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We help Filipino SMEs get found in ChatGPT, Perplexity & Gemini (AI Visibility) and convert inquiries 24/7 (AI Chatbots & Agents).

Premium AI systems built in Pasig, Philippines. Bots at Work is a Pasig, Philippines-based AI Visibility and AI Chatbot agency for Filipino SMEs. We help businesses get cited by ChatGPT, Perplexity, Gemini, and Google AI Overviews — and capture inquiries 24/7 with AI chatbots across Messenger, web, IG, WhatsApp, and Viber. Clients include Razon's by Glenn, Honda Cars Philippines, Aboitiz Power, and a growing roster of healthcare, automotive, F&B, real estate, and professional services brands across the Philippines. Part of Omnirad Technologies Inc. Book a free AI Visibility audit: botsatwork.ph/contact-us

30/09/2026

We measured a client's AI visibility on August 1st: 78.

Measured again September 1st, same method: 83.

That's the whole claim - and it's the only before-and-after we have in the entire body of work.

What makes it real rather than anecdotal: same brand, same metric, same query set. The September file records the previous score inside the data itself, so the comparison wasn't assembled afterwards to look good. And zero queries were dropped - every one returned a usable result, so the higher number isn't a smaller sample in disguise.

Now the part most agencies leave out.

One month is one interval. I can't tell you whether that movement was our work, a platform refresh, seasonality, or noise. No control group. No third measurement yet.

So I won't tell you we lift visibility 5 points a month. That's inventing a rate from one data point - be suspicious of anyone who does.

What I'll say: we re-measured a real client a month later, identical method, and the number went up. Almost nobody in this market re-measures at all.

Want your own baseline? Free 👇
https://visit.botsatwork.ph/ai-visibility-scorecard

29/09/2026

One business we audited ranked first in its own barangay - and returned zero results across five city-wide searches.

Both true. Same day. Same assistants.

Visibility isn't one score. It has a radius. You can be the obvious answer inside three streets and not exist one question wider.

And the wider question is the one new customers ask. Almost nobody types your barangay. They ask for the best in the city, or near a landmark, or "somewhere in the south."

Your barangay-level presence mostly reaches people who already know you exist. That's nice. It isn't growth.

So the business feels fine. Locals recommend them. Regulars keep coming. Nothing says there's a problem - while every city-wide question gets answered with someone else's name.

Most owners run the flattering test: search your own business name, see yourself, feel visible. That only proves AI can find you when someone already knows to look.

Run the wider one. Best in your category, in your city, no name 👇
https://visit.botsatwork.ph/ai-visibility-scorecard

28/09/2026

We audited a small local business and found exactly one mention of it across the AI answers we tested.

That mention came entirely from a forum post. Its own website was cited zero times.

Zero. Not "under-represented." The site the owner paid to build, writes for, and updates wasn't used as a source at all.

What's underneath that is worse than the number. Everything AI believed about that business - what it does, who it's for, whether it's any good - came from one person who doesn't work there, writing from memory, on a day they felt like posting.

Not malicious. Just the only voice in the room.

The reputation exists. It's in people's heads and in conversations - not in anything a machine can read.

And it's invisible from the inside. Your site looks fine. Nothing's broken. You'd have no reason to check.

Most owners have never run this test. Minutes, free 👇
https://visit.botsatwork.ph/ai-visibility-scorecard

27/09/2026

"Sorry, I already booked somewhere else." 😬

Every business owner has read that message. It lands when the reply came too late.

Your customers message you on Messenger, Instagram, TikTok, Telegram and your website. At 11 PM. At 2 AM. On Sundays.

Meet the Bots at Work platform: one AI team that answers on every channel, from one inbox.

✅ AI that replies and books appointments
✅ Flows that send every chat to the right next step
✅ One shared inbox for your whole team
✅ Broadcasts, pipelines and ecommerce in the same place

We've built chatbots for Philippine businesses since 2018, and AI chatbots since 2022.

Be the business that answers first. 👇
💬 Message us or visit botsatwork.ph

25/09/2026

The quiet fear about automating anything isn't that it breaks. It's that it breaks and you don't find out.

That's the version owners actually describe. Not "what if the bot is bad" - they can live with imperfect. It's "what if it's quietly losing me customers and I only notice in three months when the numbers dip."

Software you can't see inside of is software you have to trust on faith. Most people have been burned enough to have none left.

So - the version that doesn't require faith:

Every conversation scored against the same rubric, every month. Each one in a category with a verdict. Failures listed individually, not summarised. Real defects described with enough detail that you could go look yourself.

Day to day that's very ordinary: you open a report, see 130 conversations, see the three things that went wrong, and you know.

No wondering. No faith.

That's the actual product, more than the automation. Plenty of people can stand up a bot. Far fewer hand you the evidence of how it behaves when you're not looking.

