Services / AI and automation

Put the repetitive work on a machine. Keep the part that needs a person.

Assistants that answer from your own documents and data, inquiries qualified the moment they arrive, and the handoffs between your tools done without anyone copying and pasting.

Find where AI can helpSee what we build

Most of it isn't hard work. It's just work nobody got to.

An inquiry sits unanswered overnight. The same five questions get typed out again. Somebody re-enters an order into a second system because the two don't talk. None of it is difficult. It just needs doing, every day, by someone.

That's the work worth handing over.

What we build

Grouped by the job it does, not by the technology behind it.

Answering and support

An assistant on your site or in your inbox that answers from your own documents and data, meaning your prices, your policies and your process, and hands over to a person the moment it should.

  • Website assistants
  • Customer support
  • Common questions
  • Handover to a person
  • Internal knowledge
What this involves
  • Where answers come from: your documents, policies and prices, rather than a general model guessing, which is the difference between useful and dangerous
  • Scope: what it will answer and what it must refuse, agreed before it goes anywhere near a customer
  • Handover: the exact point a person takes over, with the conversation attached so nobody repeats themselves
  • Tone: written to sound like your business rather than like a help desk
  • Keeping it current: answers updated as prices and policies change, because a confidently wrong answer is worse than none
  • Review: reading what it was actually asked, and fixing what it got wrong

Lead handling

New inquiries answered straight away, asked the questions you'd ask, and sorted before anyone picks them up, so the good ones surface and nothing sits overnight.

  • Instant first reply
  • Qualifying questions
  • Routing
  • Booking
  • Chasing a reply
What this involves
  • First reply: acknowledged immediately, whatever time it arrives, which is most of the advantage on its own
  • Qualifying questions: the ones you would ask on the phone, asked while the person is still interested
  • Routing: to the right person or team, with the answers already attached
  • Booking: straight into a calendar where that fits how you sell
  • Chasing: following up when someone goes quiet, and stopping the moment they reply
  • Written down: everything recorded in the CRM as it happens, not reconstructed later

Sales follow-up

The follow-up that actually happens. Sequences that run on their own, records kept current without anyone updating them by hand, and messages written to the person rather than to a list.

  • Follow-up sequences
  • CRM kept current
  • Personalized messages
  • Quote chasing
  • Re-engagement
What this involves
  • Sequences: timed follow-up that stops the moment a person replies, so nobody gets a reminder after they answered
  • CRM updates: records kept current without anyone typing them up at the end of the day
  • Personalization: written to the person and what they asked about, not merged from a template
  • Quote chasing: reminders on open quotes, which is where most won work is quietly lost
  • Re-engagement: reaching back to old inquiries that were never actually closed
  • Reporting: which follow-up closes, so the pattern can be repeated

Documents and data

Information pulled out of the paperwork that arrives, such as invoices, forms, applications and reports, then checked, filed where it belongs and used to set the next step going.

  • Reading documents
  • Pulling out data
  • Summarizing
  • Filing and sorting
  • Triggering the next step
What this involves
  • Intake: email attachments, uploads and scans, taken from wherever they currently arrive
  • Extraction: pulling out the fields that matter rather than the whole document
  • Checking: flagging what looks wrong instead of passing it straight through, because silent errors compound
  • Filing: into the system where it belongs, named the way your team expects
  • Summarizing: long documents reduced to what someone needs in order to act
  • Triggering: starting the next step automatically once the information is in

Joining up your tools

The gaps between the systems you already pay for. A form that reaches the CRM, an order that reaches accounts, a booking that reaches the calendar, all without a person in the middle.

  • Website to CRM
  • Store to accounts
  • Messaging
  • Scheduling
  • Reporting
What this involves
  • Mapping: what information moves where and when, written down before anything is connected
  • Connections: website to CRM, store to accounts and bookings to calendar, which are the gaps people currently bridge by hand
  • Rules: what triggers what, including the things that should deliberately never happen automatically
  • Error handling: what happens when a system is down, so a failure is visible rather than silent
  • Monitoring: knowing when something stopped working before a customer tells you
  • Documentation: so it is not a black box only we understand

Assistants for your team

Something your people actually use: a place to ask what the policy says, to draft the usual reply, to pull last quarter's numbers, without interrupting whoever usually knows.

  • For owners
  • For sales
  • For support
  • For operations
  • Research and drafting
What this involves
  • What it knows: your policies, documents and past work, scoped to what each team actually needs
  • Who can use it: access and permissions set deliberately, not left open
  • Drafting: the replies and documents your team writes over and over
  • Lookups: finding the answer without interrupting whoever usually knows it
  • Research: summarizing what someone needs before a call, instead of during it
  • Boundaries: what it should not be trusted with, said out loud rather than discovered

It only works if it's wired into the rest.

