Is this a “Find Stock” task or a “Find Help” task? A booking, or a search? You’d pick a category, choose a business type, fill in the fields, and then hand it off to Alex Parker, our AI agent.

It worked. But it always bugged us. Because you don’t think in categories. You think in sentences.

“Can someone find me a pharmacy that still has cold medicine?” “I need a table for two tonight.” “There’s water under my sink and I need a plumber, fast.”

So we rebuilt the front door around the way you actually talk. Today, Tell Us is live for everyone at callomat.ai

One box, any errand

There’s just one thing on the home screen now: a box that says “Tell me what you need.”

You type it. Or you tap the microphone and just say it. No menu, no form, no deciding in advance which “feature” your problem belongs to. Alex reads the sentence and figures out the rest.

Real things people type into it:

• “Can you book a table at a restaurant in Berlin for dinner tonight?”

• “I need to find a pharmacy nearby that has cold medicine in stock.”

• “Please dispatch a plumber to fix a leak in my kitchen urgently.”

• “I’d like to book a beauty appointment at a salon this evening.”

• “Can you check if any cafes near me have almond milk?”

Five completely different jobs — a booking, a stock hunt, an emergency dispatch, an appointment, a quick question. One box handles all of them. Your first call is on us, and results usually land in minutes.

It listens. Then it makes a plan.

Here’s the part we’re quietly proud of.

When you hit send, Callomat doesn’t just fire off a phone call. It stops and thinks out loud — with a little personality. (”Sharpening my please-and-thank-yous…” is one of our favorites.) And it shows you a plan before it touches the phone network:

Got it — working on your request.

1. Confirm with you

2. Call the business

That order matters. Nothing gets dialed until you’ve seen the plan and said go. Tell Us is fast, but it’s never sneaky.

It turns a sentence into a plan

Under the hood, Alex takes your messy, human sentence and quietly turns it into a precise mission.

Say “book a table for two at an Italian restaurant tonight around 8pm,” and by the next screen it has extracted:

• Looking for → a table

• Party → 2 people

• Date → tonight

Every one of those is right there on the confirmation card, and every one is editable with a single tap. Got the party size wrong? Fix it. Want tomorrow instead of tonight? Change it. You’re never trapped by what the AI thought you meant — you get the last word before anyone picks up the phone.

You approve. Then it dials.

For a call-around job, the confirmation card lays it all out before you commit:

• “We found 10 restaurants near you.” A map shows the search area, with a radius you can widen from 1 km all the way to 10 km.

• “We’ll call them until one can help. We stop as soon as one says yes.”

• Cost: 1 credit — for all the calls. Not per call. One price to solve the whole errand.

And when Alex gets someone on the line, there’s no pretending. He opens every call by saying he’s an AI assistant phoning on your behalf. We think that’s the only honest way to put an agent on the phone with a real human being — and it’s non-negotiable.

You can finish with a free account (one tap, and it remembers you next time) or just continue as guest if you’re in a hurry. Either way, your first call is free, and after that you pay with credits — no card, no SMS code to re-enter.

The same box knows a booking from a hunt

Here’s the subtle magic: you never have to tell Callomat which “mode” to use.

Ask it to book a specific restaurant, and it makes the one call and books your table. Ask it to find something — a medicine, a plumber, “any Italian place with a table tonight” — and it lines up a queue of businesses and calls around until one says yes, then stops.

That decision — call one place, or call around many — used to be your job, made by picking the right feature off a menu. Now it’s Alex’s job, made by reading your sentence. There is no “Booking app” and “Find Nearby app” anymore. There’s just: tell us what you need.

Still like to browse?

Some errands start with a craving, not a sentence. If you’d rather scroll a neighborhood — restaurants, pharmacies, locksmiths, hair salons near you — Discover is one tap away under “Browse places instead.” Tell Us is the fast lane; browsing is still there when you want to window-shop the real world.

The real world, in one sentence

We started Callomat to kill hold music. Tell Us is the next step: killing the setup too. No categories to learn, no forms to fill, no deciding what kind of problem you have before you’re allowed to solve it.

Just say what you need. Alex makes the calls. You get the answer.

Try Tell Us now at callomat.ai.

