Unlocking Tech
01 /

AI automation services

Automate the work nobody should be doing by hand.

Our AI automation services take the high-volume, repetitive work your team does by hand — invoice processing, data entry, lead routing, reconciliation — and rebuild it as AI agents and workflows wired to your real systems. Business process automation measured in task-time saved, not features shipped.

Illustrative examplePick a step to see it in detailA supplier invoice, from email to an ERP draft
  1. A PDF in the shared invoices inbox. The automation reads it with its own credentials, never a person's login.

    From
    billing@example-supplier.com
    Attachment
    INV-2026-412.pdf
  2. OCR and AI extraction read the fields the posting needs.

    Supplier
    Example Supplier Ltd
    Net + VAT 23%
    €1,250.00 + €287.50
    Total
    €1,537.50
  3. The supplier exists in the ERP, the sums add up and the invoice hasn't been posted already. Whatever fails becomes an exception.

    Supplier, total, duplicate
    pass
    Purchase order
    line 2 has no match → exception
  4. Only what doesn't match goes to a person, with the PDF and the reason side by side. The decision is logged.

    Decision
    accounts match the line to the right order
  5. The purchase document is created as a draft through the API (Primavera, PHC or your ERP) and accounts confirm the posting. What came in, what the AI decided, what was written and who approved are all logged.

    Status
    purchase invoice draft, awaiting confirmation

Fictitious invoice, supplier and amounts. The document always stays a draft in the ERP until a person confirms it.

02 /

Selected work

Case study· Portugal

Seed Real Estate · AI deal-management workflows

AI-powered deal management and financial reconciliation for a real estate investment team.

Problem
No centralised visibility. Operational failure risk multiplying.
Approach
Two parallel AI-orchestrated workflows in n8n: operations and finance, each independent.
Outcome
Real-time visibility per deal. AI handling the heavy categorisation work.
  • 2AI workflows orchestrated in production
  • 6hBank statement reconciliation cycle, autonomous
  • AITransaction categorisation via OpenAI
PortugalGrupo Filtrarte · AI agents for retail lead automation

Two AI agents replacing manual lead routing and review collection across HORECA channels.

15 minLead verification cycle, fully autonomous
BrazilOmniTrade Brasil · AI agent for B2B lead qualification

AI agent automating 1,200 CSV files per month from prospecting database to CRM.

1,200CSV files autonomously processed per month
03 / At a glance
The short answer

Unlocking Tech is an AI engineering company based in Lisbon, Portugal, providing AI automation services to SMEs and scale-ups in Portugal, the UK and the rest of Europe. We take one high-volume workflow — invoice processing, data entry from email and documents, lead routing, bank reconciliation — map it, and rebuild it as an AI agent or workflow wired into your CRM, ERP and inbox, built in n8n or in custom code depending on volume and risk. Each workflow is fixed-price, reaches production after two to four weeks of build, runs with a person approving the ambiguous cases and an audit trail of every action, and is measured in task-time saved against a manual baseline. Your team owns it, or we operate it monthly.

Average task-time reduction
78%
Typical time to the first workflow in production
2–4weeks
Audit logged by default
100%
Not juniors. Not freelancers. Principal engineers only.
Seniorengineers
Typical response time
24h
04/What you get

Everything you need.Built for production.

No prototypes. No guesswork. Just production-ready systems that save time, reduce errors and scale.

Measured before and after

  • A documented map of the workflow

    Your current process written down step by step — who does what, in which system, how long it takes, and where it breaks. Useful on its own, even if you stop there.

  • Hours back per week, measured

    Task-time saved reported against the manual baseline we captured before building — not a vague efficiency gain. Across shipped agents we've averaged a 78% task-time reduction.

Connected, with a person in the loop

  • Connected to the systems you already run

    Read/write links to your CRM, ERP, inbox or database via API or webhook. The automation joins your stack; there's no migration and no parallel tool to maintain.

  • A human still in the loop where it counts

    Approval queues, confidence thresholds and exception routing to a person. Judgment stays with your team; only the mechanical steps are automated.

Auditable, with an owner

  • An audit trail of every action

    What ran, what it did, what it skipped and why — logged. The automation is reviewable, not a black box you have to trust.

  • A clear owner after go-live

    Either we operate and maintain it on a monthly basis, or your team takes it over with a runbook and handover. No orphaned automation.

05/How we work

How we work.From manual to production, fast.

Five steps from one painful workflow to a measured, owned automation in production.

  1. 01SCOPE
    Process call

    30 minutes to pick one high-volume workflow that hurts. We confirm the volume, who does it today, the systems involved and the access we'd need. An engineer, not a salesperson.

  2. 02MAP
    Map the process

    We document the workflow end to end and mark which steps need human judgment and which are mechanical. We capture the manual baseline — minutes per task times volume. This is where we tell you honestly if it shouldn't be automated.