An assistant that can't reach your systems is a toy. Here's the shape of what we actually build.

1

The job

A real task someone does by hand today, and what it costs in time.

2

The automation

An assistant or a workflow that takes the repeatable part of it.

3

Your systems

Connected to the site, store and tools you already run on.

4

The handover

A clear point where a person takes over, with the context ready.

5

What changes

The step that used to wait on someone no longer waits.

We design the handover first. Knowing exactly when a person steps in, and what they see when they do, is what separates automation people trust from automation they quietly work around.

When we'll tell you not to.

There's a lot of pressure to put AI into businesses that don't need it. These are the three answers we give most often.

Fix the process first

Automating a step that shouldn't exist makes a bad process faster, not better. Sometimes the answer is to remove the step.

A form would do it

Plenty of problems that get described as needing AI are solved by a well-built form, a template or a rule. Cheaper, and it never surprises you.

Not enough of it

If something happens twice a month, a person doing it is the right answer. Automation pays off on volume and repetition.

Automations we have built

Four of the eight, each one starting from the repetitive work that had outgrown the people doing it.

Crypto community · AI assistant

Community management assistant

A community that size asks the same questions around the clock, faster than any team can answer them. People who wait for an answer do not wait long.

Read the case study Outreach · Marketing automation

Marketing agent across Telegram, WhatsApp and email

Running outreach on three platforms meant three systems, three lists and somebody keeping them in step by hand.

Read the case study Trading community · Workflow automation

Exchange account verification and access bot

Every new member's exchange account had to be checked by hand before they could be let into the private group, so joining stalled whenever nobody was free to check.

Read the case study International services · AI assistant

Multilingual AI receptionist

Inquiries arrived from several countries, in several languages, and often at hours when nobody was at a desk.

Read the case study

All case studies

Questions we get asked

Short answers, and none of them a promise.

What can AI realistically do for a small business?

The honest answer is: the repetitive work nobody got to. Answering the same questions, replying to an inquiry the moment it arrives, qualifying leads, pulling information out of documents, and moving data between systems a person currently bridges by hand. It is rarely the dramatic thing businesses are sold.

Will an AI assistant make things up about my business?

It answers from your own documents, policies and prices rather than guessing, and its scope, meaning what it will answer and what it must refuse, is agreed before it goes near a customer. There is also a defined point where a person takes over, with the conversation attached.

Does automation mean replacing my team?

No. The handover is designed first: the point where a person steps in, and what they see when they do. The aim is that the step which used to wait on somebody being free no longer waits, not that there is nobody there.

Can it connect to the systems we already use?

Yes, and that is usually the point. Website to CRM, store to accounts, bookings to calendar: the gaps people currently bridge by copying and pasting. An assistant that cannot reach your systems is a toy.

When would you tell us not to automate something?

Three cases come up most: when the process itself should be fixed or removed rather than made faster, when a well-built form or rule would do the job more cheaply, and when something happens so rarely that a person doing it is the right answer.

The rest of the system

Website development

Business sites, landing pages, web apps.

Marketing

Search, paid growth, social and content.

E‑commerce

Shopify and WooCommerce stores.

Starting prices for all of it are on the pricing page, and what goes into every proposal is on our commitment page.

Tell us what's taking the time.

Describe the job somebody does by hand every week. We'll tell you honestly whether it's worth automating, and what it would take.

Start a conversation
hello@aniverx.com +92 310 4841746 Aniverx LLC, Connecticut, USA

Case study / Crypto community

Community management assistant

Aniverx
IndustryCrypto community
ServiceAI assistant
ClientName to add

Project overview

One of the larger crypto communities, with members in every time zone asking the same questions continuously. Moderation had become a volume problem rather than a judgment problem. Aniverx built an assistant that answers instantly, inside the channels the community already lives in.

The problem they came with

  • Volume no team could matchThe same questions arrived continuously, at every hour, from a membership spread across the world. Answering them properly would have meant a moderation team several times the size, awake around the clock.
  • Answers that had to be rightIn a community built on market information, an improvised answer is worse than a slow one. Anything automated had to answer from the community's own rules and history, not from guesswork.
  • Members do not queueAn unanswered question in a live chat is not a ticket waiting to be picked up. The person leaves, or asks somebody less reliable.

What we built

  • It answers from the community's own materialThe assistant works from the rules, documentation and past answers the community already had, so what it says is what the team would have said.
  • It remembers the conversationFollow-up questions are understood in context rather than treated as a fresh start, which is the difference between a conversation and a search box.
  • It knows where it stopsAnything outside its scope goes to a moderator with the whole exchange attached, so the member is not asked to explain themselves twice.

