Skip to content

Rehoz builds custom AI tools that run the busywork in operations-heavy businesses.

AI engineering for operations-heavy companies
We build the AIthat does the busywork.

The repetitive work your team grinds through daily, reading, re-keying, chasing, handed to an AI system built into how they already work.

Get your AI planSee a sample plan

Start free: tell us where your operation loses hours, the work that recurs every day, and we send back the exact AI system we would build for it first, scored in hours and dollars. The plan is yours to keep, with or without a call.

AI BUILD PLANSAMPLE

Prepared for: a staffing firm

Workflow to automate first
Resume screening
AI we would build
Shortlister
Recruiter hours back
48 / wk
Value recovered
$108,000 / yr
Sample 1 / 5

Illustrative samples built on public benchmarks, not real clients. Your real numbers replace every figure on the call.

Built by engineers from
  • Amazon
  • Trendyol
  • Dream Games
  • Jotform
  • Accenture
§ 01 · What we build

Custom AI systems, built into the work you already do

Not an AI transformation program. We find the one workflow where AI earns its keep first, build the AI system that runs it, and wire it to the numbers it moves. It all starts with a free plan.

An abstract field of dark tiles assembling into a system, one tile lit in amber
Fig. 01 / system assemblingin the work
  • 01
    The product

    Tools that do the busywork

    AI that takes over the repetitive, hours-eating tasks: reading, re-keying, drafting, chasing, checking. It runs inside the systems your team already uses, and a person still makes every call that matters.

  • 02
    Proof, not promises

    Measured in hours and dollars

    Every AI system is wired to the metric it moves, on numbers you already track. You watch the saving land on real work in the first week or two, not at the end.

  • 03
    No lock-in

    Yours to own and keep

    Built in your repository and your accounts, documented so any engineer can pick it up. No platform to rent from us, nothing that breaks when we step away.

§ 02 · Proof

We do not just advise on AI. We ship it.

These are real, running systems companies pay for every month, alongside the automation engine that runs our own business. The proof is not a demo. It is that people renew.

BrandVox AI§ 02.1

An AI product we built and run, paid for monthly

Visit BrandVox AI

A working AI system with more than 1,000 users. Thirty-plus businesses pay between 59 and 449 dollars a month to keep using it. It does the marketing and customer-facing busywork a small team would otherwise grind through by hand. The proof here is not a demo. It is that people renew, and the invoices clear every month.

Under the hood · Each customer gets their own private workspace, the AI answers from that customer's own content rather than guessing, and we run the whole thing on our own infrastructure.

Kodwai§ 02.2

An AI product we built end to end, live with 50+ developers

Visit Kodwai

An AI system that sits in for the slow, expensive part of technical hiring: running a structured interview and scoring the answers consistently. The point for you is not the hiring use case. It is that we can take a judgment-heavy human workflow, hand the repetitive part to AI, keep a person in control of the call, and get it in front of real users who keep showing up.

Under the hood · Twenty-two live interview scenarios, each scored two ways: a fixed pass-fail check on the things that are either right or wrong, plus an AI read on the judgment calls, with the running cost capped.

Ksenda§ 02.3

The outbound system that likely sent you here

Visit Ksenda

If an email from us brought you to this page, it came out of Ksenda. We did not just build it, we lived on it. It finds companies worth talking to and reaches them one at a time, at a scale a person could never do by hand. We pointed it at our own business and it is how we filled the paying side of BrandVox.

Under the hood · One screen, one click to send, with the AI drafting each message and a required human review step before anything goes out the door.

Ksenda · in our own operation

The outbound that is normally a full-time job, run by one system we built and one person reviewing

Done by hand, cold outbound is roughly a full-time job for a junior hire, and most of that week goes to copy-paste and list-building, not thinking. The usual payoff is one to five replies per hundred emails. We built Ksenda to carry that load, ran our own outbound on it, and counted the replies by hand. About fifteen out of every hundred people replied. We removed the manual hours and lifted the response rate several times over. That is the strongest proof we can offer: the result we are selling you is the result it produced for us.

emails sent
reply rate
industry norm
person reviewing
Reply rate, same effort
Rehoz outbound (Ksenda)15%
Industry norm3%
§ 03 · How it starts

From your operation to a working AI system

  • 01 / 04
    01

    Tell us about your operation

    A few lines: where the hours go, the work your team repeats every day, where you want more efficiency. No long forms, no access to anything.

  • 02 / 04
    02

    We write your build plan

    We find the one workflow where AI pays off first and write it up, scored in hours and dollars on numbers you already track. Free.

  • 03 / 04
    03

    We walk through it, thirty minutes

    We read the plan together and you tell us where we read your operation wrong. You keep the written plan either way.

  • 04 / 04
    04

    We build the AI system, about six weeks

    If the number is worth it, we build the AI system into your real workflow and hand it over. Only then, and only if you want it.

The cost through step 03

Through step three you have spent one link and thirty minutes. Nothing else.

§ 04 · The build plan

What your free build plan looks like

Before we build anything, you get this: the one workflow we would automate first, the AI system we would build for it, and what it saves, scored in hours and dollars. Here is a sample. It is built on public benchmarks, not a real client, so the numbers are held to the low end.

SAMPLE PLAN · Illustrative example, not a real client · Figures from public 2025-2026 staffing benchmarks

AI build plan

REGIONAL STAFFING CO.

