AI & Data Strategy
Rank use cases, define measurable outcomes, and turn the strongest option into a delivery plan.
From Operational Data to Reliable
We engineer dependable AI systems that turn operational data into decisions your teams can trust.
Assess Your AI ReadinessWhat production AI requires
Data that fits the job
We check whether your data is relevant, accessible, and reliable enough for the use case. If a gap blocks the work, you know before committing to a build.
More than a working model
A model has to connect to your existing systems, handle failures, and keep working as data and conditions change.
Controls your team can understand
Your team needs to see what the system did, trace its inputs, and know when a person should step in.
How Aliac builds it
Start with the decision
We define the decision or workflow to improve, the people involved, and the result that will count as success.
Build the whole system
We develop the model or agent together with the APIs, data pipelines, deployment, monitoring, and rollback needed to run it.
Work with your domain experts
Your experts test our assumptions and review the system behavior. We bring the AI, MLOps, and systems engineering.
How an engagement starts
1
Define the outcome
Agree on the decision, workflow, constraints, and measures of success.
2
Inspect the data and systems
Review data access and quality, existing infrastructure, and integration points.
3
Test feasibility and value
Check whether the use case is technically viable and worth the cost and operational change.
4
Make the go/no-go decision
Deliver the evidence, risks, and production plan you need to proceed, pause, or stop.
What we build
We help you choose the right use case, build the model or agent, and run it reliably in production.
Autonomous AI Agents
Build agents that work across your APIs, documents, and workflows, with permissions, monitoring, and human approval where needed.
Production Data Pipelines
Build data pipelines that validate, transform, and trace the inputs used by AI systems.
MLOps & System Architecture
Set up deployment, monitoring, rollback, and model lifecycle controls for cloud or on-premises systems.
Products
Live AI systems we build and run. Open one and try it.
Latest Insight
Exploring technical concepts and industry insights in AI and MLOps.
From Sprints to Specs: How AI Is Rewiring the Rules of Software Delivery
Two-week sprints and eight-person squads were built for human-paced code. Here is how engineering leaders are redesigning teams, roles, and delivery models for the agent era.
Read Full Article →About Aliac
AI engineering for work that has to hold up outside a demo.
Aliac builds custom AI, machine learning, data, and MLOps systems for industrial and enterprise teams.
We work with the people who understand the operation. Together, we define what the system should do, test whether the data supports it, and build it for day-to-day use. Knowledge transfer is part of every engagement.
Have an AI use case in mind?
Book a short call to discuss the decision or workflow you want to improve, the data and systems involved, and whether there is a sensible next step.
Discuss Your Use Case
Aliac
Based in Greece