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service
Data quality: Editorially Reviewed
Google Cloud
Travel & hospitality
Language (LLM / NLP)
Financial services
Databricks
Data engineering & preparation
AI strategy & roadmap consulting
Managed AI operations
Staff augmentation
Model monitoring
Industrial & manufacturing
Implementation & integration
Predictive / classical ML
Personalization
Consumer goods
Demand planning
Healthcare & life sciences
Technology & telecommunications
ML lifecycle & data
Snowflake
Amazon Web Services
Salesforce
AI strategy & leadership
Azure
Data strategy & engineering
Retail & e-commerce
Agentic / autonomous
Forecasting
Enterprise
Optimization & decision intelligence

Tredence

Implementation & integration

Offered by Tredence Inc.

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Overview

Tredence provides agentic and generative AI, data engineering and modernization, MLOps and LLMOps, data science, and digital engineering. Domain offerings include supply chain management and customer experience analytics, and the firm also advises on and builds global capability centres. Technology partners named include OpenAI, Anthropic, Databricks, Google Cloud, Microsoft, Snowflake, AWS, LiveRamp, Salesforce and NielsenIQ. Industries covered are retail, CPG, telco/media/tech, travel and hospitality, industrials, financial services, healthcare and life sciences. Its contact page lists offices in North America, India, Australia and EMEA without designating a single headquarters.

Pricing model
On request
Regions served
North America, Europe, Asia-Pacific (APAC), Middle East
Categories
Google Cloud, Travel & hospitality, Language (LLM / NLP), Financial services, Databricks, Data engineering & preparation, AI strategy & roadmap consulting, Managed AI operations, Staff augmentation, Model monitoring, Industrial & manufacturing, Implementation & integration, Predictive / classical ML, Personalization, Consumer goods, Demand planning, Healthcare & life sciences, Technology & telecommunications, ML lifecycle & data, Snowflake, Amazon Web Services, Salesforce, AI strategy & leadership, Azure, Data strategy & engineering, Retail & e-commerce, Agentic / autonomous, Forecasting, Enterprise, Optimization & decision intelligence
Last updated
7 October 2026
Published
7 October 2026

Use cases

ML lifecycle & data
Model monitoring
Demand planning
Personalization
Forecasting

Data sources & provenance

Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.

Data quality
Data quality: Editorially Reviewed
Primary source
tredence.com
Sources cited
2
Last reviewed
6 October 2026
Last updated
7 October 2026

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