We partner with enterprises, innovators, and governments worldwide to deliver trusted data, scalable AI solutions, and responsible transformation.

We are a global AI services company helping organizations innovate by building, scaling, and operationalizing AI responsibly.
We provide multimodal and structured data services, LLMOps engineering expertise, and responsible AI strategy. Our work supports the development of intelligent systems built for reliability, control, and real world use.
Across healthcare, finance, automotive, retail, and other sectors, we focus on AI systems that perform as expected. Our approach ensures models operate reliably within real operational environments.
SLAs on acceptance rate, latency, and accuracy. Multi-layer QA with measurable inter-annotator agreement.
Elastic teams + automation. Playbooks for large ramps, multilingual coverage, and peak-load handling.
Data residency options, private networking, full audit trails. Alignment with major frameworks (GDPR, HIPAA, and more).
Embedded safety evaluations, bias/fairness checks, explainability artifacts are shipped with your models.
Orchestrated automation with verified experts for sensitive workflows, leading to top model performance.


We provide accurate and representative datasets that reduce bias and support reliable model development. Our collection methods focus on coverage, consistency, and real world relevance to help teams prepare models for practical deployment.
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We deliver structured datasets across text, audio, image, video, three dimensional data, and LiDAR. Subject Matter Experts work directly within our processes to ensure annotations remain precise, context aware, and trusted across regulated and enterprise environments.
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We convert physical and legacy records into secure digital formats while protecting sensitive information. Using OCR and AI based analysis, we extract structured data from unstructured documents with accuracy, compliance, and audit readiness.
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We create high-fidelity synthetic datasets and scenario simulations to overcome data scarcity, privacy restrictions, and edge-case gaps. By generating controlled, domain-specific datasets, we enable AI systems to perform in privacy-sensitive environments with confidence.
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We support enterprises and AI teams in training and fine tuning large language and multimodal models for practical use. Our work focuses on performance, consistency, and reliability across real world scenarios and deployment environments.
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We help make large language models safe, policy aligned, and suitable for enterprise use. Through alignment data, safety programs, and red teaming, we reduce hallucinations, support compliance needs, and protect organizational trust.
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We conduct independent evaluation to measure model behavior under defined conditions. Our testing includes benchmarks and stress scenarios that produce transparent and repeatable performance reports for informed decision making.
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We connect language models to trusted knowledge sources to ensure factual and grounded outputs. Our retrieval and knowledge engineering workflows support accurate responses across enterprise information systems.
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We offer our clients access to Globik's proprietary annotation platform for in-house teams with custom workflow setup, access controls, and API integration.

