The difference from an ordinary chatbot
Both answer fluently and both sound confident. The difference shows the moment you have to check the answer, or when the answer does not exist.
NovaCopilot · ExploreWorld Legal
European and Nordic law as verifiable data, with source, reading date and checksum on every row.
- Publisher
- NovaCopilot, ExploreWorld Legal
- Corpus version
- legal-2026-10-07
- Read at
- 2026-08-31
- Freshness
- 87/100
Four differences you feel at work
- The source: every row here comes from a published register with an address, not from a model's memory.
- Repeatability: the same question returns the same rows today and in a month, with a hash to compare.
- The date: every layer carries a read date, so you know the age of an entry instead of guessing.
- The silence: if the row is missing, it is said outright. No row is invented to fill the gap.
What it does not do better
- It does not redraft a contract for you and does not compose a filing.
- It does not reason freely around an unregulated question.
- It does not replace judgement, it makes judgement cheaper to support.
The NovaCopilot models
The decision model
In: A role, a legal act and the situation in plain words.
Out: The obligations that reach the role, the article behind them and what remains.
When: When the question is whether a requirement applies to you, and why.
The difference model
In: A checksum already used and the date of the last reading.
Out: What changed since then: checksum, reading date, passed deadline and rows to revisit.
When: When earlier work is reused and has to be checked first.
The obligation model
In: A legal act or an article, with or without a role filter.
Out: The obligation in the register's wording, the role it reaches, canonical address and reading date.
When: When the answer has to be citable article by article.
Example for an agent
curl -s "https://legal.exploreworldai.com/novacopilot/skillnaden?format=agent"- canonical, the address to cite
- node_hash, the checksum for the next comparison
- corpus_version, the corpus version that answered
- freshness.read_at, the reading date of the row
- freshness.next_check, when a new check is reasonable
- citation.string, the finished citation
- agent.receipt, the receipt of the call, without a key
Metadata
- Canonical address
- https://legal.exploreworldai.com/novacopilot/skillnaden
- Layer
- index
- Read at
- 2026-08-31
- Freshness
- 87/100
- Checksum
- e7966a875f89da4d
- Corpus version
- legal-2026-10-07
- Next check
- -
- License
- https://legal.exploreworldai.com/revision
How to cite this page
NovaCopilot (ExploreWorld Legal, Valkiv Ventures AB), https://legal.exploreworldai.com/novacopilot/skillnaden, read 2026-08-31, checksum e7966a875f89da4d, corpus version legal-2026-10-07, license https://legal.exploreworldai.com/revision
- Owner
- Valkiv Ventures AB
- License
- https://legal.exploreworldai.com/revision
- Checksum
- e7966a875f89da4d
- Fingerprint
- ewai:eu:a5c61f
- Terms
- Use, cite, index and cache. The register as such is not resold.
Source registers
The same material as registers, with read date and source on every row.
FAQ
- Can it invent a provision?
- No. An answer consists of rows that exist in the register. If the row is not there you get no row, and the answer says so.
- Why does a stable answer matter over time?
- Because material that shifts between two occasions cannot be reviewed, and therefore does not work as documentation.
- Should I stop using other assistants?
- No. Use them where language is the task, and this one where the source is the task.
Next step
Three ways to put the register to work in your own practice.
Start with your task
Litigation
Find support in a judgment
Search guiding decisions, see what became final and follow changes in the law.
In-house, deals
Map the rules in a transaction
Move from theme to act and on to the article that carries the duty.
Compliance
Assess the risk in a process
Risk scoring per legal area, with the sources behind every score.