Weak fit
- Multi-year, multi-function transformation program at enterprise scale
- A problem that is pure strategy, with no shipping component
- Expectation of open-ended time-and-materials billing
- No internal owner to carry the work post-handoff
Still have a question we did not answer?
Twenty minutes is usually enough to confirm fit in both directions. No drip sequence, no follow-up spam.