What We Deliver
CAPABILITIES
Erud AI offers a full suite of services, from data creation and annotation to evaluation and fine-tuning. Whether you're launching a new model or refining an existing one, we can customize a data solution based on your goals.
1000+
75+
50+
30+
5+
MODALITIES
LANGUAGES
DOMAINS
COUNTRIES
AI TRAINERS
1000+
75+
50+
30+
5+
MODALITIES
LANGUAGES
DOMAINS
COUNTRIES
AI TRAINERS
We work in 50+ domains. No matter how niche or complex, we can create a workforce to curate your data.
Domains
LEARN MORE
It’s impossible to list every domain we can cover, but we’ve provided a sample below. Have a niche or complex project? Reach out to discover how we can build a tailored workforce to meet your unique needs.
Niche Knowledge and Skillsets
- Artists and Illustrators
- Geospatial Experts
- Agronomists
- Astronomers
- Sports Analysts
- Historians and Archivists
Highly Educated Specializations
- Domain Masters and PhDs
- STEM Scientists
- Legal Professionals
- Healthcare Professionals
- Cybersecurity Experts
- Educators and Trainers
Seasoned Business Professionals
- Senior+ Strategy Experts (Finance, Product, Operations, HR, etc)
- Enterprise Sales Leaders
- Marketing Strategy Leaders and Creatives
- Customer Support Professionals
- Policy Advocates and Ethics Advisors
Technology and Industry Specialists
- Coders and Software Engineers
- IoT Engineers
- Manufacturing Experts
- Telecommunications Engineers
Creatives and Media Industries
- Content Creators
- Gamers
- Social Media Analysts
- Media and Film Experts
We work in 30+ languages and 75+ countries.
GEOGRAPHIES AND LANGUAGES
Make your AI more inclusive and accessible by using data from native speakers of 30+ languages across 75+ countries. Our contributors bring real-world cultural and language insights to ensure your models connect with people everywhere. For any project in any modality or domain, we can source in a variety of languages and geographies.
REQUEST INFO ON AVAILABLE LANGUAGES AND GEOS
We can create, collect, annotate, and evaluate data in any modality.
Modalities
Image
Text
Video
Illustration
Tactile
Biometric
Audio
Combination
We specialize in creating, collecting, annotating, and evaluating complex, difficult to find, and niche data. Whether you need video and audio data created from scratch or evaluations of text based data, we can help!
- Examples: Articles, emails, code, transcripts, captions, chat logs.
- Applications: Sentiment analysis, natural language processing (NLP), translation, document summarization.
- Examples: Photographs, X-rays, satellite imagery, digital artwork.
- Applications: Image classification, facial recognition, object detection, medical imaging diagnostics.
- Examples: Podcasts, phone calls, background noise, alarms.
- Applications: Speech-to-text, audio classification, music generation, environmental sound recognition.
- Examples: Movies, simulated interactions, surveillance footage, live streams, animations.
- Applications: Object tracking, action recognition, video summarization, gesture recognition.
- Examples: Animations, blueprints, sketches, diagrams, comics, handwritten or drawn articles.
- Applications: Design and prototyping, educational tools, art generation, cultural preservation.
- Examples: Force feedback in gaming controllers, braille interfaces, robotic touch sensors.
- Applications: Virtual reality feedback, prosthetics, robotics, accessibility devices.
- Examples: Fingerprints, retina scans, facial recognition, voice patterns.
- Applications: Security systems, healthcare diagnostics, personalized user authentication.
- Examples: Videos with subtitles, interactive AR/VR environments, synchronized audio-visual learning materials.
- Applications: Multimodal AI, immersive training simulations, cross-modal retrieval.
We're experienced in data creation, evaluation, and annotation.
Project Examples
Multimodal Data Creation from Scratch
- Podcasting audio, video, and scripting outlines creation from scratch
- Audio collection of wake words and phrases in different emotive tones
- Video and audio educational data in a staged mock-classroom setting, created by real educators in specific educational subjects
Multi-Step SFT and RLHF Evaluations
- Complex projects with multiple specifications, incorporating diverse sub-actions within a single task for AI Trainers.
- Develop an ideal output based on a curated set of questions
- Rank model-generated responses against exacting predefined criteria
Niche Skill Capture and Annotation
- Creation of static and rigged illustrations based on stringent stylization guidelines
- Audio capture of medical provider SOAP notes based on simulated medical data and patient visits
High Velocity Project Ramping
- Less than 3 weeks to full ramp for many projects
- Scalable solutions based on repeatable processes
- Innovative, proprietary solutions for upskilling and managing workforces
Explore the range of projects we’re equipped to tackle. From large-scale data collection to custom annotation workflows, our expertise spans diverse applications, providing a glimpse into the solutions we can deliver to meet your unique needs.