You know how this goes. You put it off, because cancelling means the phone. You finally call at 4:55pm. It rings. It rings again. “Your call is important to us.” Elevator music. You’re on hold, watching the exact minutes tick by that you were trying to save.

One woman told CNBC she tried to cancel a doctor’s appointment twice and sat in “elevator music purgatory for over 20 minutes” each time, never got through — and got a $100 no-show fee in the mail three weeks later. She had tried to cancel. It didn’t matter. There was no proof.

Cancelling got expensive — and hard on purpose

Here’s the uncomfortable part: a lot of places would rather you didn’t cancel cleanly. A cancelled slot is a hole in the day. So cancelling is often made deliberately cumbersome — a number nobody answers, a 24- or 48-hour window, a card kept on file to make the penalty stick.

And the penalties are real:

• Doctors and clinics now routinely charge $100–$200 for a no-show.

• Restaurants charge $25–$50 a head — a cancelled dinner for six runs into the hundreds, and OpenTable started stacking its own fees on top in 2025.

• Salons and therapists hold your card and bill the whole session.

More than half of people say they’d switch providers over a no-show fee. But in the moment you don’t want a fight — you just want out of the booking, cleanly, without the hold music.

What Callomat does instead

You tell Callomat what to cancel — the place, the date and time, the name on the booking. That’s it. You don’t dial anyone.

Alex, our AI agent, makes the call. She waits on hold so you don’t have to, talks to whoever picks up (in their language), and cancels the booking under your name — right away, so you’re not putting it off until you’re already inside the fee window.

Then comes the part that actually matters:

Cancelled. Confirmed by “Marco” at 4:58pm. Reference #4821.

She brings back proof — who she spoke to, when, and a reference number if there is one. So if a “no-show” charge turns up weeks later, you’re not arguing from memory. You have a receipt.

The bit people don’t expect: it works for bookings you didn’t make in Callomat

You don’t have to have booked through Callomat. That reservation you made on the restaurant’s own website, the appointment you booked by phone last month, the table a hotel concierge sorted for you — Callomat can cancel any of them. You hand over the details; it makes the call.

And you only pay if it works. If the cancellation is confirmed, it’s one credit. If Alex can’t get it confirmed — nobody answers, or the place won’t cancel over the phone — you’re refunded, and told plainly: “we couldn’t confirm this — you may still be on the hook, please follow up.” No pretending. No silent failure.

Cancelling, finally, off your plate

Booking was the easy part. Un-booking is the errand nobody wants — the hold music, the awkward call, the fee you might eat anyway. That’s exactly the kind of phone call we built Callomat to take off your hands.

So next time something comes up, don’t dread the call. Tell Callomat what to cancel, and go do the thing that came up instead.

Cancel it for me → callomat.ai

So you start calling. The first is fully booked. The second doesn’t pick up. The third has 9:30, not 8. By the fourth “sorry, we’re full” you give up and eat wherever the guy in the doorway waves you into.

That whole errand — the one you dread — is what “Find me a table” does for you. Here’s how it actually works, and the thinking behind it.

What you actually do

You search restaurants in your area and see what’s around you — the real places, with their ratings and whether they’re open. Then you flip one switch at the top from “Book a place” to ⚡ “Find me a table.”

Now every nearby spot is selected for you. You keep the ones you like and uncheck the ones you don’t — it’s your shortlist. You tell us the party size and when (”tonight at 8”, or “I’m flexible”), and tap Find me a table.

That’s it. Callomat calls the places you picked until one says yes — and books the table under your name. A few minutes later you get the confirmed spot and time:

Booked at Rosa’s Thai — 8:15pm, table for 3.

You didn’t make a single call. You didn’t hear a single “we’re full.”

Why we built it this way

None of this is flashy on its own. But every choice underneath it is deliberate.

A table is two different jobs. Sometimes you want that restaurant. Sometimes you just want a table, tonight, anywhere good. Those aren’t the same request — so we made it a switch you flip, not a guess we make on your behalf. “Book a place” when you know where; “Find me a table” when you just want in somewhere.

You choose who we call. You see everything nearby and keep the places you actually fancy. Callomat calls your picks — not a mystery list it made up. We’re clear about it on screen, too: “we’ll call these until one says yes.” No black box.

