Enterprise Platform for Data-Centric AI

Name: I-Tera
Brand: Globik AI
Availability: InStock

At the core of Globik AI is iTera; a cloud-native, multi‑modal platform engineered for the complexities of modern AI. It enables seamless annotation, validation, and delivery of structured datasets for enterprise-grade AI.

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Key Features and Capabilities

Multi-modal Data Support

Handle every data type confidently. Images, audio, video, text, documents, spatial data, and more. Our platform unifies diverse data formats in one annotation environment.

Pre-configured Use Case Templates

Choose from over 50 templates built for common pipelines such as computer vision, NLP, conversational AI, multimodal systems, and synthetic data generation. Templates follow industry best practices, reducing ramp-up time and ensuring consistency.

Programmatic Data Labeling with Custom Integrations

Enabling automated annotation using your own models or foundational/LLMs with tight integration allows high-throughput and scalable labeling while retaining accuracy.

Human-in-the-Loop and Active Learning

Leverage active learning strategies to bring human validation directly into the annotation cycle ensuring the platform focuses on data samples most uncertain to the model, and optimizing label quality iteratively.

Cloud Native Collaboration and Workflow Management

Hosted in the cloud for global access, with role-based user management, integrated quality assurance workflows, and direct integration with enterprise data sources and project repositories.

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Scalability, Cost Efficiency, and Quality Metrics

Accelerate annotation workflows by up to 10× while reducing costs by up to 90 %—without compromising accuracy or scale. Every stage embeds QA metrics, benchmarking, and audit trails to maintain enterprise-grade output.

iTera at a Glance

Designed for Data-centric AI

Focusing on the highest-quality inputs so your downstream models deliver maximum value.

Integrates with Enterprise Models

Supports foundational models and your custom LLMs—including supervised fine‑tuning, preference‑based ranking, RLHF workflows, and synthetic data expansion.

Reduced Time-to-Value and Operational Efficiency

By combining automated workflows with human-in-the-loop validation, companies achieve faster project turnaround and superior dataset reliability.

Secure, Auditable, and Compliant

Designed for highly regulated industries—provides controlled access, audit logs, and supports enterprise standards including GDPR, HIPAA, SOC2.

Licensing and Deployment Models

We understand that different organizations have different needs. That’s why iTera is available in flexible models.

Platform Licensing

Enterprises can license iTera for internal annotation teams, with full workflow setup, automation, and integrations.

Direct Purchase

For clients who want full ownership, iTera can be deployed on-prem or in a private cloud — with customization and long-term support.

Partner Deployment

For governments, enterprises, or AI labs requiring controlled environments, we offer co-build and transfer models.

See How it Works in Streamlined Steps

Project Initiation

Create and configure your annotation project with custom labels and templates.

Data Source Integration

Connect cloud storage, APIs, or on-prem data for seamless ingestion.

Template Selection or Custom Setup

Choose use-case templates or define annotation guidelines manually.

Automated Annotation Use

Use integrated LLMs or domain models for programmatic labeling; custom model imports supported.

Human QA and Validation

Experts interact with uncertain cases flagged by active learning; quality thresholds enforced.

Export and Integration

Export structured datasets as per the required format into your data lake or ML pipeline.

Model Fine Tuning

Optionally fine-tune LLMs through supervised learning, RLHF, or ranking workflows.

Feedback Loop and Continuous Improvement

Monitor label performance and retrain models to evolve accuracy.

Supported Use Cases

Each template includes industry best practices and QC workflows.

Frequently
Asked Questions
‍

Q: What kinds of data can iTera handle - will it suit my project’s data types?

iTera supports a wide range of data types such as images, audio, video, text, documents, spatial data and more, so whether your project needs image annotation, speech transcription, document parsing or multimodal data handling, iTera can handle it.

Will using iTera mean we must manually annotate everything, or is automation possible?

You don’t have to rely solely on manual annotation. iTera supports programmatic (automated) annotation using your own models or foundation/LLMs. At the same time, for quality and precision, there’s optional human-in-the-loop review and active-learning workflows for uncertain cases.

If our project grows - more data, more complexity - can iTera scale accordingly?

Yes, iTera is cloud-native and built for scalability across data types and workloads. It’s designed for enterprise-scale deployment, so you can scale up annotation volume as your project grows.

Suppose we need custom annotation workflows or domain-specific labels - can we configure iTera accordingly?

Absolutely. While iTera offers over 50 pre-configured templates for common pipelines (computer vision, NLP, synthetic data, etc.), you also have the option to define custom labels and annotation guidelines manually to match your domain.

How does iTera support downstream model-building (e.g. LLM fine-tuning or computer-vision pipelines)?

iTera supports data output that’s ready for model training/fine-tuning, including structured datasets for NLP, computer vision, multimodal LLM workflows, synthetic data generation, and more. That helps accelerate time to model-ready data.

If we already have existing data pipelines or storage, can iTera work with them directly?

Yes, iTera allows integration with your cloud-storage, APIs, or on-prem data sources. You can connect your existing data infrastructure for seamless ingestion.

How does iTera ensure annotation quality and reliability, especially for sensitive or regulated use cases?

iTera embeds quality-assurance workflows at every stage. There are QA metrics, audit trails, role-based access controls, and compliance readiness (e.g. for regulated industries). This ensures datasets are reliable, traceable, and enterprise-grade.

What deployment or licensing options do we have? Do we have to use a public cloud?

There’s flexibility. iTera can be licensed for internal teams, or deployed on-premises or in a private cloud if you need full ownership and control. For highly regulated clients or controlled environments, there is also a “partner deployment” or co-build/transfer model.

What kind of cost or speed advantage can we expect if we use iTera for annotation compared to building in-house manually or via ad-hoc tools?

Clients see significantly improved throughput: annotation workflows can be accelerated by up to 10×, and costs reduced by up to 90%, without sacrificing accuracy or quality.

If we operate in a regulated industry (e.g. healthcare, finance), does iTera support compliance and audit needs?

Yes. iTera is designed with enterprise compliance in mind: it offers controlled access, full audit logs, and supports compliance standards relevant to regulated industries.

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