Four pillars
Decide
Live observation in the working environment, then a ranked opportunity portfolio with an impact against effort logic for every candidate, so investment follows evidence instead of enthusiasm.
Trust
AI policy, risk classification, human oversight and the EU AI Act documentation your regulators, auditors and largest clients will ask to see, designed in rather than bolted on.
Build
Co-creation from a chosen use case to a working, integrated solution in production, built with your team inside your systems, including the ones with no API.
Run
AI leadership, capability building and adoption support after go-live, with an exit path that leaves the capability with you.
Selected engagements
AI strategy and prioritisation
We have built AI strategies for institutions with little in common: one of the largest hospitals in Lithuania, a faculty of the country’s leading university, and an AI centre of excellence founded by six universities. Each ended in the same place, with leadership holding the evidence to choose their own direction on AI and a prioritised roadmap they could fund, defend and carry forward.
AI operations and oversight
Oversight fails quietly: a risk register is honest for about a week, and a multi-partner programme kept across separate files cannot say what is late. We build instruments that keep themselves current, from a risk register that re-scores its own ranking and generates the board summary, to a €30 million programme held in one command centre where deliverables, risks and cash flow recalculate as the work moves. The same discipline applies to the AI itself: risk classification, human oversight, decision logs and EU AI Act documentation.
Assistants and agents in production
Most AI pilots never reach a second month. We have delivered more than fifty assistants and agents across sales, finance, marketing and operations, each one starting from the problem rather than the platform, and each one built together with the person who owns the work, who set what good looks like and tested it in their own day. They are in daily use across construction, retail, logistics, manufacturing, financial services and education.
Speech and language AI
Speech AI does not exist unless someone builds the data underneath it. We led the development of the 5,000 hour LIEPA-3 corpus, the largest body of Lithuanian speech data, and created a separate 400 hour medical corpus, the first in Lithuania to cover family medicine and radiology, with a working speech recognition prototype trained on it. Both are released as open resources, and the corpus design, annotation, data pipelines and model training they demanded is the engineering layer beneath everything else we deliver.
A Gooliver brand
When the gap is a whole role, not a use case
Sometimes the question is not which process to improve, but which job nobody can fill. Handled takes over the role end to end and carries the numbers for it: one AI worker owning a queue from intake to outcome inside your systems, with a written job description, decision limits, a named human owner and a KPI contract. Twenty roles are ready across service, finance, HR, sales and legal, in Lithuanian, English and twenty more languages. Same team, same governance standard, deliberately separate brand.