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// AI automation for organizations

We find the manual work that costs you most — and engineer it away

OneZero specifies, builds and connects automation into the systems you already run — from diagnosing the process to a stable system running in production.

See what can be automated

Discovery · UX · Engineering · Integration · QA · Security · DevOps

  1. INTAKESourcesDocuments · Inbox · CRM · Manual entry
  2. AI LAYERProcessingCLASSIFY · EXTRACT · ROUTE
  3. VALIDATEChecks
  4. APPROVEHuman sign-off
  5. SYSTEMSOutcomeERP · TASK · REPORT

// 01 · The symptoms

How much of your team's day still goes into manual work?

  • Data retyped from one system into another

    The same fields, keyed in again and again. Every keystroke is a chance to get it wrong, and nobody can tell you where it happened.

  • Documents waiting to be processed and approved

    Invoices, forms and orders parked in an inbox until somebody has a free hour.

  • Leads that get an answer too late

    An enquiry answered hours later is worth a fraction of one answered on the spot.

  • Reports that depend on manual collection

    By the time the numbers are tidy in a spreadsheet, the decision has been made without them.

// 02 · Process x-ray

Pick a process and see how it runs today — and how it could run

One process, two versions. What happens now, what can be built instead, and the measures that tell you whether it actually worked.

Documents arriving from every channel, keyed in by hand and waiting for sign-off.

Today

  • The document arrives by email, WhatsApp or scanner
  • Someone opens it, reads it and types the fields into the system
  • Mismatches only surface at month-end close
  • Approval waits on one person being available

After automation

  • Automatic intake from every channel into a single queue
  • Fields extracted and the document classified by type
  • Values checked against the order, contract or payment terms
  • Only exceptions are escalated for a human decision
  • The system of record updates with a full audit trail

What we measure

  • Time from receipt to a booked record
  • Share of documents processed without human touch
  • Errors found after posting
  • Throughput during peak periods

// 03 · What we build

We don't bolt on AI for the headline. We build a process that holds.

Document intelligence

Intake, field extraction, classification and matching for documents arriving from any channel — including scans and photos.

Operational agents

Agents that carry out a sequence of actions against your systems, inside limits and permissions defined up front.

System integrations

Connecting CRM, ERP, core systems and APIs — with failure handling and monitoring built in.

Knowledge & retrieval

Search and answers grounded in your procedures, contracts and documents, with a link back to the source.

Customer operations

Digital-channel response, routing by enquiry type, and handover to a person with the full context.

Reporting & decision support

Automated collection, operational metrics and exception alerts — instead of a spreadsheet somebody maintains by hand.

// 04 · How it works

From a heavy process to a system that runs — in four stages

  1. Audit

    We map the process, what it costs, where it jams and how it fails.

  2. Blueprint

    We design the flow, the integrations, the controls and the success measures.

  3. Build & Integrate

    We build the solution and connect it to the systems you already run.

  4. Operate & Improve

    We go live in controlled steps, measure, and keep improving.

// 05 · Where it lives

Automation has to live inside your operation — not in a separate tab

What we connect to is decided by what you already run and what those systems allow. In every project we check permissions, throughput, API limits, and what happens when one side goes down.

The connection list is settled during discovery, against your architecture.

  • CRM
  • ERP
  • Legacy systems
  • APIs
  • Email
  • WhatsApp
  • Documents & data stores
  • Internal systems

// 06 · Control

Automate where it's safe. Keep a person where it matters.

Roles & permissions
Who is allowed to run, approve and change what — defined up front.
Human approval
Sensitive steps wait for a person to decide.
Audit logs
Every action is recorded, including who approved it and when.
Exception handling
Anything that fails the rules is routed for handling instead of quietly disappearing.
Privacy & security
We define which data is exposed, where it flows and how long it is kept.
Monitoring
Alerts for failures, slowdowns and unusual behaviour.
Stop & hand over
Any flow can be paused or handed back to a person at any point.

// 07 · Measurement

The technology isn't the measure. The process is.

  • Handling time
  • Manual hours
  • Error rate
  • Response time
  • Volume handled
  • Exceptions needing a person
  • Financial impact

We agree the measures with you at the start and baseline them against how things work today. We don't quote numbers that weren't measured.

// 08 · Why us

A full software house. Without the weight of a giant, or the risk of something improvised.

  • One team, start to production

    The people who mapped the process are the people who ship it.

  • Built for complexity

    Systems with many users, a lot of data and plenty of edge cases.

  • Product, UX and engineering together

    The process is designed around the people running it, not only the code.

  • Fits your existing stack

    We work with the systems you already have, legacy included.

  • QA, DevOps and monitoring

    Testing, a controlled rollout and support once the system is live.

  • Shaped to your process

    Not a one-off automation nobody knows how to maintain.

// 09 · From our work

One project already working this way

OneAI

Voice agents that update the systems in real time

The problem
Organizations run conversations at scale, but what is said in a call never reaches the systems unless somebody types it in.
What we built
A voice-agent platform that reads the relevant information before a call and connects to CRM, calendars, telephony, messaging and lead management — with an API for embedding the same capabilities elsewhere.
What changed
Call outcomes are written back to the connected systems in real time, so follow-up no longer depends on a manual summary.
Read the full story

Processes that can become an intelligent flow

Illustrative examples of the kind of process that fits — not delivered projects.

  • Supplier invoice intake, matched against purchase orders
  • Onboarding a new customer across CRM and the core system
  • First-line response to service enquiries on digital channels
  • Assembling a weekly operations report from several sources

// 10 · Questions

Questions we get asked

What is an AI Process Audit?

A working session that maps one process end to end: who is involved, how long it takes, where it jams and where mistakes creep in. You come out with a view of what can be automated, what is better left manual, and in what order to tackle it.

Which processes are a good fit?

Repetitive work that follows clear rules and crosses several systems. The more often it runs and the more predictable its inputs, the faster it pays back. A process that is reinvented every time usually isn't a fit.

Do we have to replace our current systems?

No. In most cases we build a layer on top of what you already run and connect through an API or a dedicated integration. Replacing a system is a separate decision, not a prerequisite.

Does the whole thing run without people?

No, and that isn't the goal. The repetitive part runs on its own; sensitive decisions and unusual cases go to a person. The team moves from data entry to oversight and to the cases that genuinely need judgement.

How is sensitive data handled?

At the start of the project we define which data is actually needed, where it flows, who may access it and how long it is retained. Permissions, audit logging and monitoring are part of the build rather than a later addition. Specific regulatory requirements are checked against your own legal and compliance team.

How long does it take to build?

It depends on how complex the process is, how many systems have to be connected and how much control is required. The audit produces a grounded estimate before anyone commits to a build — not before.

Can we start with a single process?

That is usually the right way in. Pick one process with real volume and clear boundaries, put it live, measure it, and only then widen the scope. It also lets the organization get used to working with the system without betting much on it.

How is this different from an off-the-shelf tool?

An off-the-shelf tool is excellent when your process looks like the one the tool assumes. The moment there is a legacy system, an unusual business rule or an approval chain of your own, people start working around the tool. A custom build is shaped around the real process, edge cases included, and stays yours to maintain and extend.

// 11 · Next step

Got a process that feels heavier than it should? Let's find out if it's worth automating.

In an AI Process Audit we map the process end to end, find the bottlenecks, and identify what can become a connected, measurable flow.

No slide deck. Just one real process of yours.

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