The results

  • Members get an answer in seconds, at any hour, instead of waiting for a moderator to come online.
  • Moderators stopped answering the same questions over and over and now spend their time on the ones that need judgment.
  • Every member gets the same answer to the same question, so what circulates in the community stays consistent.
  • The community can keep growing without the moderation team growing with it.

In short

The assistant did not replace the moderation team. It took the part of their work that was pure repetition, and handed back the hours that were going into it.

aniverx.com

Case study / Outreach

Marketing agent across Telegram, WhatsApp and email

Aniverx
IndustryOutreach
ServiceMarketing automation
Client

Project overview

Outreach was running across three platforms through three separate tools, each with its own copy of the audience. Aniverx replaced that with a single control room, so a campaign is written once and sent everywhere it needs to go.

The problem they came with

  • Three systems, three listsEmail, WhatsApp and Telegram each had their own tool and their own version of the audience. Keeping them aligned was a manual job, and manual jobs quietly go wrong.
  • Volume limited by a personHow many people a campaign reached depended on how much one person could send and track in a day, not on how many were worth reaching.
  • No single viewNobody could answer what had been sent, to whom, on which channel, without opening three tools and reconciling them by hand.

What we built

  • One place to launch fromA campaign is composed once and sent across all three channels from a single interface.
  • One audience, not threeThe list lives in one place, so the channels cannot drift apart from each other.
  • Built to be changedThe flow is visible and adjustable by the team rather than locked away, so the campaign structure can change as the business does.

The results

  • A campaign now goes out across all three channels from one interface, written once.
  • The audience is maintained once instead of three times, so the channels stopped disagreeing with each other.
  • Sending volume is no longer capped by how fast somebody can copy and paste.
  • The team can see what was sent, where, without opening three tools.

In short

Three jobs kept in step by hand became one job, run from a tool the team already had open.

aniverx.com

Case study / Trading community

Exchange account verification and access bot

Aniverx
IndustryTrading community
ServiceWorkflow automation
Client

Project overview

Access to a private trading group depended on someone manually checking each applicant's exchange account. Aniverx automated the check and the invite, so joining no longer waits on a person being available.

The problem they came with

  • Onboarding stalled on availabilityEvery applicant needed a manual check before being let in. Outside working hours, which is most hours for a global membership, that meant waiting.
  • The delay cost the sign-upPeople are at their most engaged in the minutes after they commit. A queue at exactly that moment is where they go quiet.
  • Repetitive, and therefore error-proneThe same lookup repeated hundreds of times is precisely the task where mistakes creep in and nobody notices.

What we built

  • The check happens automaticallyThe applicant's account is confirmed against the exchange itself rather than taken on trust.
  • Access follows immediatelyOn a successful check, the private invite is issued and sent without anyone being asked to do it.
  • It runs continuouslyThree in the morning works the same way as the middle of the afternoon, including at weekends.

The results

  • A verified member is inside the group within moments of applying, at any hour.
  • Onboarding no longer stops overnight or at weekends, and the backlog that used to build up has gone.
  • Access is granted on checked data rather than on somebody's judgment call.
  • The team stopped spending their day on identical lookups.

In short

Onboarding stopped being a queue. The step that used to need a person is now the fastest part of joining.

aniverx.com

Case study / International services

Multilingual AI receptionist

Aniverx
IndustryInternational services
ServiceAI assistant
Client

Project overview

A business with customers in several countries was losing inquiries to time zones and to language. Aniverx deployed a receptionist that answers whenever an inquiry arrives, in the language it arrives in, and turns the conversation into a booking and a record rather than a message in a queue.

The problem they came with

  • Inquiries arriving out of hoursA global audience does not share your working day. Messages sent overnight waited until morning, by which point the sender had often found somebody else.
  • A language barrier at the front doorStaffing a genuinely multilingual desk is expensive. The alternative, answering in English and hoping, loses people at the first message.
  • Inquiries that went nowhereEven the ones that were answered often did not become anything, because there was no reliable step between the first reply and the sales team.

What we built

  • It replies in the inquirer's languageThe conversation happens in the language the customer started in, rather than being pulled into one the business happens to speak.
  • It books, rather than promising toWhere an appointment is the right next step, it is made during that first conversation instead of after three messages back and forth.
  • Every inquiry is recordedEach conversation is written down in full, so nothing depends on somebody remembering to pass it on.

The results

  • Inquiries get a reply at the moment they are sent, including overnight and at weekends.
  • The first reply is in the customer's own language, so the conversation does not stall at hello.
  • Appointments are booked inside that first conversation rather than after a chain of messages.
  • Nothing is lost between the first message and the sales team. Every inquiry is on record.

In short

The front desk stopped being limited by office hours and by which languages happened to be on staff that week.

aniverx.com