You didn't get into business to babysit another system. Handing something off only works if you can still see it.

Running automation already - do you get a report you actually read? Or one you've learned to skim? 👇

23/09/2026

Last month a bot we run handled 757 messages.

Nine of them were typed by a human.

That's a 1.2% human share across 130 conversations. Not a projection, not a vendor estimate - a count, from a report produced every month against the same rubric.

Being careful about what this is and isn't: it's ONE client. A large utility, on Messenger and webchat. It's not a claim about what a bot would do for your restaurant or clinic - different question mix, different volume.

What it does prove: near-total deflection is achievable in production, at real volume, sustained over months. Not in a demo. Not in a pilot with someone watching.

And it proves it's measurable - which matters more. Most of this industry will tell you their bot "handles most of it." Almost nobody shows you the count.

The practical version: 9 human messages in a month is about one interruption every three days. Compare that to answering the same questions continuously, all day, in between the work that actually needs your team.

Comment your industry and I'll map where your inbox leaks after hours. Free, first 10 this week 👇

22/09/2026

We scored 130 chatbot conversations against a fixed rubric last month.

Not one failed because the bot didn't know the answer.

That contradicts how everyone imagines this work. The mental model is that a chatbot is a mouth you keep feeding - more FAQs, more documents, more training. So that's where businesses put the effort.

What the failures were actually made of:
• People who never got through the data-privacy consent step
• People who needed a SPECIFIC contact - which department, which person - where the bot had the right redirect but not the exact detail
• Three delivery defects in the platform layer, not reasoning failures at all

The correct answer existed every single time. The gap was always getting the person to it.

That makes maintenance a plumbing job, not a content job. Which is good news - a content backlog is infinite. A contact directory can actually be finished.

(Scope: one enterprise client, two months. Not a universal law. But it held across 130 conversations.)

Got a bot already? Do you know WHY its failures fail - not how many? 👇

21/09/2026

We helped build a chatbot for a large utility expecting billing questions.

The biggest category turned out to be people asking about jobs.

130 conversations scored in one month:
• Careers & recruitment: 34
• Billing & service: 18

The thing everyone assumed would dominate came second, by almost half.

Here's the mistake this exposes. Businesses scope a bot around the questions they REMEMBER being asked - the annoying ones, the expensive ones, the ones that came up in a meeting. Those are memorable, not representative.

And guessing wrong doesn't make the bot fail. It makes it excellent at the job you imagined and mediocre at the job it actually has - then you blame the technology. It was the spec.

The fix is unglamorous: look at what people actually sent you before deciding what to build.

Pull your last 100 messages and sort them by type. What's the biggest bucket, honestly? 👇

18/09/2026

Fourteen businesses. Nine industries. The same gap every single time.

Clinics, florists, restaurants, car brands, bridal, property. Different sizes, different budgets, different levels of marketing polish.

Same shape in every audit: the business gets mentioned more than its own website gets read - and the difference is filled in by people who don't work there.

I used to find that depressing. Now I think it's the most useful thing we know. Because it means this isn't a you problem. It's a structural gap almost nobody in the country has closed yet.

Being early to something everyone will eventually have to do is a good position.

And the part that changes how it feels: it's measurable. You can see which assistants mention you, what they say, which sources they trust, and where your site is missing.

Once it's on a page in front of you, the worry becomes a list. That shift - from "I wonder" to "here are four things" - is most of the relief.

Being straight about limits: we can show you the diagnosis rigorously. We can't promise an improvement rate - we've re-measured one client over one interval, and I won't turn one data point into a percentage.

Measure, fix, measure again. That's the offer.

Stop wondering 👇
https://visit.botsatwork.ph/ai-visibility-scorecard

17/09/2026

The audit that worried me most is the one that scored highest.

I remember the feeling when the number came back - and it was the wrong feeling. Relief. Big recognisable brand, strongest result we'd ever recorded. I nearly wrote it up as good news.

Then I read the actual sources.

One assistant cited twenty sources to answer questions about this brand. Not one was the brand's own site. Twenty out of twenty, all somebody else. Its after-sales reputation - the thing that decides repeat buyers - was owned by two forum threads.

Then it got worse. The service page and owner FAQ were both "coming soon." And the homepage FAQ was live placeholder text. Lorem ipsum. On a major brand's homepage. Long enough that the machines had learned to route around it.

That's the day the pitch changed for me.

I used to think this work was about rescuing invisible businesses. This one wasn't invisible - it was highly visible and completely un-sourced. Which is more dangerous, because nobody there had any reason to suspect a problem.

A weak brand at least FEELS like it has work to do. A strong brand with an empty evidence layer feels fine - right until someone asks the machine.

If you're one of the confident ones, that's exactly why it's worth checking 👇
https://visit.botsatwork.ph/ai-visibility-scorecard

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