Learn how our operational excellence leads to higher quality, lower cost, and more ethical outcomes.
CASE STUDY
The foundation of successful AI projects lies in operational excellence, especially in the curation of top notch data. Our methodology is based in lean six sigma principles. We rely on clear standard work, repeatable processes, and reduction of waste to ensure every step of the project is aligned toward achieving the client’s goals.
Our approach focuses on delivering not just data, but a seamless and efficient experience. By starting with the end goals in mind, we tailor each phase of the project—from setup and scoping to hiring, onboarding, quality control, and delivery—to meet those objectives without unnecessary rework or wasted effort.
The Problem
Our Process
The Results
Why It Matters
- Data availability was scarce due to being niche in nature
- Vendors refused to quote the project due to exacting requirements and heavy operational lift
- The project required onsite workforces to create the data because it consisted of video/audio recording with precise room specifications
- Excessive rework in prior similar projects drove up costs and wasted resources.
- Researchers spent large portions of time coaching the previous vendor's AI Trainers on specifications, and sifting through delivered data that didn't meet requirements.
By following this approach, the client saw real, measurable benefits:
1. Faster Innovation
Clear planning and reliable delivery helped them cut project timelines by ~12%, allowing them to focus on meeting project timelines rather than worrying about data availability as a bottleneck.
2. More Diverse Datasets
Our hiring process ensured that the dataset reflected a wide range of cultures and scenarios, improving the data's ability to train for performance in diverse environments.
3. More Time for Researchers
With clean, ready-to-use data, the client’s researchers were able to spend more time on high-value work and less time fixing issues. After the initial scoping phase, the client's researcher was able to be hands off with training, feedback, and rework.
5. Reduced Costs and Improved AI Trainer Pay
By delivering data that didn’t need rework and sticking to efficient processes, we were able to pay AI Trainers at a highly competitive market rate, leading to lower turnover and higher innovation velocity for the client.
This isn’t just about delivering data—it’s about delivering results. At Erud AI, we help our clients innovate faster, produce better models, and work more efficiently by focusing on quality from start to finish.
First we took the time to shadow the researcher and understand project specifications, how the data would be used, and how ground truth data was structured. During this phase, the researcher was very hands on and shared all the documentation available.
2. Tailored Hiring to Build the Right Team
After understanding project requirements and the goal data outcomes, we created a tailored hiring strategy to create a team who could create the data necessary. Since this project was extremely niche, we had very few AI Trainers who could work on the project and needed to source from scratch. Using our standardized hiring process, we trained our Recruiting partners on the exact profile and skillset needed to succeed in this project. We also created a skills test to vet AI Trainers prior to onboarding them to ensure that their work would meet the specifications.
3. High-Touch Onboarding for Immediate Results
We created a comprehensive onboarding program for this project from scratch. The project had extremely specific stylization guidelines, and specific criteria for several aspects of the data structure. Rather than providing the material in text format and hoping that AI Trainers would read and retain the information, we created a University style lecture and help live trainings with the AI Trainers. AI Trainers practiced with a series of quizzes and had to complete a final exam prior to moving onto the project. We also provided clear training on the expected outputs and deliverables so that we could hold accountability to our AI Trainers.
4. Built-In Quality Control at Every Step
We worked in the customer's platform which meant that we had to create an exacting process to ensure our customer did not receive bad data. We approached this in the following manner:
- Comprehensive Training: Every AI Trainer completed an in-depth onboarding process, including university-style lectures, quizzes, and a final exam, before being assigned to a project.
- Probationary Period: New AI Trainers started in a probationary role, working closely with reviewers to receive live feedback on their video and audio collections. This hands-on coaching helped prevent the development of bad habits.
- Performance-Based Advancement: AI Trainers who maintained a 95% pass rate over a week or a 99% pass rate for 3 days advanced to a trusted role, where they could submit work autonomously. However, any drop in quality returned them to probation for additional coaching.
- Ongoing Quality Monitoring: Even trusted AI Trainers had ~70% of their work audited to maintain high standards. Trainers falling below a 90% pass rate for two consecutive days were retrained to restore performance.
- Final Quality Assurance: All deliverables underwent our proprietary speed auditing process, ensuring no bad data reached our customer.
- Deliverable-Based Payment: The client paid a fixed amount of Y dollars for a deliverable of X amount of data.
- Aligned Objectives: This structure motivated us to optimize resources and processes, balancing training, quality control, and any necessary rework within the agreed budget.
5. Delivering Data That Works
Our ultimate goal is to deliver data that requires no additional work from our clients. Through operational excellence, we were able to deliver data with a .05% rejection rate from our customer.
