Spreadsheets and workbooks
Historical financial, operational, engineering or planning models with formulas and revisions.
For companies with valuable operating history
Your data may be one of your most valuable assets.
The spreadsheets, systems, corrections and decisions created while running your company may contain exactly the real-world knowledge frontier AI cannot learn from public data.
Why now
Public text can teach a model what professionals say. Operating data teaches it what professionals actually do.
Sofitra helps companies license or sell that knowledge without simply handing over a raw archive. We define the rights, transform the data, reconstruct the workflow and package only the agreed derivative environment.
What has value
The trail behind the output is often more valuable than the output.
The strongest assets show how expert work changed over time: what was tried, corrected, rejected, approved and ultimately delivered.
Application histories
CRM, ticketing, project, underwriting, QA, ERP or workflow-system records.
Corrections and approvals
Reviewer changes, exceptions, overrides, escalation histories and final decisions.
SOPs and manuals
Written procedures linked to the actual cases in which those rules were applied.
Decision records
Messages, comments, meeting outputs and contextual explanations around material choices.
Usage and action traces
Timestamped activity showing how experts navigate software and recover from mistakes.
Commercial structures
A partnership shaped around the asset and the owner.
Data ownership, business continuity and future supply determine the right structure. Terms are agreed per asset.
Data licence
Retain ownership while granting defined rights for approved training or evaluation uses.
- Fixed term or continuing
- Exclusive or non-exclusive scope
- Upfront and/or milestone economics
- Buyer and domain restrictions
Revenue share
Build a continuing data supply relationship and participate in downstream environment revenue.
- Ongoing refreshes
- Shared asset development
- Partner review checkpoints
- Performance-linked economics
Asset acquisition
Sell a dataset, software archive, workflow library or selected data-rich business asset.
- Upfront acquisition
- Transition support
- Carve-outs and exclusions
- Optional continuing supply
Valuation lens
What determines the value of company data?
Size matters, but scarcity, workflow depth, ownership clarity and verifiability matter more.
Can it be found elsewhere?
Private, domain-specific histories with little public substitute are more valuable than generic text or commodity labels.
Does it show the workflow?
Linked source, action, correction and outcome data is more useful than disconnected final artifacts.
Can it be used cleanly?
Clear ownership, consent, customer restrictions and permitted-use boundaries reduce delivery risk.
Can success be verified?
Structured outputs, rules, outcomes and expert approvals make robust training rewards possible.
Partner control
You define what enters and what never leaves.
The partnership agreement establishes source scope, exclusions, permitted transformation, buyer access and deletion or return obligations before processing begins.
Named data boundaries
Approved systems, date ranges, file classes and modalities are explicitly identified.
Partner-defined exclusions
Customers, matters, geographies, fields or workflows can be excluded before transformation.
Pre-delivery review
Partners can review the transformed asset or environment under the agreed process.
No public disclosure by default
Company identity, logos and relationship details are not published unless separately authorised.
Partnership process
A controlled process from first look to final delivery.
A lightweight first review determines whether the asset merits deeper diligence, without requiring an immediate raw-data transfer.
Describe
Share systems, date ranges, modalities, scale and known restrictions.
Sample
Review a tightly controlled structural sample or schema-level inventory.
Assess
Evaluate scarcity, workflow depth, rights, transformation and buyer demand.
Structure
Agree licence, revenue share, acquisition or continuing partnership terms.
Ingest
Transfer authorised data into segregated processing under agreed controls.
Transform
Build the approved privacy-safe data universe and derived environment.
Monetise
Deliver within the permitted scope and report economics as agreed.
Data valuation
Find out what your operating history is worth.
A short inventory is enough for an initial assessment. Raw data is not required at the first stage.