It books — it doesn’t just check. “They might have space” is useless five minutes later. So when a place says yes, Alex — our AI agent — holds the table under your name and party size, and brings back the confirmed time. A real reservation, not a lead.

It stops the moment one says yes, and you only pay if you get a table. Callomat isn’t trying to call everywhere — it’s trying to get you seated, then it’s done. One credit, refunded if nobody can seat you. And because Alex speaks the language of the place she’s calling, a trattoria in Rome is no harder than the spot round the corner.

The point

The magic isn’t a robot that can dial a phone. It’s the boring, awkward, “call around until someone has space” errand — done for you, while you get on with your evening.

So next time you want a table, don’t make a dozen calls. Pick a few places you like, tell Alex when, and go look at the fountain. We’ll call around and book it.

We’ll find your table. Try it → app.callomat.ai

We’ve all been there.

You need something specific—a specific size of screw, a table for six at 7 PM on a Friday, or a pharmacy that actually has your medication in stock.

You check Google. It says “Open.” You check the website. It says “In Stock” (last updated: 24 hours ago). You drive 20 minutes across town, fight for parking, walk to the aisle, and find an empty shelf.

That 45-minute round trip was a tax on your time. And it was completely avoidable.

The “Last Mile” Problem of Search

Modern search engines are incredible at organizing the world’s information, but they are terrible at verifying the current state of the world.

• They know where the hardware store is.

• They don’t know if the hardware store sold their last 12mm plywood sheet five minutes ago.

To bridge that gap, you have to become a logistics manager. You have to pull up a list of phone numbers. You have to dial. You have to wait on hold. You have to explain what you need to five different strangers. You have to hear “no” four times just to hear “yes” once.

It’s exhausting. It’s friction. And frankly, it’s a job for a machine.

The Rise of Agentic Search: Your Personal Logistics Agent

This is why we built Find Nearby. We wanted to move beyond “passive search” (indexing what happened yesterday) to “agentic search” (finding out what is happening right now).

Agentic AI distinguishes itself from standard AI by its ability to act. It doesn’t just generate text; it pursues a goal. It behaves autonomously to bridge the gap between your intent and the outcome.

When you use Callomat, you aren’t just querying a database. You are dispatching a goal-oriented agent—Alex Parker—to go out into the real world and do the work for you.

Here is how this changes your day:

1. You get your time back.

The average “Find Nearby” task involves calling 3 to 5 businesses. That’s 15-20 minutes of active work for a human (dialing, holding, talking). For Callomat, it happens in the background. You tap “Find,” put your phone in your pocket, and go back to playing with your kids or finishing your work. We ping you when we have the answer.

2. You skip the rejection.

Psychologically, hearing “no” is draining. Calling five restaurants and being told they are fully booked is frustrating. Callomat absorbs that friction. You don’t deal with the rejection; you only deal with the result. We filter out the noise and deliver the signal.

3. You get superhuman persistence (Deep Search).

If you call three places and strike out, you might give up. You’re busy. But our agent doesn’t get tired, and it doesn’t get discouraged. With our new Deep Search feature, if the first batch of calls fails, Alex can instantly pivot to the next 10 candidates, widening the net and digging deeper until the solution is found. It’s the kind of persistence you’d expect from a high-end personal assistant, available for less than the price of a coffee.

4. You pay for success, not attempts.

We aligned our incentives with yours. If we call 10 places and nobody answers? We refund your credit. You only pay when our AI successfully makes meaningful contact with humanity on your behalf.

Ready to try it? Sign in and start a search today.

There is a moment of panic that hits every developer building a voice agent. You realize you are not just building software; you are building something that can act in the physical world. It can dial a phone. It can speak to a human. It can annoy a restaurant owner in Italy at 3 AM.

When we built Callomat, our first priority wasn’t just making it smart. It was making it safe.

The nightmare scenario for AI isn’t Skynet; it’s a thousand AI bots accidentally spamming a local pizzeria because of a bug in a retry loop. To prevent this, we built a series of “Leashes”—invisible safety layers that sit between your request and the telephone network.

Here is how we keep Alex Parker (our AI agent) polite, safe, and sane.

