Document automation
Invoices, purchase orders, contracts, claims and forms read, extracted, validated and pushed into your ERP or accounting system with confidence scores on every field.
AI automation services
AI automation that runs your operations.
We design, build and run automations that take real work off your team - document handling, approvals, data movement, reporting and the long tail of manual steps nobody wants to own.
Most automation projects stall for the same reason: the tooling can move data between two systems, but it cannot read a messy invoice, judge an exception or decide what to do when reality does not match the happy path. AI automation closes that gap. We combine deterministic workflow engines with models that read, classify, extract and reason, so the automation keeps working when the input is imperfect.
Aixeron builds automations as production software, not as scripts. Every workflow ships with logging, retries, human-in-the-loop review, permissioning and a dashboard that shows exactly what ran, what it cost and what it saved. That is the difference between an automation demo and an automation you can run your business on.
The automations we build most often
Workflow automation
Multi-step business processes across approvals, onboarding, procurement and fulfilment, with branching logic, SLA timers and escalation to a human when the automation is unsure.
Intelligent RPA
Robotic process automation for legacy systems with no API, hardened with vision models so the bot survives UI changes instead of breaking on every release.
Data automation
Pipelines that clean, deduplicate, enrich and sync records between CRM, ERP, warehouse and reporting layers on a schedule or on an event.
Report and comms automation
Recurring reports, summaries, alerts and customer messages drafted by a model, reviewed against your rules and delivered to the channel your team already uses.
Compliance automation
Automated checks, audit trails and exception reporting so regulated processes stay evidenced without a person maintaining a spreadsheet.
How an automation gets from idea to production
- 01
Process mapping
We sit with the team doing the work, map every step, and measure volume, handling time and error rate. Automation candidates are ranked by hours saved per engineering week.
- 02
Pilot on real data
One process, real historical data, measured accuracy. No slide deck. You see the automation handle your worst inputs before anyone commits to a rollout.
- 03
Harden and integrate
Authentication, retries, idempotency, audit logging and review queues. The automation is wired into your identity provider and your existing systems.
- 04
Run and improve
We monitor accuracy and throughput after launch, retrain on the exceptions your reviewers correct, and expand to the next process once the first one is boring.
Where these automations pay for themselves
Manufacturing
Supplier document intake, quality report generation and production data reconciliation without manual re-keying.
Logistics
Proof-of-delivery capture, freight invoice audit and exception handling across carriers and portals.
Finance
Reconciliation, KYC document review and month-end close automations with a full audit trail.
Healthcare
Referral intake, prior authorisation packets and claims scrubbing routed to staff only on exceptions.
Retail
Catalogue enrichment, pricing updates and returns triage automated across marketplaces.
Energy and utilities
Field report processing, permit tracking and asset data sync between maintenance systems.
Built on a stack we run in production
Orchestration
- Temporal
- Airflow
- Celery
- Event-driven queues
Models
- LLM extraction
- Layout-aware OCR
- Classification
- Fine-tuned rerankers
Integration
- REST and GraphQL
- SAP and ERP connectors
- Webhooks
- Legacy UI drivers
Operations
- Audit logging
- Human review queues
- Accuracy dashboards
- Cost tracking
Trusted to ship AI across the world's operational industries
ManufacturingLogisticsEnergyHealthcareFinanceSmart CitiesAgricultureRetailAerospaceTelecomMiningPublic SectorManufacturingLogisticsEnergyHealthcareFinanceSmart CitiesAgricultureRetailAerospaceTelecomMiningPublic Sector
Questions we get asked about ai automation
What is AI automation?
AI automation combines traditional workflow automation with machine learning models that can read documents, classify requests, extract structured data and decide between paths. Classic automation follows fixed rules. AI automation handles the unstructured and ambiguous inputs that make up most real business work.
How is this different from a no-code automation tool?
No-code tools are excellent for connecting two SaaS apps with clean data. They struggle with unstructured documents, custom logic, high volume, on-premise systems and audit requirements. We build automations as owned software so you keep the source, the data and the ability to change it.
How long does an automation take to build?
A single well-scoped process pilot typically runs two to four weeks to a measured accuracy result, then a further two to six weeks to production hardening and rollout, depending on how many systems it has to touch.
How do you measure whether an automation worked?
Before we build, we baseline volume, handling time and error rate. After launch we report straight-through processing rate, exception rate, hours returned to the team and cost per transaction on a live dashboard.
Can automations run on our own infrastructure?
Yes. We deploy into your cloud account or on-premise, including fully air-gapped environments with self-hosted models where data cannot leave your network.
Related capabilities
Let's build
Have an idea? We'll ship it.
Tell us the problem. We'll come back with an architecture, a timeline and a team ready to build it in production.