I find the one workflow you're still doing by hand that an AI agent should own — and I ship it in two weeks.

It starts with a fixed-price audit: I rank what's worth automating — and tell you what isn't. If something clears the bar, I build and ship it in two weeks, and the audit fee credits toward the build. You own what's built. No retainer, no lock-in.

Fixed-price audit as the way in Go/no-go before you commit to a build Audit fee credits toward the build You own the code & the runbook

The problem

The work that should be automated is the work no one has time to automate.

It's not that the tooling isn't there. It's that the people who could wire it up are the same people drowning in the manual workflow.

The pilot that never shipped

A weekend prototype that demoed well, then stalled the moment it had to survive real inputs. It never reached production.

The tax of doing it by hand

A recurring task someone copies, pastes, and re-checks every week — quietly eating hours that should go to the actual business.

No one to own the agent

You know an agent could do it. You don't have someone in-house who can scope it honestly, build it right, and hand it back working.

How the engagement works

Two steps, one gate between them.

You buy the audit first. The build only happens if the audit finds something worth building — so you commit on data, not on faith.

Step 1 / Workflow Audit

Workflow Audit

A standalone, fixed-price product — about four days. I inventory your workflows and rank them by automation ROI.

You always walk away with a ranked automation map and a clear go/no-go on whether anything is worth building. This is the low-commitment way in.

Step 2 / Build Sprint

Build Sprint

Only if the audit finds a viable target. Quoted separately, and the audit fee credits toward it.

About a week and a half: the agent is built audit-first and tested against the real workflow, then shipped with a runbook and walkthrough. You own it.

→ Commissioned only when a target clears the bar.

— decision gate —

This is the advantage, not a catch: you commission the build with data, not on faith. If nothing clears the bar, you keep the audit and stop here — no awkward refund, because the audit was its own paid deliverable.

The boundary is the offer

Two steps, each drawn tight.

Fixed scope only works if the edges are clear. Here's what each step delivers — and what's out of both.

What's included

  • A workflow inventory with ROI ranking Audit
  • A clear go/no-go recommendation, in writing Audit
  • One production automation — not a prototype, not a Zapier-zap-with-a-chatbot Build
  • A runbook and handoff so your team owns it Build
  • A delivery walkthrough call Build

What's out

  • A second automation — each build is its own sprint
  • A build with no greenlight from the audit
  • Ongoing maintenance or SLAs
  • Custom model training
  • Infra migration, security, or compliance work
  • Anything touching regulated data without a separate agreement

What you walk away with

A working agent — and everything you need to keep it.

No black box, no dependency on me. The sprint ends with your team able to run, change, and trust what was built.

01

A production agent, live

Deployed against your real workflow and tested past the happy path — not a demo waiting to break.

02

The audit, in writing

A ranked view of what's worth automating and what isn't — useful long after this one agent ships.

03

A runbook your team owns

How it works, how to run it, where to change it. Written so the next person doesn't need me.

04

The code, free and clear

You own what's built. No retainer, no per-seat license, no lock-in to keep it running.

Who it's for

You have one manual workflow and no one to own the agent for it.

Technical founders Small eng teams Solo SaaS operators Research labs

A recurring manual workflow, real stakes, and no in-house agent expertise — that's the fit.

How it works

A fixed-price audit first — then a build, only if it's earned.

Days 1–4 · Audit

Inventory → ranked map → go/no-go

I map where the manual time goes, rank your workflows by automation ROI, and hand you a written recommendation on whether anything is worth building — and what isn't.

— decision gate —

You commission the build with data, not on faith

If a target clears the bar, you greenlight the build and the audit fee credits toward it. If nothing clears the bar, you keep the audit and stop here — the audit was its own deliverable.

~1.5 weeks · Build (only if greenlit)

The agent gets built and tested

Audit-first, production-shaped. Tested against the real workflow, not a happy path.

End of build · Ship

It goes live and becomes yours

Deployed, documented, walked through — with a runbook and handoff. Your team leaves able to run it without me.

Why work with me

I ship production software, and I tell you the truth about ROI.

