Valuable data exists beyond the obvious sources.

Argo Reach connects AI developers with difficult-to-source proprietary data, from established businesses to specialized industries.

What is AI data licensing?

AI developers use specialized datasets to train, test and improve their systems. Argo Reach helps identify potentially suitable collections and coordinates conversations about licensing specific data for agreed uses.

You can start by telling us what you have. No files are needed for an initial conversation.

How the process works
  1. Existing records
  2. Defined licensing agreement
  3. AI development

Valuable data isn’t always public.

Real-world records AI developers cannot easily find elsewhere, from established businesses to specialized sources.

Interaction & service operations

Consent-appropriate speech, conversations, transcripts, workflows, and outcomes across languages, dialects, and mixed-language settings.

  • Call recordings
  • Transcripts
  • Customer interactions
  • Multilingual conversations
  • Resolutions

Customer and client rights must be independently established.

Sourcing interests, not available inventory.

2 / Licensing potential

$100K to $1M+

Illustrative potential licensing value for operating & specialized datasets.

The value is in the context.

Illustrative potential licensing values only. Actual value depends on dataset quality, scale, rights, permitted uses, and buyer demand. No transaction or compensation is guaranteed.

  • Scale

    Enough volume to matter

  • History

    Years, not months

  • Context

    Decisions and outcomes, connected

  • Rights

    Clear authority to license

  • Demand

    A defined buyer need

Context is the value.

Rows alone say little. Connected records show what was decided and how it turned out.

8 years
Operational history
2.4M
Shipment records
180K
Documented exceptions
  1. Context

    Shipment

    The movement and its planned arrival.

  2. Context

    Delay

    An exception linked to the shipment.

  3. Action

    Investigation

    Evidence gathered to explain the delay.

  4. Decision

    Decision

    The response chosen from that evidence.

  5. Outcome

    Resolution

    What happened after the response.

Fictional example

Identity removed. Context kept.

Before an approved use, identifying details may be removed or transformed. The useful workflow can remain.

Original record

Customer
Jane Smith
Order
#184829
Issue
Package not received
Action
Replacement approved
Outcome
Delivered successfully

Prepared copy

Customer
Customer 1
Order
#12345
Issue
Package not received
Action
Replacement approved
Outcome
Delivered successfully

Fictional record. De-identification can reduce exposure of identifying information while preserving useful context. Appropriate privacy, ownership, consent, contractual, and permitted-use requirements still apply.

Start with a description, not the data.

From system overview to commercial exploration: evaluate your data’s potential in three simple steps.

  1. 1 Describe

    Tell us what systems and records exist.

  2. 2 Assess

    We evaluate relevance, scale, rights, and buyer fit.

  3. 3 Explore licensing

    If there is a match, we coordinate access, permitted use, and terms.

Wider reach.
Careful qualification.

  • Proprietary data.

    Information that cannot simply be obtained publicly.

  • Difficult-to-reach sources.

    Relationships across specialized industries.

  • International reach.

    Beyond conventional U.S. sourcing channels.

  • Careful qualification.

    Not every dataset is useful or licensable.

  • Commercial coordination.

    Qualified owners, connected with potential buyers.

Have proprietary data worth exploring?

A conversation starts with what you know