Co-founder at ResiDesk

I build software with the people who have to use it.

Right now, that means building ResiDesk with property teams. Residents text about rent, repairs, renewals, parking, and everything else that can make a building hard to live in. We help the team answer well, remember the context, and fix the things that keep coming back.

Before ResiDesk, I built software for financial advisors at BlackRock. Then I ran product, engineering, and data at Climb Credit. Both jobs taught me the same thing: sit with the person doing the work, measure what changed, and keep fixing the parts that fall apart on a normal Tuesday.

Arjun Kannan
I live in New York and build ResiDesk with a small team. Most days involve residents, software, and a lot of questions.

Renting is expensive. Getting a straight answer should not be this hard.

A resident might ask about a broken lock in a text, mention it again on a call, and leave a review after the third attempt. Property teams hear versions of that story all day across texts, tickets, surveys, calls, and renewal notes. Answering one message is useful. Knowing the repair is still open is the part that matters.

We started ResiDesk after seeing how much of this work lived in separate inboxes, property systems, spreadsheets, and people's heads. I co-founded the company, and my week moves between product and data, customer calls, sales, hiring, and helping the team get past whatever is stuck.

AI helps us read and connect more of that history. It still has to know the building, follow the policy, admit what it does not know, and hand the work to a person when the person needs to decide.

See ResiDesk
01

Read the message

Start with what the resident actually said. Do not flatten a broken lock, a rent question, and a noisy hallway into the same score.

02

Pull the history together

Find the lease, building policy, earlier messages, open work order, and what the team has already tried.

03

Help the team act

Answer the question, open the repair, explain the policy, or ask someone to decide. Make it clear who owns the next step.

04

Fix what keeps repeating

If move-in instructions confuse twenty residents, the answer is not twenty better apologies. Fix the instructions.

I came to software through physics. The useful part was making somebody else's work easier.

I studied applied physics at Cornell and spent time in an electron microscopy lab. Part of a magnetic-noise experiment meant doing the same slow analysis again and again. I wrote a small program to do it faster, and a researcher got hours back. That was the first time software felt useful to me.

Physics

I wrote a tool because the experiment was slow.

The code was not ambitious. It removed a tedious part of someone else's day. I still start there.

BlackRock

The new tool had to beat the spreadsheet.

At BlackRock, I built analytics software for financial advisors and the people planning their retirements. I won the internal Aladdin Hackathon three times. A prototype could still win the room and lose the next morning to a spreadsheet that people knew how to use.

Climb Credit

We asked whether the school changed what someone could earn.

At Climb Credit, I ran product, engineering, and data while we built loans for career-focused education. We brought completion rates, graduate earnings, and employment outcomes into the product instead of pretending a credit score told the whole story.

ResiDesk

At ResiDesk, the customer is right there in the conversation.

A resident's message can become an answer, a repair, a renewal conversation, or a decision about how a building is run. I want our product to follow that work far enough to know whether anything got better.

30,000+

Homes covered in a four-month study of what residents said about Wi-Fi and how it related to renewals. Read the study

$1M → $300M

Climb's annual loan volume grew from roughly $1 million to $300 million while I led product, engineering, and data. The early Climb story

$40M ARR

Annual recurring revenue reached by the advisor analytics product I helped build from its first version at BlackRock.

I do my best work when the problem is concrete and the people closest to it can disagree with me.

01

Start with the person doing the work.

Ask what they are trying to finish, what information they are missing, and what happens when the queue gets busy.

02

Take the problem seriously. Check the scope.

I want the person who found a problem to feel glad they raised it. Then we can count the cases, find the cause, and fix the part we control.

03

Make it survive the busy day.

The real test comes when the queue is full, the policy is unclear, and nobody who built the demo is in the room.

04

Teach the tool what you fixed.

If a person has to correct the same mistake twice, I want the second correction to become part of how the work gets done next time.

I write when I am not sure yet.

I usually start because I caught myself saying something too neat in a meeting. Writing forces me to find the example, check the claim, and decide what I would actually do.

With AI, I care less about which model won this week than whether the product can read the right information, use the right tools, show what it did, and stop when it is unsure.

I am also starting to look more seriously at fair housing as AI takes on more leasing and resident work. If software helps decide who gets an answer, which problem gets attention, or when a person steps in, we should be able to test whether it treats people fairly.

Read what I've been writing

Conversations

Three videos

I like a hard problem and a candid conversation.

I am always glad to hear from founders, housing people, and teams trying to make AI useful in a real business. I also enjoy helping with product choices, early company problems, and the ordinary mess that does not fit neatly into a job description.

You do not need a polished pitch. A few honest sentences about what happened, what you have tried, and where you are stuck are plenty.

I am especially useful when there is a customer to understand, a product decision to make, or a team that needs a clearer next step.