Intelligent Automation

Intelligent Automation for real business operations

We replace manual, repetitive work with AI agents and pipelines that handle exceptions, integrate with your existing systems, and keep humans involved where judgement matters.

Trusted by 40+ businesses

Automation that handles real work

Old school RPA breaks the moment your process changes. Modern intelligent automation combines LLMs, agents, and process mining to handle the messy, semi structured work humans actually do. Invoices that don't match the template. Emails that need judgement. Customers who don't pick from the menu. We map your processes, find the highest impact wins, and ship automations your operations team can trust.

How we automate

Discovery first, automation second.

01

Map

Process discovery and mining to find the steps where automation actually makes a difference.

02

Design

Pick the right tool for each step. LLM agent, classifier, RPA, or workflow. Avoid over engineering.

03

Build

Ship the automation with humans involved, exception handling, and clear success metrics.

04

Scale

Roll out across teams, monitor accuracy, and continuously improve as edge cases surface.

Why teams pick Codino for automation

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AI first, not rule first

We use LLMs and agents where they're cheaper and more flexible than rigid rule bots.

Measurable ROI

Every automation ships with a measurement plan. Hours saved, errors reduced, throughput gained.

Tool agnostic

We pick the right platform for your stack instead of locking you into one vendor.

Operational handoff

We don't disappear after launch. Your ops team gets the playbooks and dashboards to run it.

Intelligent automation, explained

Traditional RPA follows fixed rules and breaks on edge cases. Intelligent automation uses LLMs and ML to handle the unstructured, exception heavy work humans do, and integrates rule bots only where rules are genuinely simpler.
With a process mining engagement or a focused workshop on one painful workflow. We pick something measurable, ship it in weeks, and use the learnings to scale across more processes.
High volume, repetitive, and exception heavy processes. Document handling, customer triage, data reconciliation, internal request routing. Anything where humans are pattern matching all day.
Yes, and we recommend it. We design escalation paths, confidence thresholds, and review queues so humans handle judgement calls while AI handles volume.

Let's Talk About Your Project

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Maciej Roman|CEO & Co-founder