AI Agent Design for Zero-Error Domains
AI that is right.
Not just plausible.
We build AI workflows for banks, insurers, wealth managers, law and tax firms, and other organizations where one wrong number or false citation costs money or creates liability. Normal AI tools sound convincing but make errors nobody notices. Ours check their own work before you see it.
Documents you can rely on
We turn PDFs, scans and spreadsheets into clean, searchable text and tables, so your team and your AI tools work from the same correct data.
Why it works: every page is checked a second time by AI and scored. Unreadable values are marked as unclear instead of guessed. Same AI model, accuracy up from 88.8% to 97.1%.
Your document archive, organized and answerable
Thousands of contracts, policies and regulations sorted by topic, with duplicates and outdated versions identified. Ask what applies, and see what changed between versions.
Why it works: every statement links back to the exact source document and paragraph. Example: the 2026 amendment to MaRisk (German bank risk rules) compared paragraph by paragraph, with every AI-relevant change flagged.
Research reports on a schedule
Regular market, technology and regulation reports, briefings and eBooks, produced automatically and with sources, instead of being written from scratch each time.
Why it works: one tested process is reused every time, and claims are checked against sources before publication. Six quarterly reports so far; the latest cites 247 sources.
AI that follows your rules
You define what the AI may and may not do. Every action is checked against those rules before it happens, and logged.
Why it works: the check is ordinary software, not AI, so it behaves the same way every time. Compliance and audit teams get a complete record of what the AI did and why.
Runs where your data is allowed to be
The same workflows run with cloud AI providers, in a mixed setup, or fully on your own servers without internet access, if your data must not leave the building.
Why it works: quality comes from written, step-by-step procedures with built-in checks, not from one particular AI model. That is why smaller models you can host yourself still give reliable results.