Request automation

Form goes to CRM, notification to the right person, and task to the calendar. No manual retyping.

• individuallyScope
• AI and automationsArea
• 6 hours – 2 daysLaunch

Who this is for

Companies receiving leads from multiple channels.

Problem

Inquiries get lost in emails and messages. This applies to companies that receive leads from multiple channels at once and don't have one place where everything lands.

What we do

We set up the lead journey from start to finish: form → CRM → notification → task. No manual entry at any stage.

What's included

Four stages, we start with the map, not the tool:

• Process map
• Integrations
• Testing
• Launch

Timeline

Implementation takes 6 hours – 2 days. Stages are process map, integrations, testing, and launch.

Pricing

What counts is how many routes enquiries reach you by and how many places they then have to be wired into — one form is different work from a form, a chat, a phone line and a messenger at once.

What you get

Order and faster response to every lead.

Where inquiries actually get lost in your business

We automatically analyzed the websites of Warsaw-based companies and found two points where an inquiry disappears before it ever reaches a person. Among 16,592 Warsaw-based companies whose websites we analyzed automatically, 14.3% are visible only on a third-party platform — they have no place of their own where someone could leave contact details. Another 9.4% have a registered domain, but the site did not load at the time of the check (automated scan, July–August 2026).

The third leak point is no longer a missing website — it's what happens AFTER the inquiry reaches you: the message lands in one of several inboxes, nobody sees it the same day, and the client is already calling a competitor.

The formula for the cost of the routine hour automation takes over

Before calculating whether automation pays off, it's worth calculating what doing it manually costs today. The formula is simple, and deliberately contains no number from us — you plug in all of them yourself:

• t — the time one person spends manually copying a single inquiry from email or a messenger into the CRM, in hours
• s — that person's hourly rate, meaning their cost to the company per hour of work, not just take-home pay
• n — the number of inquiries per month, meaning how many times this same action repeats
• Monthly cost of the routine = t × s × n

Compare the resulting amount with the implementation price from the service's price list — that's the only honest comparison, because you calculate both sides from your own data, not someone else's estimate.

Four routes an inquiry can take into your business — and how handling them differs

An inquiry can come in through four different channels, and each handles the same question differently: will anyone see it the same day.

• A website form — data arrives in a fixed format, but often into a single inbox checked once a day
• Phone — the fastest for the client, but depends on whether anyone happens to pick up, and leaves no trace without a manual note
• Messaging apps (WhatsApp, Messenger) — the client expects a reply within minutes, and the message easily gets lost among that same person's private chats
• Email — leaves a trace and a timestamp, but lands in a shared inbox without being assigned to a specific person or case

Automation doesn't replace any of these channels with another — it pulls them into one place, so an inquiry from any of them lands in the same queue instead of getting lost in whichever channel nobody happened to check.

What here is actually AI, and what is just a rule

To be honest: most of what's called “inquiry automation” is rules and thresholds, not artificial intelligence — we'd rather say that plainly than call arithmetic something it isn't.

• Rule (not AI): “an inquiry from form X goes to person Y” — that's a plain redirect based on a fixed condition
• Rule (not AI): “if an inquiry has no reply after 4 hours, send a reminder” — that's a time threshold, not reasoning
• Language model (AI): understanding what a freely written message is about and assigning it to the right category or person
• Language model (AI): pulling specific data out of a client's long description — a date, an address, a type of service — into CRM fields

Which of this is in scope gets settled at the process-mapping stage — the more free text needs to be understood, the more work falls on the language model rather than plain rules.

When inquiry automation doesn't pay off

Not every business benefits from this service, and it's better to check that before starting than after.

• You get a handful of inquiries a month, not dozens — the cost of maintaining automation can exceed the cost of manually copying those few messages
• Every inquiry needs a long phone conversation with an individual quote anyway — automation only speeds up the logging, not the conversation itself
• The business hasn't yet decided who should get which inquiry — without that decision, automation gets a rule to implement, not a problem to solve
• Inquiry channels change every month (new ad, new platform) — reconfiguring won't keep up with the change any faster than manual redirection would

What you need to have on your side

Implementation starts with your data and your decisions, not with our tool.

• Access to the channels inquiries currently come from: inbox, form, messenger, ad account
• Access to the CRM or wherever inquiries should land, along with configuration rights
• A list of who different types of inquiries should go to, and the rules for assigning them
• One decision-maker on your side — changing the rules mid-implementation extends the timeline the most

How to check after a month whether it's working

Agree on the metrics before you start, and calculate them from your own data — not from the impression that “it feels better now”.

• Time from an inquiry arriving to the first response — from CRM logs, not memory
• The number of inquiries that actually reached the CRM, compared with form visits or calls from your billing records
• The number of inquiries with no assigned person after 24 hours — should drop to zero
• The number of manual re-entries of the same information from one system to another — should drop to zero

Compare the same period with the same period — not the implementation month with a vacation month.

The most common mistake when implementing inquiry automation

The costliest mistake isn't a bad CRM setup — it's implementing automation on rules nobody in the company can actually state out loud. The rule “rental inquiries go to Kasia” works as long as Kasia is there — but when she's replaced, automation keeps sending inquiries to the old address, because nobody reported the change.

What this service doesn't do: it doesn't judge whether an inquiry is worth pursuing, doesn't negotiate price with the client, and doesn't replace a conversation where a decision needs a human. It watches over one thing — that no inquiry sits unanswered just because it landed in the wrong place.

What you get

• Map of enquiry sources and destination systems
• Field mapping, lead routing and task-creation rules
• Internal alerts, error handling and end-to-end flow testing

When the problem lies elsewhere

If your problem sounds different, neighbouring areas of the same system stand right next to it — AURA connects them to each other rather than selling them separately:

• AI lead qualification — AI evaluates and tags inquiries by potential before anyone starts calling back. The team starts with the best inquiries, not the newest.
• AI follow-up — Message sequences for those who didn't respond. Second and third reminder go out on their own, at set time and with stop condition.
• CRM and automations — Requests, reminders and client data work on their own, without re-entry from paper to calendar.
• AI Reports — Weekly summary of leads, campaigns and sales, written in simple language and sent on its own. Instead of a dashboard that nobody checks.