AI delivery
Multimodal annotation for an autonomous systems developer
A developer of autonomous ground systems with engineering operations in North America and Asia, training perception models for operation in dense, unstructured environments.
- Industry
- Technology and Startups
- Pillar
- AI delivery
- Client geography
- North America and Asia
- Delivery location
- Corpshore AI global delivery with UAE programme management
- Languages
- English C1, plus multilingual review capability
- Engagement model
- Programme-based, output priced with quality gates
- Timeline
- Fourteen months, ongoing
The challenge
The client needed very large volumes of precisely annotated sensor data across camera, lidar and radar, with temporal consistency maintained across sequences. Their previous vendors could produce volume or precision but not both, and the failure mode was consistent: quality degraded as throughput scaled, and the client only discovered it during training. They also needed a partner capable of handling environments the client's existing datasets underrepresented, including the dense mixed traffic and pedestrian conditions typical of Gulf and South Asian cities.
What Corpshore did
Corpshore AI ran the programme through its global delivery network with programme management based in the UAE, giving the client a single accountable interface across time zones.
The core design decision was to make quality a gate rather than a report. Every batch passes through layered review with defined agreement thresholds, and a batch that fails does not ship. Annotator progression is tiered, so the most complex sequence work is performed only by annotators who have demonstrated sustained accuracy at the tier below. Throughput scales by promoting annotators upward rather than by adding untiered capacity, which is the mechanism that breaks most annotation programmes at scale.
We also collected and annotated data from Gulf and South Asian urban environments to address the client's coverage gap, under full consent and data governance controls.
Delivery model
Programme-based with output pricing, quality gates on every batch, UAE programme management, global annotation capacity across Corpshore AI's multi-country footprint.
Results
- Sustained delivery at the client's required volume with quality held at the acceptance threshold across fourteen months and multiple scale increases, which was the client's central requirement and the thing previous vendors had failed.
- Temporal consistency errors across annotated sequences reduced substantially against the client's prior vendor baseline.
- Coverage of previously underrepresented urban environments materially improved the client's evaluation performance in those conditions.
- The programme has expanded twice and now covers additional sensor modalities.
Why it worked
Every annotation vendor promises quality at scale. The difference is whether quality is enforced before delivery or measured after it. Gating batches costs throughput in the short term and is the only mechanism that holds quality through a tenfold volume increase.
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This is a representative engagement. The client is anonymised, and the figures are drawn from engagement reporting. We do not name a client without written consent, and we do not publish a number we cannot evidence.