  3. 03BUILD
    Build against your real systems

    A working automation in staging within days, wired to your actual data with read/write access, with human-in-the-loop checkpoints where the map said judgment matters.

  4. 04QA
    Run in parallel and QA

    The automation runs alongside the manual process on real cases. We compare outputs, tune the rules and prompts, and only hand off the steps it's provably reliable on. Nothing goes live on trust.

  5. 05GO LIVE
    Go live and measure

    Production with monitoring. We report task-time saved against the baseline from step two. Then we either operate it monthly or your team takes it over with the runbook.

06/Who it's for

We’re not for everyone.We’re for operators who are ready to fix it.

If any of these sound familiar, we should talk.

01

COO or Head of Operations

Leading a 50–300 person company

You're dealing with

  • Hours a day lost to invoice entry, order processing or reconciliation
  • The next move is hiring two more people, and you'd rather not
  • You have the systems, but not the engineering to connect them

What you're after

You need the manual back-office work rebuilt as software, without adding headcount.

Outcome

Operations run smoother, with less effort and more control.

02

Founder or CTO

Whose team’s time is going to glue work

You're dealing with

  • Engineers and ops staff babysitting integrations and copying data between SaaS tools
  • Reports assembled by hand, quietly eating senior capacity
  • A fragile chain that breaks silently and has no owner

What you're after

You need the glue work gone, owned and reliable — not a fragile chain.

Outcome

Your team builds again. Instead of maintaining duct tape.

03

Teams outgrowing RPA or no-code tools

Past the easy 60%, stuck on the rest

You're dealing with

  • The remaining 40% needs judgment rule-based RPA can't handle
  • A no-code flow that's become spaghetti nobody trusts
  • No proper error handling and no one senior owning the architecture

What you're after

You need AI in the loop, real error handling and a senior owner for the architecture.

Outcome

Production-grade automation you can trust at scale.

We work with a few companies at a time.
If this is you, let’s build it right.

Senior engineers. No handovers. No fluff.

07 / In depth

07.1AI automation services

What do AI automation services include?

AI automation services cover five things, and the price reflects all of them: mapping the process to find where the hours actually go; designing the workflow and its failure modes; building the workflow automation and wiring it into the systems you already run — CRM, email, ERP, spreadsheets; the reliability layer that separates production from a demo — error handling, escalation to a person on ambiguous cases, logging, a cost ceiling per run; and operating it with the result measured in task-time saved.

Read more

The first two weeks are mapping and design, the rest is build — you see the workflow running against your real data before the end of the first month.

Business process automation with AI: what to automate first

Start with the process that scores highest on six things: volume (dozens a day, not a few a month), repetition (mostly the same format), input quality (native PDFs and digital data beat bad scans), an integration surface (a documented API), a low cost of error (the output lands as a draft a person checks) and a clear owner. In practice the winners are almost always the same: invoice processing into the ERP, data entry from email and documents, lead generation and routing into the CRM, bank reconciliation, support triage and the weekly report someone still builds by hand. Score each candidate from 1 to 5 per line: above 20 it's worth building, below 14 leave it for later. Operational efficiency comes from doing one of these well, not five badly.

AI automation examples: three workflows in production

Seed Real Estate, Portugal: two workflows in n8n — one moves deal management from ClickUp to Slack with Airtable as the system of record, the other reconciles bank statements against InvoiceXpress invoices and uses OpenAI to categorise each transaction; reconciliation now runs on its own in a 6-hour cycle and Excel is gone as the system of record. OmniTrade Brasil: an AI agent reads 1,200 construction-project CSV files a month, scores each lead against configurable rules and pushes the qualified ones into HubSpot, turning days of manual screening into hours. Grupo Filtrarte, Portugal: two AI agents — lead routing and post-service review collection — working across HubSpot, Outlook, WhatsApp and Google Sheets; lead verification takes 15 minutes and no leads are lost to slow manual routing.

07.2Tools, cost and ROI

AI automation tools: n8n, Make, Zapier, Power Automate or code?

We pick the tool per workflow, after the process map, not before. n8n is what we use for most business workflows: it can be self-hosted, keeps data inside your infrastructure when it has to, and lets us drop into code where a node isn't enough.

Read more

Zapier and Make are fine for simple SaaS-to-SaaS triggers your team can own. Power Automate makes sense when you already live in Microsoft 365. Robotic process automation (RPA) tools such as UiPath drive a screen the way a person would — useful for a system with no API, fragile when the screen changes. Intelligent automation is RPA plus AI — today mostly generative AI — for the unstructured parts; agentic AI goes a step further and lets an LLM choose the next step within guardrails. When volume, latency or compliance demand it, we write custom code instead.

