LAKSPIRE

Services

AI annotation, training datasets and the operations behind them.

A nine-service annotation console for modern AI teams, plus the surrounding data operations — collection, cleansing, coverage analytics and programme support — that keep every labelled dataset honest end to end.

The flow

Raw records in. Structured, verified data out.

Every engagement runs through the same disciplined flow — processing, gears of technology-enabled work, human review where it matters, then structured records the client can actually use.

01 · Annotation types we ship

Ten label types. One annotation console behind every dataset.

From 2D boxes to LiDAR point clouds, multilingual NLP and document OCR — the label formats we deliver as production-ready training and evaluation data for modern AI teams.

2D Bounding Boxes

Tight rectangles around every subject in a frame — the foundational label behind object detection, retail vision and safety AI.

VisionDetection

Polygon & Semantic Segmentation

Pixel-perfect outlines and per-pixel class masks for medical imaging, autonomous driving and precision retail applications.

VisionPixel-level

Keypoint & Pose Estimation

Skeleton-graph labels for sports analytics, ergonomics, fitness apps and human–robot interaction — every joint tagged and linked.

VisionKeypoints

3D Cuboid Annotation

Volumetric boxes with width, height and depth for AR overlays, warehouse robotics and driver-assistance systems.

3DSpatial

LiDAR Point-Cloud Labelling

Per-point class, instance and cuboid annotation on raw LiDAR scans — the ground truth self-driving and robotics stacks are trained on.

LiDARAutonomy

Video Tracking & MOT

Frame-by-frame object tracking with stable IDs across occlusion — behaviour analytics, sports vision and multi-object tracking.

VideoTracking

NLP & Named-Entity Recognition

Entity spans, relations, intent and coreference — the linguistic labels behind search, chat, extraction and compliance NLP.

TextNLP

Audio Transcription & Events

Word-level transcripts, speaker turns, timestamps and sound-event tags for voice assistants, contact-centre AI and ambient audio.

AudioSpeech

Sentiment & Classification

Topic, intent, sentiment and moderation labels applied at scale with disciplined guideline enforcement and inter-annotator checks.

TextClassification

OCR & Document Field Extraction

Text detection, key-value field capture and clause labelling on invoices, forms, contracts and records — accuracy under real-world document variation.

DocumentsOCR

02 — 05 · Broader capability

Around every labelled dataset — the operations that make it work.

Sample preparation, annotation analytics, versioned training sets and programme support — the surrounding work that turns Section 01's labelling into production-ready training data.

Group 02

Data Operations

Everything that has to happen before a sample is ready to annotate — sourcing, entry, cleansing, conversion and validation of the raw material that feeds the labelling console.

Data collection

Data entry & transcription

Data cleansing & normalisation

Format conversion

Data validation

PII redaction

Deduplication

Sample preparation

Group 03

Annotation Analytics & Reporting

The numbers behind the labels — coverage, class distribution, inter-annotator agreement, throughput and quality trends — reported clearly enough that decisions get made.

Annotation coverage analysis

Class distribution reports

Inter-annotator agreement

Throughput dashboards

Quality trend reporting

Delivery reporting

Group 04

Training & Evaluation Datasets

Assembled, versioned datasets that ship straight into your training and evaluation pipelines — training splits, gold sets, HITL corrections, edge-case packs. Section 01 is the bench that produces them.

Training splits

Evaluation gold sets

Preference & ranking data

HITL correction sets

Edge-case packs

Dataset versioning

Group 05

Programme Support

The programme layer around an annotation engagement — guidelines, taxonomy management, reviewer onboarding, documentation and delivery co-ordination. The quiet work that keeps a labelling operation honest.

Annotation guideline authoring

Taxonomy & schema management

Reviewer onboarding

Documentation & runbooks

Delivery co-ordination

Programme reporting

Scope

We only publish services we can genuinely deliver.

If your requirement sits at the edge of what's listed — or spans two groups — start a conversation. The team will tell you plainly whether we're a good fit and, if not, what a good fit would look like.

Discuss your project