For companies
Your data could be worth more than you think.
Qualifying data partnerships may range between €90,000 and €1.75 million+, with compensation for qualifying data starting from approximately €30,000 per terabyte. The first step is a confidential assessment — no data upload required.
No obligationNo immediate data transferConfidential initial review
The asset you already own
Most valuable AI data was never created for AI.
It was created by people doing their jobs well — and it is often sitting unused inside systems your company already runs.
Operational records
Decisions, cases, tickets, claims, transactions and workflow histories created over years of real activity.
Expert judgement
Annotations, reviews, corrections and outcomes that capture how skilled people actually reason.
Domain-specific language
Reports, notes, correspondence and documentation written in the vocabulary of your industry.
Measured outcomes
Results linked to inputs — the ground truth that general-purpose data rarely contains.
What we look for
Examples of data we assess.
If your organisation holds any of the following, it is worth a confidential look.
Records of real work
- Historical operational data and records of real work
- Decisions linked to subsequent outcomes
- Transactions, exceptions, resolutions and quality-control results
- Domain-specific documents, images, audio, video or sensor information
- Customer-support interactions and escalation patterns
- Specialist evaluations, reviews, corrections and professional judgements
- Software interactions, testing, debugging and product-support activity
- Repeatable workflows that reveal how complex work is completed
Knowledge and process assets
- Internal documentation
- SOPs and playbooks
- Knowledge bases
- Process documentation
- Project management workflows
- Internal communications
- Business process artifacts
- Templates and operational frameworks
- CRM and workflow metadata
- Task execution histories
Who fits best
Organisations with mature, repeatable operations.
- 20 to 200 employees (more is also fine)
- Strong operational maturity
- Significant internal documentation and process knowledge
- Active use of modern software tools
- Well defined workflows that employees execute repeatedly
Examples include
Three examples
What this looks like in practice.
Three common starting points. Pick the one closest to your organisation.
The conversations your teams already have
A customer asks a difficult question. An employee investigates the issue, asks a colleague for help and sends the customer the correct solution.
You may have
- Slack conversations
- Microsoft Teams messages
- Emails
- Customer-support tickets
- Internal questions and answers
What we remove
We remove personal and sensitive information before preparing the remaining conversation for approved AI use. This can include removing or replacing:
- Names
- Email addresses
- Telephone numbers
- Customer numbers
- Account details
- Personal information
- Confidential information outside the agreed scope
What AI can learn
- Understand real questions
- Find the right information
- Resolve difficult cases
- Escalate problems
- Write useful answers
Your conversations show AI how real problems get solved.
Assess our conversationsSimple explanation
We do not simply hand over your raw company data.
lalalab turns agreed parts of your company data into structured examples that AI can learn from — identifying the useful information, removing personal and sensitive details, and clearly showing what actually happened. Only data within the agreed scope is prepared.
- 1What happened
- 2What information was available
- 3What decision was made
- 4Which action followed
- 5What the final result was
How it works
From company data to an approved AI partnership.
Seven steps, each confirmed with you before the next begins.
Tell us what you have
You tell us where relevant information may exist. You do not need to upload data during the first assessment.
- Slack
- Microsoft Teams
- GitHub or GitLab
- Customer-support systems
- Internal applications
- Reports and documents
We assess the opportunity
We look at the type of information, volume, quality, uniqueness and potential AI use. The first assessment helps determine whether further work is worthwhile.
We agree the boundaries
Together we define the rules of the partnership.
- Which sources may be included
- Which information must be excluded
- Which personal information must be removed
- Which use cases are allowed
- Which AI companies may receive access
- Which commercial terms apply
We remove sensitive information
Depending on the data and agreed use, information may be:
- Removed
- Replaced
- Pseudonymised
- Aggregated
- Redacted
- Excluded entirely
We prepare the data
We structure the remaining information so it becomes useful for AI training, evaluation or testing.
You approve the partnership
The proposed dataset, buyer, permitted use, protections and compensation are agreed before licensing.
Your company gets paid
When an approved dataset is licensed, your company receives the compensation stated in the partnership agreement.
Every step is confirmed with you before the next one begins. Nothing moves without your approval.
Data protection
Your data. Your boundaries. Your decision.
Exploring a data partnership does not mean giving lalalab unrestricted access to your company.
You choose the sources
Your company decides which systems, repositories, conversations or documents may be assessed.
We minimise the data
We only prepare the information needed for the agreed purpose.
We remove personal information
Personal and sensitive information is identified and removed, replaced or protected according to the agreed process.
You approve the use
No data should be licensed outside the agreed scope.
Use is documented
The buyer, purpose, restrictions, retention period and commercial terms are defined contractually.
Your underlying rights remain protected
Your company retains its existing rights to its data, software and intellectual property unless explicitly agreed otherwise.
Commercial value
What a partnership can look like.
Value depends on quality, uniqueness, usable volume, rights and demand. Nothing is guaranteed — but qualifying data can be commercially significant.
From €30K+
Indicative starting reference per qualifying terabyte.
€90K–€1.75M+
Indicative total range for a qualified data partnership.
Agreed permissions
Permitted use, recipients, retention and restrictions are documented before release.
Retained ownership
Your company keeps its existing rights unless explicitly agreed otherwise.
Figures are indicative and not an offer or guarantee. Actual outcomes depend on qualification, data quality, rights, usable volume and buyer demand.
Questions
The questions decision-makers ask first.
Straight answers on value, control, rights and process — without overstating what we can promise.
Find out whether your company is sitting on a valuable AI data asset.
Start with a confidential assessment. Tell us what kind of information your organisation holds — without uploading the data itself.
No obligationNo immediate data transferConfidential initial review