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Managed data operationsEnd-to-end managed data operations.
We run the data operation behind your model, from the first scoping call to the final handoff. One accountable team covers calibration, staffing, workflow, model-assisted processing, quality control and reporting, so you get validated data without building a labelling operation of your own.
What’s included.
Every part of the operation has an owner. You agree the requirements and acceptance criteria with us; we manage the rest and show you the record.
Scoping
The use case, inputs, output format, acceptance criteria, priorities and practical constraints, written down before work starts.
Calibration
A pilot on representative data tests the guidelines, exposes edge cases and fixes how each one is handled.
Staffing
A trained team of Point AI employees is assigned to the project and stays on it, so knowledge of your data builds up.
Model-assisted processing
Where a suitable model exists, it pre-labels and people correct. Where it does not, the team labels from scratch.
Quality control
Structured review against the agreed acceptance criteria. Unclear cases are raised, decided and added to the guidelines.
Reporting
Batch status, error types, agreement and raised questions, visible to you in Point AI Studio’s quality dashboards.
Handoff
Delivery in agreed batches, exported in standard formats, through the API or by cloud delivery.
From first sample to dependable production.
A focused calibration phase establishes the right interpretation before the team and the dataset scale.
- First
Align on data and success criteria
We clarify the use case, inputs, output format, acceptance criteria, priorities and practical constraints.
- Then
Calibrate on representative data
A focused pilot tests the guidelines, exposes edge cases and establishes a repeatable review approach.
- Ongoing
Move into managed production
The trained team delivers in agreed batches, with quality review, feedback and requirement updates built into the workflow.
A trained team that stays on your project.
Our 30+ neurodiverse professionals are employed and trained in-house, never crowdsourced, with offices in Tel Aviv and Haifa. Annotators who remain on a project build familiarity with your data, your guidelines and your edge cases over months, instead of restarting the learning curve with every batch.
- Long-term trained teams. Professional training for your task, and the same people on your data from batch to batch.
- Project management. Onboarding, delivery, QA and feedback coordinated by us as requirements evolve, without adding management overhead on your side.
- Structured QA. Calibration, documented decisions and structured review keep interpretation consistent as the dataset grows.
- Communication. Questions and edge cases are raised early, so decisions can be documented and applied across the dataset.
- Within your workflow. Deliveries follow your formats, guidelines and rhythm through Point AI Studio.
| batch_03 | same 6 annotators |
| batch_09 | same 6 annotators |
| batch_14 | same 6 annotators |
| guidelines | v1.0 → v1.6, documented |
How we handle your data.
For defense, aerospace and medical programs, this is usually the first question. These are the practices behind every project.
In-house, employed team. The people who see your data are Point AI employees, trained in-house. No crowd.
Have a challenging data problem?
Tell us what you’re building and what data you have. We’ll suggest a practical way to process, check and deliver it.