AI & Automation

Automation You Can Audit

AI that takes real work off your team without taking the decision away from them — measured before it ships, gated by a human where it matters, and reversible when it is wrong.

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Overview

Automation that starts with the process, not the model

The failure mode of AI projects is not bad models. It is automating a process nobody measured, with no way to tell afterwards whether it helped. We baseline first, automate the step where the cost actually sits, and instrument it so the answer is visible.

How we keep it accountable

Baseline before build. Hours, error rate and cost per run measured on the current process, so any claim afterwards has something to be measured against.
People on the gate, not in the loop. Humans approve the consequential actions and skip the routine ones. An approval queue your operators can actually work from.
Evaluated like software. A versioned eval suite in CI. Prompt and model changes are diffed against it, so a regression is caught before your customers find it.
Reversible by design. Every automated action has an undo and an audit record. Rollout is staged, and turning it off is a documented step, not a crisis.

Audit trailEvery run, every decision, logged

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What we build

From the process map to the running agent

Ten engagements covering discovery, build, evaluation and the operational surface your team uses every day.

Colleagues stacking hands over paperwork at a table

Why teams pick us

Why choose SysStacks?

We automate the expensive step

Discovery starts with where the hours and the errors actually are. Often the answer is a rule, not a model — and we will say so.

A human owns the consequence

Approval gates on anything that spends money, contacts a customer or changes a record. Autonomy is earned per workflow, not granted by default.

Evaluated before it ships

A versioned eval suite runs in CI. Prompt, model and tool changes are scored against it, so drift shows up as a failing build.

Costed per run

Tokens, latency and spend per workflow on a dashboard from the first week, so the business case stays honest as volume grows.

Reversible and recorded

Staged rollout, an undo path for every action, and an audit log detailed enough to reconstruct any decision months later.

How we deliver

How an automation programme runs

Six stages, one continuous loop — automation is supervised software, not a delivery.

Process discovery

We watch the work happen, map the steps, and measure the current cost in hours and errors. That baseline is the only thing later claims can rest on.

Feasibility & design

Which steps are deterministic, which need a model, and which should stay human. You get the reasoning and the estimated run cost before we build.

Build & instrument

Tools, prompts and policies in version control, reviewed like code, with logging and cost tracking wired in from the first run.

Evaluate & tune

Scored against a held-out set and a written policy for refusals and escalation. We tune until the failure modes are ones you can live with.

Supervised rollout

Shadow mode first, then a narrow slice of live volume with every action gated, widening only as the evidence supports it.

Operate & review

Drift monitoring, cost review and a regular look at what the approval queue is catching — which is where the next improvement always comes from.

Industries we focus on

Where automation pays off first

Finance & back office

Reconciliation, invoice and statement processing, and KYC document review — high-volume, rule-heavy work with an audit obligation attached.

Healthcare administration

Referral triage, coding support and correspondence handling, designed so a clinician holds the decision and the system holds the paperwork.

Logistics & operations

Exception triage, delay classification and customer notification — the queue that grows every time something goes wrong upstream.

Retail & customer service

Order enquiries, returns and product questions, with escalation to a person built in rather than bolted on after complaints.

Manufacturing & quality

Non-conformance write-ups, supplier documentation and inspection records, structured so the data is usable afterwards.

Find Your First Workflow

Our tech stack

The AI stack we operate

Models, orchestration and the observability that makes an automated workflow supportable at 3am.

Python

PyTorch

TensorFlow

Jupyter

pandas

NumPy

FastAPI

Django

TypeScript

Node.js

OpenCV

PostgreSQL

Redis

Elasticsearch

Kafka

Docker

Kubernetes

AWS

Google Cloud

Azure

Terraform

Grafana

Prometheus

Featured insights

Stories of our transformations across services and industries

From concept to completion.

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Get in touch

Describe the process you want back. An engineer — not a sales rep — replies within one business day.