01/Too much raw data
More capture than you can label
Fleets and sensors generate far more than any budget can label. We find the slice worth the spend so the rest does not slow you down.
We mine and select your data.
Most captured data is redundant. Our team dedupes the repeats, mines the long-tail edge cases, and selects the smaller set worth labeling, so you spend on the data that improves the model and skip the rest. The same Curate pipeline that powers the product, run for you.
When to put our team on curation.
The service fits teams drowning in raw data who need the high-value slice surfaced before they spend on labeling. We curate; the Curate product puts the same pipeline in your hands.
02/Long tail to find
Rare cases hiding in the pile
The scenarios that break models are rare and hard to surface by hand. We mine the whole dataset to bring them to the front.
03/Label less, learn more
Spend where it counts
Teams that want to cut labeling cost without cutting what the model needs to learn, instead of paying to label the same scene twice.
What we deliver.
A focused, labeling-ready dataset, built on the same proprietary pipeline that runs the Curate product, delivered with the reasoning behind every selection.
Deepen·Curate
Full dataset
Everything you captured, mostly redundant
Dedupe→Mine→Select
Curated set
The smaller set worth labeling
Rare long-tail scenarios kept
A full dataset reduced to the set worth labeling, with the rare cases kept
01/Dedupe
Deduplication
We cut near-duplicate and redundant frames, so you never pay to label the same scene twice.
02/Selection
Scenario and edge-case selection
We select for coverage across conditions and pull the edge cases that teach the model what it does not yet know.
03/Mining
Long-tail mining
We search the whole dataset for the rare, hard scenarios that improve model performance, not just the easy majority.
04/Dataset
A labeling-ready dataset with rationale
The curated set comes back ready to label, with the reasoning behind every choice, so you can see why each frame was kept.
How we engage.
A dedicated team, a shared plan, and reporting you can act on. The same engagement model backs every Deepen service, framed here for curation programs.
01 · Scope
Plan the program
We define your dataset, target scenarios, labeling budget, and the formats your pipeline already speaks.
02 · Dedicated PM
One point of contact
A dedicated program manager owns selection quality, communication, and delivery.
03 · Pilot
Prove it on a sample
A focused pilot curates a slice and shows the cost and coverage gain before you commit the full dataset.
04 · Scale
Across the dataset
We roll the same method across everything you capture, with reporting on what was kept, cut, and why.
Label less, learn more.
Teams curating with Deepen label a fraction of what they capture and still ship models that hold up on the long tail. We curate to the certifications safety-critical programs depend on.
Compliance built inISO 27001SOC 2TISAXGDPRHIPAAISO 9001
200+
Programs in production
300K+
Validation scenarios
Mined
Long-tail cases surfaced
Ready
Labeling-ready dataset
Find the data worth labeling.
Tell us about your dataset and labeling budget. We will put a dedicated team on it and send back the smaller set that teaches the model more.