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AI & SOFTWARE FOR BUSINESSFOUNDERS · TEAMS · OPERATORS

Make AI useful
in your business.

Find where AI helps, build it in, and leave you software you can run. Most projects start with a short sprint.

New to AI or past the demo stage.
Bring the real problem.

SEE HOW WE START↓
✳ WHAT THIS IS

Less theory.
More working software.

A small engineering company. We decide if AI belongs in your work, build the useful parts, and hand them over.

01 / HOW YOU START

A short sprint.
A result you can judge.

Fixed scope. Fixed fee.
One problem, then you decide what’s next.

THE ENGINEERING SPRINT

Pick one problem.
Fix something real.

Learn how the work happens, build one improvement in your stack, and leave you something you can keep. Not a deck.

FORMATFixed scope
WHO LEADSHands-on senior engineer
Code, docs, and handover. Scope, timeline, and fee agreed up front.
01

Understand the problem.

How work happens now, what’s broken, what better looks like. Tools come after.

SHARED PICTURE OF THE WORK
02

Build the useful part.

Ship one improvement you can use. Short loops. Decisions in the open.

WORKING SOFTWARE & DEMOS
03

Hand it over.

You review against the scope. You keep the code and a plain plan for next steps.

CODE, DOCS & NEXT STEPS
02 / WHAT WE DO

From first questions
to shipping code.

Still figuring out AI? Already building?
We start where you are.

Start with a question
or something half-built.

FROM IDEA TO FIRST PROOF
01How you work today
02Where AI might help
03A small working proof
↗A clear yes / no / next

Not sure if AI fits? We look at how you work, pick one place it could help, and build a small proof before a bigger spend.

  • +Map workflows and pain points
  • +Where AI helps (and where it doesn’t)
  • +A first useful prototype
  • +Plan for cost, risk, and next steps
03 / RESULTS

What people said.
What changed.

Testimonials and outcomes from published customer stories. Each one links to the original source.

01Workflow consolidation
LitmusRead story ↗

“Having messaging, chat, and help articles in one place has been a lifesaver. We can finally see the big picture instead of stitching reports from three tools.”

Taylor DavisSenior Director of Customer Experience, Litmus
THE PROBLEM

Customer conversations were split across Intercom and WordPress. Reporting was messy and the CX team was stuck in manual work.

THE OUTCOME

One place for email, chat, and docs. Customers who got help in their first three months retained at a 26% higher rate.

Help Scout customer story

02Ops automation
HackerOneRead story ↗

“We’ve saved 588 hours on scheduling meetings. That’s 73 business days back for actual customer work, not calendar ping-pong.”

Alek RelyeaManager, Customer Success, HackerOne
THE PROBLEM

Back-and-forth email scheduling burned days. Compliance needed SSO and SCIM, so the old tools had to go.

THE OUTCOME

Enterprise scheduling with security controls. 169% ROI in a year, 114% more meetings booked year over year.

Calendly customer story

03Support AI
RebrandlyRead story ↗

“The old decision-tree flow wasn’t dynamic, and it definitely wasn’t scalable. The chatbot is already a core part of how we support users.”

Dario De GuzHead of Customer Support, Rebrandly
THE PROBLEM

A lean team supporting hundreds of thousands of users with a rigid, manual help flow that couldn’t keep up.

THE OUTCOME

AI support chatbot on their docs: 50% fewer tickets, 90–95% answer accuracy, and 16,000+ conversations handled.

Zapier customer story

04 / THE COMPANY

Close to the code.
Responsible for
the outcome.

We put AI into products and internal tools, plus the software around them.

Clear scope, working software, handover. Not a black box.

One engineer accountable for delivery.From the first question through handover.
Who we are
BACKGROUND
01 / LEADERSHIP

Built and led engineering teams.

Technical leadership at Trafilea across architecture, delivery, experiments, and production systems.

02 / PRODUCT

Shipped a product from scratch.

Finly AI: mobile, backend, infrastructure, and analytics. Idea through a working product.

Product engineering
03 / AI PRACTICE

Beyond calling an API.

Helping teams use AI in day-to-day work, including local models and the engineering that makes them reliable.

Founder experience behind Tiercel Labs. Not client logos.

TOOLS WE USE OFTENReact & Next.jsTypeScriptNode.jsAWSAI & local models
05 / WRITING

Articles people
can find and read.

Research and practical notes on AI in business — written to be findable and useful.
All 28 articles

Field note · Sep 20, 20265 min read

Where Jev fits in business automation.

Ticket routing, refund gates, alert triage, agent tool choice — high-volume judgments with clear options. Skip it when you still need a paragraph.

Read
Field note · Sep 18, 20265 min read

Decision models vs chat models in a real workflow.

Use a general LLM when you need language. Use a decision model when you need a branch. Mixing them up is how bills and latency explode.

Read
Research · Sep 16, 20266 min read

What Jev is — and why it spread so fast.

TypeSafe’s System One model returns typed decisions, not chat. Vercel reported the fastest first-day AI Gateway adoption in its history.

Read
QUESTIONS

Straight answers.

01Who is this for?

Founders, operators, and teams with a real problem, or who want help deciding if AI belongs in the business. Strategy decks with no build? Probably not a fit.

02We’re new to AI. Can you still help?

Yes. We often start by walking through how you work, spotting where AI or simple automation helps, and building a small proof you can judge.

03What does a first project look like?

Usually a fixed-scope sprint. You get a written scope: deliverables, timeline, and a fixed fee. Bigger work comes after the first result.

04How do you work with our team?

In your tools and repos when that helps. Access, communication, and timezone overlap are agreed before we start.

05What do we get at the end?

Agreed code, docs, and a handover. Your team should be able to run it without us.

NEXT STEPTELL US WHAT YOU’RE TRYING TO FIX.

Got a problem?
Let’s talk it through.

Messy brief, half-built prototype, or “not sure AI helps yet.” All fine.

LET’S FIND THE RIGHT FIRST STEP

A useful conversation
starts with your problem.

Tell us the problem, even if you’re not sure AI is the answer. We’ll help decide if a short sprint is the right first step.

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