I'm Avery Karlin — a computational physicist and developer who builds systems that have to work on real data, not slideware.

I'm a master's student in Medical Physics at Columbia and an independent medical researcher, building and validating the imaging pipelines behind MRI-guided radiotherapy — work where a model that's confidently wrong isn't a bug, it's a dose error. That's the same discipline I bring to an agent: audit first, test against reality, and earn trust before it ships.

On my own I design and ship production tools end to end — PrismTask, Gamemasters Assistant, and Anneal Ambiance — so I know what it takes to make software that survives real users, not just a demo.

This engagement is delivered through Annealing Signet Institute Inc. I'm taking on a small number of founding clients at the introductory rate below — which is part of why the offer is scoped this tightly.

How I keep it low-risk

The audit comes first — so you decide before you commit to a build.

Honesty before code

If the audit shows nothing clears the ROI bar, I say so. You leave with the ranking and a clear answer — not a build you'll regret.

Small fixed fee to find out

The audit is a fixed price — a small commitment to learn what's worth building, instead of a large fee on faith. The build is quoted separately and the audit fee credits toward it.

No lock-in

You own the code and the runbook. No retainer to keep it alive, no dependency on me after handoff.

Questions

The things worth asking before a call.

What kind of workflows is this for?
Recurring, mostly-manual work with clear inputs and a clear definition of "done" — triaging and routing inbound messages, pulling and reconciling data across tools, drafting structured documents, monitoring and summarizing, research-and-extract loops. If a capable person could explain it in a call, an agent can probably own it.
Why split it into an audit and a build?
Because it lets you commit a small fixed fee to find out what's worth automating, instead of a large fee on faith. The audit is its own paid deliverable — a ranked map and a go/no-go — so the build only gets commissioned when there's a target worth it. If nothing clears the bar, you keep the audit and stop; no awkward refund.
How much does the audit cost, and what about the build?
The audit is a fixed price, set as the low-commitment way in. The build is quoted separately — only if the audit finds a viable target — and scoped against your real constraints on the call. If you proceed, your audit fee credits toward the build. We keep dollar figures off this page and settle them on the scoping call.
What if the audit says nothing's worth automating?
Then that's the deliverable, and it's a good one. You leave with a written ranking of your workflows by ROI and a clear answer on where AI does and doesn't help — which is worth far more than a build that was never going to earn its keep. The audit is its own paid product, so the build simply never gets commissioned — nothing to refund.
What do you build it on?
Production-grade LLM tooling, wired into the systems you already use — your data sources, your APIs, your stack. The aim is something your team can run and change, not a proprietary platform you have to rent. Specifics get decided in the audit, against your real constraints.
What happens to my data?
We scope data access to exactly what the workflow needs, and nothing more. Anything touching regulated or sensitive data is handled under a separate agreement before any work starts — it's explicitly out of the base scope so the boundary stays clear.
Do you offer ongoing support or maintenance?
Not as part of the build — you own the code and the runbook, so you're not dependent on me to keep it running. If you want a maintenance arrangement or a second automation later, that's a separate conversation. Each build is its own sprint.
Who is Annealing Signet Institute Inc.?
It's the entity this consulting work is delivered and contracted through. The work is mine — Avery Karlin — and Annealing Signet is how it's invoiced and engaged.
How do we start?
Book a 20-minute call to scope your audit. No prep needed — we figure out live whether there's a workflow worth auditing. If there is, we set the audit scope and dates. The build is a decision you make later, with the audit in hand.

Pricing

A fixed-price audit to start. The build is quoted against your scope — and your audit fee credits toward it.

You buy the audit first: a fixed price to find out what's worth automating, with a go/no-go you can act on. If a target clears the bar, the build is scoped against your real workflow — and the audit fee comes off it. The figures above are introductory founding-client rates.

Fixed-price audit Audit fee credits toward the build Introductory founding-client rate You own the code

Start here

Let's find the workflow worth auditing.

A 20-minute call, no prep, no pitch deck. We look at where the manual time goes and decide together whether there's a workflow worth a fixed-price audit. Worst case, you get a sharper read on where AI fits your operation.