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Applied artificial intelligence

Assistants, intelligent search, request triage and document analysis that answer with your organization’s information, not with generic content.

  • On your own data
  • We define which information leaves your infrastructure
Analyzing information with the support of artificial intelligence

When information exists but is hard to find or process

The problem is rarely a lack of information. It is usually spread across folders, emails, documents and undocumented knowledge, and finding it takes longer than using it.

Before proposing a model we review what data exists, what condition it is in and which specific decision needs to improve. Without that step, artificial intelligence produces answers that are convincing and wrong.

These situations usually point to the opportunity

Internal assistants

When the answer exists but nobody can find it

An assistant that answers from your manuals, policies and procedures, and cites the source of every answer.

  • Search across documents
  • Answers with a source
  • Access control

Automatic triage

When the volume of requests exceeds the capacity to review them

Emails, tickets and forms sorted by type, urgency and owner from the moment they arrive.

  • Classification by type
  • Automatic prioritization
  • Assignment to an owner

Document analysis

When long documents must be read to extract a few data points

Extraction and summarization of contracts, invoices, case files or reports, with the data already structured for use.

  • Data extraction
  • Summaries
  • Structured output

Signs that this service applies

  • The same questions come up again and again because the answer is hard to locate.
  • Someone sorts emails or requests by hand before the actual work can start.
  • Long documents get read end to end just to pull out a handful of fields.
  • There is enough data to decide with, but nobody has the time to analyze it.
See how we work
A team reviewing its operation with Cronode

About this service

No, unless your organization authorizes it. From the outset we define which information leaves your infrastructure and which stays inside it, and when the case calls for it we work with models that run in your own environment.

Verification is part of the design: answers cite their source and sensitive processes keep a human approval step. The system proposes; the decision with consequences stays human.

That is the usual situation, and tidying it up is part of the work. What does not work is putting an assistant on top of unreviewed data and expecting reliable answers.

Before artificial intelligence, let’s look at your data

Half an hour to assess the state of your information and which specific decision could improve.