List of Oracle Cloud Infrastructure Vision Customers
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Since 2010, our global team of researchers has been studying Oracle Cloud Infrastructure Vision customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Oracle Cloud Infrastructure Vision for Image Recognition from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Oracle Cloud Infrastructure Vision for Image Recognition include: Qti.ai, a United States based Professional Services organisation with 2000 employees and revenues of $340.0 million, My Eyelab, a United States based Retail organisation with 1000 employees and revenues of $200.0 million, Children's Medical Research Institute, a Australia based Life Sciences organisation with 300 employees and revenues of $27.0 million, Qti.ai, a United States based Professional Services organisation with 10 employees and revenues of $1.0 million and many others.
Contact us if you need a completed and verified list of companies using Oracle Cloud Infrastructure Vision, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Children's Medical Research Institute | Life Sciences | 300 | $27M | Australia | Oracle | Oracle Cloud Infrastructure Vision | Image Recognition | 2021 | n/a |
In 2021 Children's Medical Research Institute adopted Oracle Cloud Infrastructure Vision as part of an OCI deployment supporting large-scale bioinformatics and data science. The Oracle Cloud Infrastructure Vision implementation, classified under Image Recognition, is being used to automate image-based workflows such as bounding cells for biomedical research in healthcare and research contexts.
The implementation includes Oracle Cloud Infrastructure Vision and OCI Data Labeling to create labeled training sets and to operationalize bounding box workflows, model training, and inference pipelines. Configuration emphasizes scalable compute for high throughput image processing and data labeling pipelines that feed into experimental image recognition models.
OCI Vision is integrated into the broader OCI environment used by CMRI for compute and storage intensive bioinformatics and numerical simulation workloads, enabling research and data science teams to run image analysis alongside other analytic pipelines. The operational scope is centered on biomedical research groups and bioinformatics teams working on image-based experiments and simulation driven studies.
Governance is described as experimental and early stage in Oracle’s materials, with usage focused on pilot workflows and iterative validation. The move to OCI produced reported large compute and cost benefits, example results include reducing typical numerical simulation time from approximately 30 days to approximately 5 days, and improving resource efficiency by 30 to 50 percent.
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My Eyelab | Retail | 1000 | $200M | United States | Oracle | Oracle Cloud Infrastructure Vision | Image Recognition | 2022 | n/a |
In 2022, My Eyelab, part of the Now Optics retail group, implemented Oracle Cloud Infrastructure AI capabilities by deploying OCI Language to analyze customer feedback and surface operational signals for customer experience and CRM teams. The initial deployment centralized multi-channel feedback into natural language processing pipelines to categorize issues and prioritize response workflows for store operations and customer service.
OCI Language was configured to support automated feedback ingestion, text classification, intent detection, and routing into CRM and customer experience workflows, aligning outputs with operational ticketing and agent queues. The configuration emphasized integration of NLP outputs into existing customer service processes to accelerate issue triage and enable programmatic escalation across customer experience and operations functions.
My Eyelab intends to extend its AI footprint by adopting Oracle Cloud Infrastructure Vision, using Oracle Cloud Infrastructure Vision in the Image Recognition category to flag potential eye diseases from retinal images as a planned diagnostic screening capability. Oracle Cloud Infrastructure Vision is described as a next step to integrate visual inference into clinical intake and screening workflows, generating triage alerts for follow up rather than as a fully documented live deployment in the case study.
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Qti.ai | Professional Services | 2000 | $340M | United States | Oracle | Oracle Cloud Infrastructure Vision | Image Recognition | 2023 | n/a |
In 2023, Qti.ai implemented Oracle Cloud Infrastructure Vision to operationalize Image Recognition for brand protection across e-commerce platforms. The implementation addressed detection, documentation, prioritization, and evidence collection workflows that feed takedown and legal processes for independent artists and designers.
The technical implementation combined OCI Data Labeling for assembling and annotating training datasets, Oracle Cloud Infrastructure Vision custom models for deep learning based image analysis, and OCI Object Storage for secure, redundant image storage and dataset consolidation. Qti.ai generated labeled infringed image training sets, trained brand specific Vision models once labeling thresholds were met, and deployed those custom models to flag modifications such as cropping, rotation, color inversion, and watermark removal. The deployed models perform probability scoring so that images are automatically sorted by likelihood of infringement prior to human review.
Operationally the solution is integrated into Qti.ais automated scanning pipeline that monitors e-commerce listings, pre-sorts high probability infringements for the review team, and preserves evidentiary artifacts for downstream takedown and legal workflows. The deployment scope centers on brand protection functions across client engagements, with direct impact on the image review team and legal/client interfacing functions. Models are implemented per brand to maintain precision in detection and prioritization.
Governance and process design explicitly account for the Digital Millennium Copyright Act requirement for human confirmation of infringements, therefore automated Vision outputs are used to accelerate pre-review triage rather than replace legal signoff. After adopting Oracle Cloud Infrastructure Vision and associated OCI AI services Qti.ai reported labeling and review throughput improvements of about 5.5 times faster than before, enabling reallocation of staff time toward client engagement and pursuing legal action against infringers.
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Professional Services | 10 | $1M | United States | Oracle | Oracle Cloud Infrastructure Vision | Image Recognition | 2023 | n/a |
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