High quality,
human-in-the-loop,
data services.

Fully-managed, end-to-end data services - inclusive of AI data annotation/labelling, dataset validation, data collection, surveys, market research, ethnographic intelligence, etc. across a wide variety of use-cases.

Looking for robust training dataset?

Accurately labelled data translate to better model performance - an underlying truth about machine learning and its functional potential. We partner with AI enterprises to co-create workflows, provide human-in-the-loop, pixel-accurate data labeling services, and deliver robust training datasets.

Our Annotation Stack.
Bounding Box/
Ellipse
Polygon/
Polyline
Semantic
Segmentation
Categorisation
Video
Annotation
Point
Labelling
LiDAR
Annotation
Optical Character
Recognition
Audio
Transcription
DICOM
Annotation
Standard AI Data Annotation Pricing Packages.

Starter Pack.

USD $4.5+/hr.

+ Single-pass quality check
+ 1x workforce supervisor
+ 95% accuracy guarantee

Appropriate for standard CV, NLP, LLM, and/or ASR recognition tasks utilising our labeller workforce.

Enterprise Pack.

USD $8/hr.

+ Multi-pass quality checks
+ 2x workforce supervisor
+ 98.5% accuracy guarantee

Appropriate for complex workflows pertaining to large datasets requiring high accuracy.

Domain Expertise.

USD $12-25/hr.

+ Key domain experts
+ 1x project manager
+ 1x data engineer

Fit for medical, agronomy, legal, financial, among other use-cases requiring expert support.

Academia.

USD $4/hr.

Special pricing for university faculty members and PhD pursuants.

Academia partner packages are customised based on their needs and research expectations.

We accommodate free pilot projects to understand quality and velocity parameters of all assignments, and provide both instance-based and hourly pricing packages.

DO A FREE PILOTCHECK OUR OPEN DATASETS

Data collection/research?

We support our partners with a myriad of data collection, analysis, and research.

Market Research

Uncover consumer behavior, brand perception, and competitive dynamics through targeted surveys, focus groups, and segmentation analysis.

Data Analytics + Intelligence

Transform raw data into actionable insights using advanced analytics or spatial pattern recognition, predictive modeling, and interactive dashboards.

Industry-Specific Research

Deliver deep-dive analyses focused on sectors such as technology, healthcare, and finance to address specialized market challenges.

Digital & Social Media Studies

Monitor online trends, digital behavior, social sentiment and salience to guide effective digital strategies pertaining to advocacy and product mobilisation.

Mapping + GIS

Integrate aerial and spatial imagery, street mapping, and advanced GIS analysis to deliver insights for urban planning, logistics, and environmental monitoring.

Surveys

Design, execute, and analyse custom surveys that capture critical data - such as on market sensitivity, behaviors, engagement efficacy - aided by our AI tools.

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Example Case for Data Collection
Mapping Dhaka’s Informal Settlements for Climate Resilience and Urban Development with Humanitarian OpenStreetMaps Team and World Vision Bangladesh.

Activating supervised learning models.

Acme AI works with models surrounding computer vision, natural language processing, and automatic speech recognition in urban planning, construction, banking, national security, healthcare, transportation, retail, manufacturing, acoustic healthcare, consumer electronics, agriculture, robotics, etc.

All of our projects have dedicated project and customer support for smoothing out experience and communication.

Annotation Workflow.

01 Intro. Convo.

Introductory conversation with a client to understand brief and gather requirements for the data project.

02 Guide + Pilot

Develop initial work guidelines and setup project. Additional personnel training ascertained if the assignment calls for it.

03 Demo Production

Mobilise a demo production run, share questions with the client for clarification and fine-tune data quality parameters.

04 Final Setup

Setup project based on approved workflow in addition to creating and assigning tasks for annotators/surveyors/data workers.

05 Data Work Begins

Delve into the data work and complete tasks - be it data collection, validation or labelling - for the project, either in batches or collectively.

06 Data Quality Check

Operationalise a single-pass or multi-pass quality check process in parallel to production to isolate inconsistencies.