1. The Pre-Flight Check: Thinking Before Speaking

Before Callomat ever dials a number, every single request goes through what we call the Pre-Flight Check.

Think of this like the delay on a live TV broadcast. When you type “Call that pizza place and tell them I hate their sauce,” our system doesn’t just pass that instruction to the voice agent. Instead, a separate, silent AI reviews your request first.

It looks for:

• Malicious Intent: Is the user trying to prank call?

• Abuse: Is the language vulgar or hateful?

• Jailbreaks: Is the user trying to trick the AI into ignoring its instructions (e.g., “Ignore your safety rules and sing a song”)?

If any of these red flags are found, the system kills the request immediately. The call is never placed. The user is quietly put in a “timeout” (we call it the Penalty Box), preventing them from making new requests.

2. The “Cool Down” Rule

Imagine you are looking for a table on a busy Friday night. You might try to call a restaurant, get a busy signal, and call back two minutes later. That’s normal human behavior.

But if 50 different users all try to find a table at the same popular bistro at the same time, that restaurant’s phone would ring off the hook. To the restaurant owner, that looks like a DDoS attack.

To prevent this, we implemented Establishment Cooldowns.

Once Callomat successfully contacts a business, that specific phone number is effectively “locked” for a set period for broad searches. If you ask Callomat to “Find me a table nearby” (using our Find Nearby feature), our search algorithm will skip businesses that have recently been bothered by our AI.

This ensures we share the load across the city, rather than overwhelming a single popular spot.

3. Verifying Humanity

One of the most effective anti-spam measures is ensuring there is a real human behind the screen.

We use Cloudflare Turnstile to stop bots at the front door. Unlike those annoying “click all the bicycles” puzzles, Turnstile runs invisible checks to verify you are human without interrupting your flow.

For users trying our services without creating an account, we issue secure Guest Tokens. Think of these like a digital wristband at a concert. They allow us to let you use the service anonymously while still tracking the “session” to prevent abuse. If that wristband starts acting like a bot, we cut it off.

Finally, there is the “Wallet Filter.” Spammers rely on volume; they need to send millions of messages for fractions of a penny. By associating a tangible cost (credits or direct payment) with every action, the economics of spamming collapse.

4. Structured Sanity

Finally, we don’t let the AI improvise too much.

When you ask Callomat to “Check if they have those cool shoes,” we don’t just tell the AI “Ask about cool shoes.” We force that request into a Structured Data format.

• Item: Running Shoes

• Brand: Nike

• Model: Pegasus 40

• Attribute: Size 10

The AI is given a strict “mission.” It knows exactly what “Success” looks like (Product In Stock) and exactly what “Failure” looks like (Out of Stock). It isn’t allowed to chat about the weather, discuss politics, or hallucinate a discount that doesn’t exist.

Building Trust

We know that for Callomat to succeed, it needs to be trusted—not just by the people using it, but by the businesses receiving the calls.

We are building a tool that respects the time and attention of everyone involved. By putting these leashes on the AI, we ensure that when Alex Parker calls, he is helpful, brief, and gone.

When we tell people Callomat can “call a restaurant and book a table,” the immediate assumption is that we’ve just hooked up a Large Language Model (LLM) to a voice synthesizer. Give it a script, give it a number, and hit go.

But anyone who has ever made a phone call knows it’s never that simple.

In the real world, phone calls are chaotic. Connections crackle. Background noise intervenes. People speak over each other. And most importantly, human conversation is full of ambiguity. A successful AI agent isn’t just a chatbot that reads text aloud; it has to be a highly adaptive negotiation engine.

Here is a high-level look at the product challenges we face in engineering Alex Parker to navigate the complexities of the analog world.

1. The Context Challenge: Grounding the AI in Reality

One of the first hurdles in building a voice agent is “grounding.” An LLM running in a data center has no concept of “here” or “now” unless you explicitly give it one.

If a user in New York asks to book a table for “tomorrow” at a restaurant in Tokyo, the AI needs to understand more than just the calendar date. It needs to understand the business’s reality. Is “tomorrow” already today in Tokyo?

We spend a significant amount of engineering effort on what we call the Pre-Processing Layer. Before a call is ever placed, we have to translate the user’s digital intent into natural, human-readable context. The AI shouldn’t speak in ISO dates (”2025-12-20”); it should speak in relative human terms (”this coming Saturday”). This ensures that when the AI speaks, it sounds like a local human, not a database reader.

