AI deployed against real business processes.
We deploy AI against processes that already exist and already cost money — classification, retrieval, matching, translation. Each system has boundaries, an evaluation set and a fallback, and we operate it after it ships.
What we do
AI as a system component.
AI agents
Agents with defined tools, boundaries and fallbacks, deployed against real processes — quoting, triage, classification, support — not a chat box on a landing page.
Retrieval and grounding
Answers drawn from your own documents and data, with citations, so a response can be checked rather than trusted.
Matching engines
Systems that score and rank entities against each other — buyers to suppliers, candidates to roles, products to intent.
Multilingual NLP
Classification, extraction and generation across languages and scripts, including right-to-left, evaluated per language rather than assumed to transfer.
Structured extraction
Turning documents, invoices, specifications and filings into structured data a system can act on, with confidence scores and a path for the cases it cannot resolve.
Evaluation harnesses
Test sets, baselines and regression checks, so a model change can be measured rather than argued about.
Who it's for
Where this gets deployed.
High-volume decisions that follow rules people cannot apply consistently at scale.
Document-heavy processes where the answer exists but finding it takes hours.
Work spanning languages, regulations and formats that do not map cleanly onto each other.
Approach
Data. Boundaries. Evaluation.
01
Grounded in your data
Retrieval over your own documents and records, so answers cite a source rather than a probability.
02
Bounded by design
Defined tools, permitted actions and explicit failure paths. The system is allowed to say it does not know.
03
Evaluated continuously
Held-out sets, human baselines and monitoring in production, not a demo that worked once.
Advantages
How we know it works.
Measured against a baseline
Every deployment has an evaluation set and a human baseline. If the system does not beat it, it does not ship.
Runs in production
Monitored, logged and on call — not a pilot
Traceable decisions
Every output can be traced to its inputs
Have a process worth automating?
Tell us your growth target. We'll put together the engine — channels, content, and the AI layer that runs it.
We research this as well as ship it. Ara, our applied AI research project