07 Delivery

Final quality assurance check to confirm 95% accuracy with project files handed over to the client as a final delivery.

08 Data Razing

Data razed 10 days after delivery or earlier based on client requirement and our data protection policies.

Tools we frequently use.

Industries.

Accurate labeling is a critical part for any algorithm to perform as intended. We strive to provide pixel-accurate datasets within cost-effective packages for our clients across different industries. Following are some example of annotations done on different industries.

Spatial Intelligence.

Geospatial detection use-cases are one of the key avenues where AI is breaking barriers. Iterations of object detection from EOS multispectral and radar imagery can be many, inclusive of land use and land cover, vegetation mapping, vehicle detection and types, oceanic vessels, urban planning, and even detecting pollution spread trajectories.

Popular Labelling Forms.

Bounding Box

Polygon/Polyline

Classification

Transportation.

We refer to transportation as a progenitor space for machine learning - revolving around AI iterations of autonomous vehicles, fleet management, number plate detection, smart accessories, traffic management and road infrastructure management.

Popular Labelling Forms.

Semantic/Panoptic Segmentation

Polygon/Polyline

Video/Sequence Annotation

3D Cuboid in LiDAR/ Bounding Boxes

Manufacturing + Retail.

Automation in manufacturing and industrial production lines are increasingly being explored, ranging from defect detection in consumer goods to developing computer vision systems that guide manufacturing automatons. Retail and warehousing work in a similar context with real-time feedback on customer experience or clusters, and predicting stock surplus or shortages to name a few.

Popular Labelling Forms.

Bounding Box

Polygon/Polyline

Classification

Optical Character Recognition

Banking + Insurance.

Document processing is a big part of banking and insurance sectors which can often become an arduous endeavor. Thankfully, NLP and computer vision can change the game and we are here to make sure that they do it right.

Popular Labelling Forms.

Optical Character Recognition

Classification

Medicine + Healthcare.

Precision medicine, diagnosis automation, remote surgeries, treatment modelling, prescription analysis and emergency medicine deliveries are just a few of the enormous wealth of medical innovations currently in the process of development and scaling in the world. Annotation on DICOM or multi-layered TIFF images paired with robust deep learning algorithms is expected to make the next generation of medical AI systems.

Popular Labelling Forms.

DICOM Annotation

Polygon/Polyline

Audio Transcription

Free Pilot

Task Guide

Do a pilot before starting the project for checking quality and accuracy parameters and bottlenecks.

Detailed task guidelines for resources to minimize roadblocks once  work commences.

Management

Quality Control

Provide a project manager who takes ownership of the work and can be reached at any time.

Single-pass and multi-pass QA, ensuring global standard quality control prior to releasing data.

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PERKS

We provide fully managed annotation services. Our skilled annotators are rigorously trained and our team leads have extensive experience in managing image annotation workflows and coordinating with clients. The perks mentioned here are services we provide which are included in our standard pricing model.

Expert workforces,
ready to take on any challenge.

Confidentiality certification.

All of our workforce are certified in CDC/NCHS Confidentiality Training to PIIs. This is critical for medical data and is also interoperable to banking and retail use-cases.

Total Data Quality (TDQ) certification.

Our operational leaders are certified in Total Data Quality from the University of Michigan - adopting best practices to assimilate into client's use-cases and inform on possible data and bias issues.

22.2%

faster work per
hour by our certified annotators

Faster labelling equals time and cost savings.

Acme AI only employ workers who pass our rigorous certificate training programme. In comparison to the average labeller, certified annotators work faster - translating to hourly cost savings.

270+

certified workers

A growing on-prem and remote labelling army.

What started out as a team of four people in 2020 scaled to a taskforce of over 270 people in a span of two years. Our workforce grows by at least 7% every month.

30%

on-demand workforce scaling potential

We can scale on short notice.

Based on requirement and business value, we can scale our on-prem and remote workforce by upto 30% of its current capacity. Examples include increasing workforce by 13% in a week's notice.

Let's start a project together.

Get high-quality data or training dataset for your AI models or research/monitoring endeavours. We bring the best-in-class, scalable, and adaptive data processing services.

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