ET Ethos Tech / ethos-tech.ai

What we do

We take on the whole problem

Not advice by the hour. We scope it, build it, and ship it — with a small senior team on the work the whole way. Below is what that actually looks like.

AI use-case design & agentic systems

Most AI projects fail because nobody found a problem worth solving. We start in your data, pick the use case that actually moves a number, and build the system around the model — the context it sees, the checks that catch it, the gates that keep a human in control.

What you get

  • Use-case scoping and prioritization, grounded in your numbers
  • Architecture: context design, verification layer, human approval gates
  • A working system running in your stack — not a prototype
  • Runbook and handoff so your team can operate it

Good fit when

You want AI leverage on a recurring, customer-facing task, but you can't let an unsupervised model touch a customer.

CS org buildout & transformation

Stand up a customer-success organization, or rebuild one that has stopped working. The operating model, the workflows, the tooling, and the quality bar that turn post-sales from a cost center into a retention engine.

What you get

  • Operating model and account segmentation
  • Playbooks and workflows people will actually follow
  • Health scoring and the retention motion around it
  • Tooling selection, rollout, and enablement

Good fit when

Retention is leaking, CS is reactive, or you are scaling post-sales for the first time.

Cloud-migration & platform programs

Own a complex migration or modernization program end to end — through the hard middle, where most of them stall. Scoping, sequencing, and the cross-functional coordination that keeps technical delivery tied to a business outcome.

What you get

  • Discovery, sequencing, and a defensible plan
  • A migration playbook your teams can repeat
  • Delivery cadence, risk tracking, and escalation that works
  • Cutover planning and the validation gates around it

Good fit when

A program is stuck, or you need one person accountable for the whole thing rather than five vendors.

Retention & growth systems

Find where you are quietly losing ground, then build the motion to fix it — data, process, and tooling together. Not a dashboard nobody opens: a system that changes what people do on Monday.

What you get

  • Analysis of retention and expansion signals in your own data
  • The motion: who does what, when, and on what trigger
  • Instrumentation so the effect is measurable
  • The operating cadence to keep it alive

Good fit when

The numbers are drifting and nobody can point at exactly why.

Engagement models

Sized to the problem, not to a retainer

Full project

A defined build, scoped and shipped. Typically several weeks to a few months, with a clear done.

End-to-end program

We own a multi-workstream program through delivery — the coordination as much as the building.

Fractional advisory

Senior judgment on tap when a full build isn't the right size. Roughly 10–20 hours a week.

How we work

Four commitments, on every engagement

  1. Problem first, from the data. We find the business problem in your numbers before anyone picks a technology.
  2. Human-gated. Nothing customer-facing ships without a person approving it. That is what makes an agentic system safe to run.
  3. Verifiable. A separate checker re-derives the evidence behind a claim. "Done" is a proof, not a vibe.
  4. Ship over slideware. You get a working system and the runbook to operate it, not a deck describing one.

Want the long version? Read a reference architecture that worked pretty ok — the stages, what the verification layer caught, and what we'd change.

Let's talk

Book the builder

No forms. No qualification call. Pick a time and we'll talk about your actual problem.

Grab a time →

Prefer email? jeremy.brazell@ethos-ai.tech