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SanJose, Usa
AWS SageMaker
CVAT
Dataloop
Datasaur
iMerit
Labelbox
Toloka
V7 LabsNo subject matter listed
Medical Dicom
TextiMerit is a leading AI data solutions company providing high-quality data across computer vision, generative AI, natural language processing, and content services that power machine learning and artificial intelligence applications for large enterprises. iMerit provides end-to-end data labeling technologies and solutions, model evaluation solutions to Fortune 500 companies in a wide array of industries including agricultural AI, autonomous vehicles, commerce, geospatial, government, financial services, medical AI, frontier models and enterprise technology. iMerit is headquartered in the United States, with large CV, Gen AI and NLP teams in India, US, Bhutan and Europe.
Security & Privacy Overview At iMerit, safeguarding client data and projects is at the core of our operations. We maintain a multi-layered security framework that combines physical safeguards, advanced cybersecurity measures, employee confidentiality programs, and rigorous compliance practices. Our approach ensures confidentiality, integrity, and availability of data across all environments. Physical Security Access to delivery centers is strictly controlled through biometric readers, proximity card-based systems, CCTV surveillance, and on-site security personnel. Guest access is managed through pre-authorization, temporary access cards, and mandatory escorting. Sensitive work areas are restricted to authorized staff, where photography is prohibited and movement of client assets requires formal approvals. Facilities are equipped with fire detection systems, environmental controls, and backup power through generators and UPS units. Cybersecurity & Technical Controls Our infrastructure employs next-generation firewalls, IDS/IPS, VPNs with multi-factor authentication, and MAC-based Wi-Fi access controls. Client data is stored in encrypted S3 buckets and transmitted via TLS 1.2 or higher. Data storage on local devices is prohibited unless approved, with secure deletion procedures followed as per client requirements. Platforms are hardened to CIS benchmarks, hosted on AWS/GCP, and undergo regular patch management and OWASP-compliant security audits. Endpoints are secured with full-disk encryption, antivirus protection, DLP policies, centralized patch management, and restrictions on removable media. Employee Confidentiality & Data All employees and contractors sign strict Non-Disclosure Agreements (NDAs). Mandatory and ongoing training programs cover data security, privacy, phishing awareness, and compliance best practices. Access to data and systems follows the principle of least privilege, with role-based permissions, unique user IDs, multi-factor authentication
Leading Foundation Model company leveraged iMerit Scholars and Ango Deep Reasoning Lab to create original math problems capable of stumping their current development model.
Global consumer tech company partnered with iMerit to create a diverse set of prompt-response pairs across various domains to improve LLM accuracy.
To improve the precision of its medical chatbot, this US technology company consulted iMerit on how to utilize and implement a new medical dataset to ensure accurate medical advice for users.
To support the clients large-scale HD mapping efforts, iMerit deployed a specialized team with a tiered skill structure designed to handle both foundational GIS tasks and advanced autonomous vehicle mapping. Deployed tiered GIS talent to execute both foundational and advanced HD mapping tasks using AWS RTN and QGIS Proposed 12 tool enhancements to improve mapping efficiency, accuracy, and user experience Conducted RTN validator reviews and city-specific QA feedback sessions to drive annotation standardization and quality Rolled out comprehensive validator training and updated PKTs to reinforce best practices and project knowledge Reengineered the QA workflow to include three internal validation layers, improving first-pass accuracy and reducing client rework
A global healthcare technology company partnered with iMerit to apply supervised fine-tuning (SFT) to a vision-language transformer model designed for generating clinically accurate reports from radiologic images. The objective was to improve model output reliability using expert-reviewed and scored medical data.