2. The Negotiation Dance

The biggest misconception about AI calls is that they are transactional. “I want X.” “Here is X.”

In reality, booking a service is a negotiation. Humans rarely have a single, rigid requirement. We have preferences.

• “I’d like 7:00 PM, but I can do 7:30.”

• “If you don’t have a table inside, the patio is fine.”

A rigid script fails the moment a host says, “We’re full at 7, but how about 5:30?”

We learned early on that our prompts needed to move beyond simple instruction following and into Intent Understanding. The AI needs to know how flexible the user is. Is this a specific anniversary dinner that must be at 7:00 PM? or is this a casual search for any table tonight?

Depending on the user’s intent, the AI changes its posture. It can be firm and specific, politely declining alternatives if the user needs a precise slot. Or it can be open and collaborative, actively hunting for the “first yes” if the user just wants to get in the door.

3. Surviving the “Unhappy Path”

In software, the “happy path” is when everything goes right. In phone calls, the happy path is the exception.

What happens if the restaurant is “Walk-in Only”? What if the person who answers speaks a different language? What if the line is bad?

We treat our prompts like decision trees for chaos. We have to map out dozens of Scenario Maps—specific instructions for common off-ramps.

• Language Switching: Our agents are designed to listen for language cues. We seed the context with the country’s likely language, but the AI must be ready to switch instantly from English to German or Spanish if the human on the other end does.

• Graceful Exits: Sometimes, the answer is “no.” The restaurant refuses to take a booking, or they are closed. The AI must know how to accept defeat gracefully, end the call professionally, and report the specific reason back to the user, rather than getting stuck in a loop of trying to convince a closed business to open its doors.

Bridging the Gap

Building Callomat isn’t just about better prompts; it’s about building a bridge between digital intent and physical reality. It requires a deep respect for the nuances of human interaction.

We are building a system that doesn’t just “talk,” but understands the goal of the conversation. It respects the constraints of time and space. And most importantly, it acts as a reliable proxy for you, handling the awkwardness and the hold music so you don’t have to.

We’re making it easier.

Today, we are rolling out Flu Shot Find, a dedicated feature to help you secure your vaccination without the hassle.

How it works Just tell Callomat you need a flu shot. Alex Parker, our AI agent, will call pharmacies in your area to check for:

1. Availability: Do they have the vaccine in stock?

2. Appointments: Can you walk in, or do you need to book?

3. Timing: When can you get it done?

Alex handles the calls. You get the result: a list of places where you can go right now or book an immediate appointment.

Stay healthy this winter Don’t waste time on hold while you could be getting protected. Let Callomat do the legwork so you can focus on staying warm and healthy.

Try Flu Shot Find today at Callomat.

We built Callomat because, in 2025, finding information from local businesses is still harder than it should be. Whether you are hunting for a specific medication at a pharmacy, looking for a last-minute restaurant table, or trying to find an electrician who is actually available today, the solution is usually the same: making call after call after call.

We fixed that.

With Callomat, you don’t make the calls. Alex Parker, our AI agent, does.

What is Callomat?

Callomat is an intelligent search engine that interacts with the real world. You tell us what you need, and Alex calls multiple businesses in your area simultaneously to find it.

• She speaks the language: Alex automatically detects and speaks 9 languages (including German, French, Spanish, and Dutch).

• She is efficient: She filters through businesses to find the one that says “Yes.”

• She handles the awkwardness: No more “sorry, we’re closed” or “no, we don’t stock that.” You only get the positive results.

What can you do in 1.0?

The Find Nearby feature is live now with support for 30+ business categories:

• 💊 Find Stock: Locate items in pharmacies, hardware stores, and retail shops.

• ⚡ Find Help: Locate available electricians, plumbers, and locksmiths.

• 🍽️ Find Space: Check real-time table availability at restaurants.

Follow our journey

We are just getting started. We have an aggressive roadmap of features coming soon. We will keep this Substack updated with:

• New feature releases

• Version changelogs

• Tips on getting the most out of your credits

Ready to stop waiting on hold?

Try Callomat 1.0