SampleAs of June 2026

A 90-person regional light-industrial staffing firm. 6 recruiters on the desk, no AI in use today.

What it returnsEstimate

recruiter-hrs / wk

given back across the 6-person desk

first-year value

hours returned plus recovered placements

< 1

quarter to payback

on the fuller picture, build cost cleared

The workflow we would automate first

Every weekday, inbound resumes land in a shared inbox and the job-board queue. Each recruiter opens them one by one, reads each resume, decides if the person clears the basics for the open order, then re-types the useful details into the ATS by hand before anyone can be submitted. The first agency to put a qualified person in front of the client usually wins the placement, so the hours lost reading and re-keying are not just admin. They are placements that walk to a faster competitor while the resume sits unread.

What we would build

First-Submittal Shortlister

A quiet helper that watches the same inbox the team already uses. The moment resumes arrive, it reads each against the open order's real requirements and hands the recruiter a ranked shortlist worth a call, each with a one-line reason and the key fields already dropped into the ATS draft. The recruiter still makes every call. The AI system just removes the reading and re-typing.

TodayWith the tool
Today
Recruiter time reading and re-keying
~12 hrs / recruiter / wk
Time for a qualified candidate to surface
1 to 3 days
Fillable orders lost each week to a slower first submittal
~2 / week
With the tool
Recruiter time reading and re-keying
Recruiter-hours returned across the 6-person desk
Time for a qualified candidate to surface
minutes
Lost orders recovered
Payback

On the recovered placements alone, the build pays for itself in under 10 months. Counting the ~48 recruiter-hours given back each week as well, first-year value lands near $108,000, so on the fuller picture the build clears its cost inside the first quarter.

Assumptions & sources

These figures are illustrative, not a real client's books, and held to the conservative end on purpose. Built from public 2025-2026 staffing benchmarks: recruiters spend ~52% of the week on admin; 8 to 10 hours to hand-screen ~200 resumes; teams report 10 to 15 hours per week saved per recruiter from screening automation (this sample claims only ~8); average recruiter cost ~$28/hr, taken to ~$35/hr fully loaded; light-industrial temp gross margin runs ~21 to 25%. Your real numbers replace every figure here on the call.

§ 05 · Built with, plugged into

Built on tools you trust. Plugged into the systems you run.

We build on the standard infrastructure your engineers already trust, set up in your own accounts, and we connect to the business systems your team already runs, so the AI lives where the work already happens.

Engineered on
  • AI & models
    OpenAIAnthropicHugging FaceLangChainPyTorchOllama
  • Languages
    PythonTypeScriptJavaC++GoRust
  • Frameworks & runtime
    Next.jsReactNode.jsSpringFastAPIDocker
  • Cloud & data
    Amazon Web ServicesGoogle CloudCloudflareVercelPostgreSQL
Plugs into the tools you already run
  • ERP & operations
    SAPOracleOdoo
  • Finance & accounting
    QuickBooksXeroSageStripe
  • CRM, sales & support
    SalesforceHubSpotMailchimpZendesk
  • Commerce, comms & data
    ShopifySlackZapierNotionAirtableGoogle SheetsTwilioDropbox
§ 06 · Where this works

Built for operations-heavy businesses

The work does not care what you make or sell. It cares whether your team repeats a task every day that eats hours: chasing the same information, re-keying the same data, drafting the same replies, catching the same errors after the fact. That pattern is in every operation below.

  • Staffing & recruiting

    Screening, submittals, candidate matching.

  • Warehousing

    Inbound, inventory, exception handling.

  • Logistics & distribution

    Scheduling, documents, status chasing.

  • Manufacturing

    Quoting, specs, quality notes.

  • Healthcare admin

    Intake, records, back-office work.

  • Professional services

    Proposals, reporting, client comms.

§ 07 · FAQ

Straight answers

  • Fair question, and you are right to be tired of it. We are not going to pitch you a future. We pick one workflow you already run, where the work is repetitive and slow, and we build the thing that does it. You see it running on your data before you decide anything. The free build plan names that one workflow and what it would save, in hours and dollars, not in adjectives. If the number is not worth your time, you say so and we are done.

Start with the free build plan

See exactly what we would build you.

Tell us where your operation loses hours. We read how it runs, write the plan, and bring it to a 30-minute call, peer to peer, no slides. If you would rather just read it first, email us and we will send it over, no call needed.

Build plan
$0
The call
30 min
Slides
none
Book the 30-minute callOr email us about your operation

hakan@egehakan.com · Istanbul, TR

§ 08 · Company

Who you are dealing with

Rehoz is an AI engineering firm founded by Ege Hakan Karaagac.

He spent two years at Amazon building the systems that ran checkout and tax for millions of orders, then backend at Dream Games, before that Accenture. We build AI products of our own: BrandVox, with more than 1,000 users and 30-plus paying every month, and Kodwai, an AI interview platform more than 50 developers use. We built Ksenda, the outbound system that brought you here, and ran it on our own pipeline: more than 5,000 emails, about 15 percent reply against an industry norm of 1 to 5 percent. We do one thing for clients: we find the first place AI earns its keep in your operation, and we build it.

LinkedInhakan@egehakan.com
An abstract navy and amber schematic of the system Rehoz builds: the engine that runs the busywork.
fig. 10
the systembuilt to keep running