01
Discover the requirement
We define the buyer use case, required examples, target distribution, quality expectations, licensing conditions, delivery format, and acceptance criteria.
Our process
A disciplined path from request to dataset.
Calvek AI is designed around buyer-defined specifications, practical sourcing, verified permissions, quality criteria, and accepted deliveries—not speculative data accumulation.
01 / How we work
Five steps. One clear objective.
Source data that can actually be used for the intended model task.
02
Map the sourcing path
We identify potential rights holders, domain experts, data-generating workflows, and collection partners; then evaluate feasibility, volume, costs, and sample access.
03
Validate authority and permitted use
We assess ownership and licensing questions, confidential and personal data, third-party constraints, and appropriate contract and handling requirements before acquisition.
04
Collect, transform and check
Once the approach is agreed, the relevant parties collect or supply materials, prepare the data, and run sample reviews and agreed quality checks.
05
Deliver, evaluate and refine
The buyer receives the contracted outputs and supporting information, reviews them against acceptance criteria, and can request remediation or a defined follow-on batch.
02 / Risk-managed delivery
Pilot first. Scale when the evidence supports it.
A smaller scoped dataset can reveal licensing complexity, mismatch between source material and buyer needs, processing cost, and rejection rates before either side invests in a large program.
- Use a concrete acceptance sample
- Confirm source rights and actual commercial terms
- Measure usability, completeness, and exception rates
- Determine whether replenishment is viable
Illustrative pilot outputs
01
Written data spec
Clear unit definition, schema, sample expectations, quality bar, and intended use.
02
Supplier and rights review
A documented assessment of candidate sources and conditions for data use.
03
Sample dataset & QA notes
Representative examples, any transformations, and identified limitations.
04
Next-stage recommendation
A proposed continuation or stop decision based on quality and commercial fit.
Start a conversation
Discuss a data needStart with a well-defined problem.
Whether you have a formal RFP or just a stubborn data gap, we can begin with the questions that matter.