AI Automation

Win back the hours your team loses to routine.

Somewhere in your week there is a person copying data between systems, chasing the same follow-ups, or rebuilding the same report. AI automation is the discipline of finding those workflows, automating the ones that pay, and being honest about the ones that do not.

Talk to us All AI development

Workflow run trigger · 3 steps

Order email received

Extract order dataitems, quantities, delivery date

Validate against price listflags mismatches for review

Post to ERP & notifysales order created, team pinged

14 hrsof manual work saved this week

In one paragraph

AGI Software Solutions provides AI automation services for small businesses and mid-market teams: document processing, customer support triage, data entry, reporting and follow-up workflows, automated with AI and wired into the systems you already run. Most clients start with two or three high-volume manual processes and reclaim 10–20 hours of team time per week; typical builds run $10k–$80k, and you own the result — no per-seat subscription.

What We Build

Automate what pays. Skip what does not.

Not every workflow is worth automating. The ones that are share a shape: high-volume, rule-like, currently manual, and expensive when done wrong. We map your workflows against that shape first, so the build starts where the return is.

Mapping

ROI before build

We quantify hours and error cost per workflow before automating anything, so the first project is the one with the fastest payback.

Ownership

Built, not rented

You own the automation. No per-seat SaaS meter that turns a saving into a subscription.

Judgment

Handles the messy cases

Confidence thresholds route the clear cases straight through and the ambiguous ones to a person — the design that makes automation trustworthy.

Proof

Measured in hours

Every automation ships with a dashboard of items processed, exceptions raised and hours returned — so the ROI is a number, not a feeling.

Plain English

What is AI automation?

AI automation applies language models and machine learning to workflows that rules alone could never handle: reading documents that arrive in every format, understanding customer messages, extracting data from unstructured sources, drafting responses. Where classic automation needed everything to be structured first, AI automation works with your processes as they actually are — messy inputs included.

Compared

AI automation vs Zapier/n8n vs RPA

Three different tools, often confused. The honest comparison.

	Zapier / n8n / Make	RPA (bots)	Custom AI automation
Handles messy inputs	No — structured triggers only	No — breaks when the screen changes	Yes — documents, emails, free text
Judgment steps	No	No	Yes, with review thresholds
Cost shape	Monthly per-task fees, forever	Licences plus fragile maintenance	One build, you own it
Best for	Simple app-to-app triggers	Legacy apps with no API	Workflows involving reading and judgment

How We Build It

Five stages from problem to production.

The same process across every AI Development project, scaled to the size of the problem.

Discovery

We work out what the system actually has to do, what data exists, and what happens today when it goes wrong.

Design

Architecture, model choice, integration points and failure handling, defined before any of it gets built.

Integration

Connecting to the systems that hold your data, with security and permission boundaries handled properly.

Automation

The system takes on real work, in the workflows your team already uses rather than beside them.

Refine

Tuned against real usage and measured with evals, because how people use a system is never quite how it was designed.

Use Cases

Where ai automation services pays off.

The patterns we see deliver, across startups, SMEs and enterprise teams.

Documents

Invoice and form processing

Documents arriving by email in every format, read and posted into your systems, with exceptions queued for review.

Support

Inbox and ticket triage

Incoming messages classified, enriched with account context, drafted a reply, and routed — before your team opens them.

Sales

Follow-up that happens

Quotes chased, leads warmed and CRM records kept current automatically — the pipeline work that slips when the week gets busy.

Reporting

The Monday report, written

Recurring operational reports assembled and drafted from live data, arriving before anyone asks.

Related Work

Systems we have shipped.

AI DevelopmentAI Automation

Support Hub Inbox

One inbox across web chat, email, WhatsApp and Facebook, with AI replies trained on past resolutions.

60% faster replies, 99.95% uptime

AI DevelopmentAI AutomationLogistics

Warehouse Intelligence

Demand forecasting, OCR-driven receiving and anomaly detection across 14 fulfilment centres.

47% fewer stockouts, 14 warehouses

AI DevelopmentMarketplace

AI Marketplace Platform

Support chatbot, live SEO analyser and a vector recommendation engine, all sharing one retrieval layer.

+10% GMV, 40% fewer support tickets

See all case studies

What Teams Say

Hear from the teams we work with.

“We needed a voice agent that could actually qualify leads, not a chatbot pretending to be one. The team shipped a sub-700ms pipeline in 6 weeks. It now handles 5k calls a day.”

Priya RajHead of Growth, Ninjatech

“What sold us was their willingness to put AI engineers and product designers on the same call. We got working prototypes by week two and a production rollout in three months.”

James ThorntonCTO, Allindex

“AGI designed a CRM system tailored to our client management process. It is intuitive, reliable, and has centralized all our communication and history in one dashboard. This has greatly improved client retention.”

Carlos MendesProduct Manager, Qilinlab

Common Questions

Before you get in touch.

What should a small business automate first with AI?

The workflow that is high-volume, manual and painful when wrong — for most SMEs that is document processing (invoices, orders), inbox triage, or customer follow-up. Automating two or three such processes typically returns 10–20 hours of team time a week.

What do AI automation services cost?

A single well-scoped workflow: $10k–$25k. A programme covering several workflows with review queues and dashboards: $30k–$80k. Compare that against the loaded cost of the hours currently spent — the payback period is usually months, and you own the result.

Why not just use Zapier or n8n?

Use them — for structured app-to-app triggers, they are excellent and we build on them where they fit. They cannot read a messy PDF, judge an ambiguous email, or handle the exceptions. AI automation is for the workflows where the input is messy and the step needs judgment.

What happens when the AI gets something wrong?

It is designed for: confidence thresholds send uncertain cases to a review queue, every action is logged, and error rates are tracked per workflow. Automation you cannot audit is automation you cannot trust.

How long until it is running?

A first workflow is usually live in 4–8 weeks, including the shadow period where the automation runs alongside the manual process until the accuracy numbers earn it autonomy.

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