What does AI automation cost? Pricing and ROI

A first serious AI automation project typically lands between a few thousand and a few tens of thousands of euros, at a fixed price per workflow agreed before the build; our packaged AI agents start at a one-off setup of €1,500 per agent for a single workflow. What moves the number is rarely the model: it's how many systems the workflow touches, whether they have a documented API, how messy the inputs are and how many exceptions need a person. On top sit two running costs — operation, monthly if we run it, and model usage, capped per run. The ROI test is simple: hours saved per week × loaded hourly cost × 52, against the build plus 12 months of running cost. If it doesn't pay back within 12 months at today's volume, we tell you to wait — and you keep the process map.

How to choose an AI automation partner (and when not to hire one)

Ask four questions and listen for specifics. What happens when the workflow fails at 3am? Without exception routing and alerts there is no reliability. How will we know it works? There should be a metric and a manual baseline before anything is built. What does it cost to run in the worst month? No cost ceiling means the budget is a guess. Who owns what gets built? The workflows, the code and the credentials should be yours, with no lock-in. Then ask who actually builds it — an engineer or a salesperson with a template. And don't hire anyone if the volume is a few cases a month, if the process is broken and needs fixing first, or if a single Zapier or Make flow your team can maintain already does the job.

07.3AI chatbot development services

AI chatbot development services

Our AI chatbot development services build conversational assistants that do work, not ones that read from a script.

Read more

Each chatbot is grounded in your own data — docs, knowledge base, past tickets — so answers are specific to your business, and it takes real actions in your tools: it looks up an order, creates or updates a CRM record, opens a ticket, triggers a workflow and hands off to a person when it should. It runs where your customers or your team already are — website, WhatsApp, email or an internal tool. Every chatbot ships with guardrails: retrieval limited to approved sources, clear limits on what it can do, logging and an escape hatch to a human. This is not a rule-based FAQ bot with a decision tree: it understands the request, pulls the right context and finishes the task.

What technology is used in AI chatbots?

Four layers. A large language model (LLM) — OpenAI's GPT models, Anthropic's Claude or Google's Gemini — chosen per use case on quality, cost, latency, language and where the data may be processed. Retrieval-augmented generation (RAG): your documents are indexed so the model answers from approved sources and can cite them, instead of from memory. Tool calls: typed actions into your CRM, ERP or database, each with its own permissions and validation. And the reliability layer: an evaluation set of real questions run before every change, a log of every conversation, and rules for when to hand off to a person. The model is the easiest part to swap; retrieval, tools and evals are where the engineering goes.

Security, GDPR and the audit trail

Before anything connects, we agree what counts as personal data under GDPR in the workflow, where it may be processed and what must never leave your infrastructure — for EU and UK companies that usually decides between a self-hosted and a managed setup, and which model region to use. The automation runs with its own least-privilege credentials, never a person's login. Every run is logged: what came in, what the AI decided, what was written and who approved it. Write-backs land as drafts or behind an approval queue until the numbers justify more autonomy. That log is what your DPO and your auditors will ask for, and it is far cheaper to build in from day one than to bolt on later.

08 / How it compares

AI automation vs RPA vs workflow tools

Where AI automation fits against workflow tools (Zapier, Make), robotic process automation (UiPath, Power Automate) and doing it by hand — and where it doesn't.

  • AI automation

    What we build: n8n or code + LLMs

    Handles unstructured input (text, docs, email)
    Yes
    Reads and writes your live systems
    Via APIs
    Adapts when the process changes
    Re-prompt or retrain
    When a source system changes
    Raises an exception to a human
    Time to first workflow
    2–4 weeks
    Cost at 10× volume
    Model cost per run, capped
    Best for
    Judgment and unstructured work
  • Workflow tools

    Zapier, Make — rule-based flows

    Handles unstructured input (text, docs, email)
    No
    Reads and writes your live systems
    Via pre-built connectors
    Adapts when the process changes
    Edit the flow
    When a source system changes
    Fails the run; alert if configured
    Time to first workflow
    Hours to days
    Cost at 10× volume
    Per-task pricing
    Best for
    Simple SaaS-to-SaaS triggers
  • RPA

    UiPath, Power Automate

    Handles unstructured input (text, docs, email)
    No
    Reads and writes your live systems
    Brittle UI clicks
    Adapts when the process changes
    Rebuild the bot
    When a source system changes
    Silently breaks
    Time to first workflow
    Days to weeks
    Cost at 10× volume
    Per-bot licensing
    Best for
    Stable screens with no API
  • Manual / scripts

    Handles unstructured input (text, docs, email)
    No
    Reads and writes your live systems
    If coded
    Adapts when the process changes
    Rewrite the script
    When a source system changes
    Silently breaks
    Time to first workflow
    Varies
    Cost at 10× volume
    More people
    Best for
    One-off or tiny volume
09 /

Frequently asked questions

10 / More services
11/Start the conversation

Start your deployment.

Talk directly to a principal engineer.

No sales team.

No discovery workshops.

No procurement circus.

We scope, build and ship.

  • Reply within one business day
  • Engineer-led assessment
  • Written proposal
  • Lisbon · UK time zone

No commitment. Just an engineer.

Budget (estimated)
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