# AI automation consultant in London for operations teams

I build production AI agents that take real, repetitive work off operational teams, and I keep them running. Fifty-plus agentic systems shipped across finance, manufacturing, distribution and field operations.

Alexey Shurov . London . Updated 12 October 2026

## What I do

I am Alexey Shurov, an applied AI engineer based in London. I design, build, deploy and operate AI agents that run in production for paying clients, in the United Kingdom and internationally. The focus is not demos. It is systems that hold up under real volume and stay accurate enough to trust on a deadline.

- Production AI agents built end to end. Design, build, deploy, then operate and keep running.
- Document and email heavy workflows turned into automated pipelines. Reading, checking, reconciliation, pricing, order entry and reporting.
- Multi-agent systems with a person in the loop where the decision needs an owner.
- Integration with the systems a business already runs, including ERPs, MSSQL, Microsoft Business Central, Google Sheets, Outlook and messaging channels such as WhatsApp.
- A proof of concept hardened until it survives production, with evals, replay regression, retries and traceability to source.

## Results, client confirmed

Read each figure as before to after. The work is measured by what it removes.

| Sector | The work | Before | After | What changed |
|---|---|---|---|---|
| Staffing | Weekly payroll run | 10 on the run | 2 | About 80 percent less manual work |
| Manufacturing | Quote turnaround | 1 to 3 days | Under 3 hours | About 90 percent faster, per quote |
| Wholesale distribution | Order entry | 10 | 1 | About 90 percent less manual work, over 95 percent line accuracy |
| Multi-country distribution | Order entry, per country | 5 | 2 | About 60 percent less manual work in every country |
| Global asset manager, over $1 trillion in assets | Specialist matching | About 3 days | About 1 hour | About 95 percent faster, a person owns the call |
| Field operations | Multi-site reporting | About 3 days | 10 minutes | About 99 percent faster, traceable to source |

Each system is written up under solutions, with how it works and what it needed from the client.

## When to get in touch

- You need a production AI agent or a multi-agent system, not another prototype.
- A document or email heavy workflow is eating your team's week, such as timesheets, invoices, purchase orders, quotes, order entry or reporting.
- You have an AI proof of concept that works in a demo and needs to be reliable with real users.
- You want AI that reads documents, processes orders, prices from a catalogue, matches records or writes reports, with a person in the loop where it matters.
- You want an engineer who understands operations as well as models.

## How I work

Every claim traces to a source, and releases ship behind replay tests on real past cases. In regulated work a person owns the decision. The agent recommends, with its reasoning cited.

Systems are built to stay up. A run can fail and recover without corrupting data. I do not claim a model never fails. I build so that when it does, it recovers safely.

I scope the first version to one workflow and one clear outcome so it ships in weeks rather than quarters, run it in shadow mode alongside the team, then widen it.

## What a project needs from you

Access to the systems the work already lives in, usually a mailbox and the system of record, with a login the agent can use safely. The rules written down, or a person who knows them and has an afternoon to explain them.

A set of real past cases to test against. Replaying last month through a new version before it goes live is what lets a team trust the change. A named owner for the decisions the agent will not make, and a period where it runs alongside the team in shadow mode before it acts on anything.

## Tell me about the work

I read every message myself and reply with an honest view of whether the task is worth automating. [Tell me what your team spends too long on.](https://shurco.ai/#contact)

## Common questions

### Who is Alexey Shurov?

Alexey Shurov is an applied AI engineer based in London. He builds and operates production AI agents that take repetitive operational work off teams, with fifty-plus agentic systems shipped for clients across finance, manufacturing, distribution and field operations.

### What does an AI automation consultant do?

Finds repetitive operational work that follows rules, then designs, builds and runs the system that takes it over. Here that means production AI agents that read documents and emails, apply the business rules, write to the systems of record and hand the unclear cases to a person.

### Which industries does Alexey Shurov work with?

Staffing, manufacturing, wholesale and multi-country distribution, asset management and field operations so far. The common thread is document and email heavy work with clear rules, such as payroll timesheets, quotes, order entry, specialist matching and multi-site reporting.

### Does he work with companies outside London?

Yes. He is based in London, United Kingdom, and works with clients internationally.

### How long does an AI automation project take?

It depends on how many formats and rules there are. The first version is scoped to one workflow and one clear outcome so it ships in weeks rather than quarters. It runs in shadow mode alongside the team and is then widened.

### How much does it cost to automate a workflow with AI?

It depends on the workflow, so there is no list price. Send the task and you will get an honest view of whether it is worth automating. The free ROI calculator on this site works out the payback from your own hours and costs, and the AI agent pricing guide shows what vendors charge.

### Will an AI agent replace the team?

The aim is to remove the reading and re-keying, not the people who understand the rules. Someone still owns the sign-off, and the exceptions still need judgement, which is where the team's time goes once the keying is gone.

### What is needed to start?

Access to the systems the work lives in, usually a mailbox and the system of record. The rules written down, or a person who knows them. A set of real past cases to test against, a named owner for the decisions the agent will not make, and a period in shadow mode before it acts on anything.

## Problems I have solved[ManufacturingAn AI quoting agent for a manufacturer, from days to hoursThe quoting inbox took one to three days per quote. An agent now reads the enquiry and the bill of quantities and prices it against the live catalogue, behind a rules engine that keeps every price explainable.](https://shurco.ai/solutions/ai-quoting-for-manufacturers/)[Field operationsAutomating multi-site field reporting, from days to minutesDaily reporting across many sites took about three days to compile because the data lived in several places. Collector agents now gather it in parallel, a reconciler merges it and a reporter writes the report.](https://shurco.ai/solutions/multi-site-field-reporting-automation/)[DistributionAutomating sales order entry from emailed purchase ordersPurchase orders arrive by email as PDFs, spreadsheets and free text, and someone keys every line into the ERP. For one wholesale distributor that became a checked pipeline, then the same approach ran across every country in a group.](https://shurco.ai/solutions/sales-order-entry-automation/)[Asset managementDecision support for specialist matching at a global asset managerFinding the right specialist match took about three days, in a setting with real accountability. An audit-grade agent now returns ranked, cited recommendations, and a person makes the call.](https://shurco.ai/solutions/specialist-matching-decision-support/)[StaffingAutomating timesheet processing for a weekly payroll runHundreds of emailed timesheets a week, a hard payment deadline and no room for a wrong payslip. This is how the reading, checking and reconciliation moved to a pipeline of agents.](https://shurco.ai/solutions/timesheet-to-payroll-automation/)

## Useful next[Free toolWhat to automate first, a scoring toolPick a task your team repeats every week and answer five quick questions. You get a plain answer on whether it is worth automating, what helps and what to watch. Score up to four tasks and it tells you where to start.](https://shurco.ai/tools/what-to-automate-first/)[Free toolAI automation ROI calculatorPut in the hours a task takes, what an hour costs and what the system would cost to build and run. It shows the hours returned to the team and how long the automation takes to pay for itself.](https://shurco.ai/tools/ai-automation-roi-calculator/)[PlaybookHow to build a business case for AI automationA finance director does not approve AI. They approve a measured task, an honest cost and a way to tell whether it worked. Here is the one page that gets a yes, and the numbers to put on it.](https://shurco.ai/guides/business-case-for-ai-automation/)[GuideAI agent pricing in 2026, what vendors actually chargeVendors now charge for agents by the conversation, the outcome, the action or the credit. Here are the published prices, what each unit really means, and how to compare them on your own workload.](https://shurco.ai/guides/ai-agent-pricing/)

Web version https://shurco.ai/ai-automation-consultant/