ThirdEye is a Silicon Valley based one-stop-shop for Data Sciences, Analytics & Engineering services & products.
ThirdEye has a decade of experience in building end-to-end technical solutions for Fortune 500 companies and start-ups as well.
ThirdEye's services help organizations transform knowledge into strategic & tactical insights for informed & timely business decisions.
Data Sciences
ThirdEye implements end-to-end Big Data solutions with Data Sciences technologies like Artificial Intelligence, Machine Learning, and Deep Learning seamlessly baked into it.
Data Analytics
ThirdEye’s Data Analytics services help businesses increase revenues, improve operational efficiencies, respond quickly to emerging market trends and gain a competitive edge.
Data Engineering
ThirdEye’s Data Engineering Services transform organizational knowledge into insights for more informed and timely business decisions with the best possible TCO.
ThirdEye is a Silicon Valley based one-stop-shop for Data Sciences, Analytics & Engineering services & products.
ThirdEye has a decade of experience in building end-to-end technical solutions for Fortune 500 companies and start-ups as well.
ThirdEye's services help organizations transform knowledge into strategic & tactical insights for informed & timely business decisions.
Data Sciences
ThirdEye implements end-to-end Big Data solutions with Data Sciences technologies like Artificial Intelligence, Machine Learning, and Deep Learning seamlessly baked into it.
Data Analytics
ThirdEye’s Data Analytics services help businesses increase revenues, improve operational efficiencies, respond quickly to emerging market trends and gain a competitive edge.
Data Engineering
ThirdEye’s Data Engineering Services transform organizational knowledge into insights for more informed and timely business decisions with the best possible TCO.
AI Overview
Performance snapshot
ThirdEye Data Inc. is a data engineering and AI/ML consultancy with a broad portfolio spanning machine learning, BI, cloud infrastructure, and custom software development. Across 23 reviews, the vendor earns predominantly strong ratings in technical expertise, communication, and client satisfaction, with one notable low-scoring engagement flagging reliability and delivery concerns. Project management scores are generally consistent, though a modest number of schedule sub-ratings below 4.5 introduce a mild mixed signal. Cost-to-value perception is a recurring strength.
Performance breakdown
Technical expertise
StrongMultiple reviews cite proficiency across a broad modern stack including MS Azure, AWS, Google Cloud, Apache Spark, TensorFlow, GAN models, IBM Watson, Kubernetes, and Python. A utility company engagement delivering ML models into production via MLOps architecture on Azure serves as a high-density anchor confirming advanced applied AI capability.
Project management & delivery
MixedMost engagements report on-time milestone delivery, with several clients explicitly praising schedule adherence and the provision of a dedicated project manager. However, one engagement recorded a schedule sub-rating of 1.0 and another logged 3.5, indicating inconsistent delivery performance across projects.
Communication & collaboration
StrongClients consistently highlight responsive communication, virtual meeting cadence, transparency, and a collaborative working style across multiple independent reviews. The glass manufacturer's Head of R&D specifically rated communication top-notch, and the data services engagement praised pricing and overhead transparency as distinguishing traits.
Reliability
MixedThe majority of engagements conclude with stable, deployed deliverables and positive product outcomes. One significant outlier—a monitoring solutions firm that rated quality and cost at 2.0 and schedule at 1.0—cited unresolved issues and unmet expectations over a two-year engagement, introducing a meaningful reliability concern.
Client satisfaction & outcomes
StrongTangible outcomes are documented across multiple engagements, including a significant increase in BI data volume delivered to an asset management client via AWS Quicksight, 3,000 quality audio recordings for an AR project, and an ML QA automation system delivered to a 10,000-plus-employee electric utility. Willingness-to-refer scores are predominantly 5.0.
Best for
ThirdEye Data is best suited for mid-to-large enterprises and growth-stage technology companies seeking AI/ML model development, data lake architecture, BI analytics pipelines, and cloud deployment on Azure or AWS, particularly where budget predictability and collaborative engagement are priorities.
Clients info
ThirdEye Data's client base spans utilities, manufacturing, media, energy, business services, information technology, and hospitality sectors. Clients range from small startups and founder-led companies with 1–10 employees to global enterprises exceeding 10,000 employees, with project budgets most commonly falling in the $50,000–$999,999 range. Primary industries represented include Information Technology & Software, Utilities & Energy, Manufacturing, Media, Business Services, Hospitality & Leisure. Typical client size bands include 1–10 Employees, 11–50 Employees, 51–200 Employees, 201–500 Employees, 1,001–5,000 Employees, 10,001+ Employees. Common project budget ranges include $10,000 to $49,999, $50,000 to $199,999, $200,000 to $999,999.
Review strength
The assessment is based on 23 reviews drawn from a single platform. The review base spans from 2018 to April 2025, providing reasonable recency; however, a substantial portion of reviews predate 2021 and should be weighted accordingly when evaluating current capabilities. Review date range: May 10, 2018 - Apr 17, 2025.
Performance breakdown
Technical expertise
StrongMultiple reviews cite proficiency across a broad modern stack including MS Azure, AWS, Google Cloud, Apache Spark, TensorFlow, GAN models, IBM Watson, Kubernetes, and Python. A utility company engagement delivering ML models into production via MLOps architecture on Azure serves as a high-density anchor confirming advanced applied AI capability.
Project management & delivery
MixedMost engagements report on-time milestone delivery, with several clients explicitly praising schedule adherence and the provision of a dedicated project manager. However, one engagement recorded a schedule sub-rating of 1.0 and another logged 3.5, indicating inconsistent delivery performance across projects.
Communication & collaboration
StrongClients consistently highlight responsive communication, virtual meeting cadence, transparency, and a collaborative working style across multiple independent reviews. The glass manufacturer's Head of R&D specifically rated communication top-notch, and the data services engagement praised pricing and overhead transparency as distinguishing traits.
Reliability
MixedThe majority of engagements conclude with stable, deployed deliverables and positive product outcomes. One significant outlier—a monitoring solutions firm that rated quality and cost at 2.0 and schedule at 1.0—cited unresolved issues and unmet expectations over a two-year engagement, introducing a meaningful reliability concern.
Client satisfaction & outcomes
StrongTangible outcomes are documented across multiple engagements, including a significant increase in BI data volume delivered to an asset management client via AWS Quicksight, 3,000 quality audio recordings for an AR project, and an ML QA automation system delivered to a 10,000-plus-employee electric utility. Willingness-to-refer scores are predominantly 5.0.