AI automation

Automate the work nobody
should be doing by hand

The work worth automating is rarely glamorous. It is the triage, the copying between systems and the report somebody rebuilds every Monday. We find it, automate it, and leave a person in charge of the decisions that matter.

Rated 4.9 on Clutch across 38 reviews


1-2weeks to map where
the manual work actually is
4-6weeks to a first workflow
running in production
100%of automated actions
logged and reversible
0silent failures. Every run
reports its own outcome

Where it pays off

Six patterns account for most of the manual work we find. Each one is measurable before and after.

Triage and routing

Tickets, leads and email sorted, tagged and sent to the right queue as they arrive, with the reasoning attached.

Data entry

Documents, forms and emails turned into records in your system, with anything uncertain sent for review instead of guessed.

Recurring reports

The weekly summary somebody assembles by hand, generated from the source systems and delivered on schedule.

Approvals

Requests checked against your rules, the routine ones cleared automatically, the rest escalated with the context already gathered.

System-to-system

Records kept in step between tools that have no integration, without anyone copying fields between two browser tabs.

Monitoring and alerts

Watching for the conditions your team currently notices by accident, and telling the right person while it still matters.

How it works

Every automated action is logged with what it saw and why it acted, so an error can be found and undone rather than argued about.

Your side

What triggers it

  • New ticket, lead or email
  • A file dropped in a folder
  • A schedule or a threshold
  • An event from your app
What we build

The automation layer

  • Classification and extraction
  • Your business rules, explicit
  • Human review where it matters
  • Full audit log of every action
  • Retries and failure alerts
Behind it

What it touches

  • Your CRM, helpdesk, ERP
  • Databases and spreadsheets
  • Email and messaging
  • Anything with an API

How we work

We automate one workflow properly before touching a second.

1

Watch the work

One to two weeks sitting with the people doing it. The workflow that looks worst on paper is often not the one worth automating first.

2

Model the rules

Writing down the decisions your team makes without thinking. This step usually surfaces disagreements worth resolving anyway.

3

Build with a human in it

The first version proposes and a person approves. You see exactly what it would have done before it is allowed to do it.

4

Loosen the leash

Once the approval rate is consistently high, the routine cases go through automatically and the rest keep escalating.

5

Operate

Volume handled, escalation rate, errors caught and time returned to the team, reviewed against the baseline we measured first.

Built by a team that ships

The AI layer is new. The engineering underneath it is not. These are products we designed, built and still maintain.

Planable Omniconvert Wolfpack Digital OPEN social CANGO Mobility Zerotak TaskManager Bookster Life in Codes HCT Envision Tickbird
VerityPanel Market research platform

Data collection at scale

A digital market study and data-collection platform built for fast, reliable research at scale.

Product development · Frontend
Mobility Mobility

Fleets, tracked

CANGO Mobility builds fleet and mobility software for operators managing vehicles at scale.

Product · Web development
IT and software services IT and software services

Tooling for teams

Life in Codes helps teams work more efficiently, implementing collaboration and code-quality tooling as an Atlassian partner.

UX/UI · Frontend

How it is built

Automation earns trust slowly and loses it instantly. These choices are all about staying reversible.

Webhooks, polling, schedules or a file drop

Whatever your systems already emit. We avoid asking your team to change how they work to suit the automation.

Rules, a model, or both together

Rules where the logic is known and stable, a model where it is fuzzy. Most real workflows want both, in that order.

Approve everything, sample it, or only see the exceptions

Every workflow starts at approve-first. Moving to exception-only is a decision you make on evidence, not a launch setting.

A trace on every run, outcome logs and alerts

A run that fails quietly is worse than one that fails loudly. Every execution reports what it did and what it saw.

Your cloud, our managed runner, or on-prem

Automations touch live systems, so this usually follows wherever your other backend services already run.


“What impressed us most was their deep technical expertise combined with a proactive, solution-oriented approach.”

Denisa Ursu · Founder, Bride to Bride Verified review on Clutch

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Frequently asked questions

We spend a week or two with the people doing the work. The volume is rarely where managers expect it, and the workflow that looks worst on paper is often not the one worth automating first.

Every workflow starts approve-first: it proposes, a person confirms. Nothing runs unattended until the approval rate has been consistently high for long enough to justify it, and every action is logged and reversible.

In our experience it removes the part of the job people already dislike: the copying, the sorting, the chasing. What it frees up is time, and the teams that get the most out of it decide in advance what that time is for.

Usually. Anything with an API, a webhook or an inbox can be connected. Where a system has none of those, we say so early rather than building something fragile around it.

We record the baseline before building: volume, handling time, error rate. Afterwards the same numbers are on a dashboard, so the argument about whether it helped is settled with data.

One to two weeks to map where the manual work actually is, then four to six weeks to a first workflow running in production with a person still in the loop.