ContextMate
Grounding Your AI in Governed BI Metrics
Make your AI assistants trustworthy
ContextMate is a governed semantic layer accelerator that settles every conflicting metric definition in your BI estate. This ensures your AI assistants stop giving wrong answers that sound right.
Take the guesswork out of every AI answer
Every tool in your BI estate defines metrics (like “revenue”) in its own way. When you connect an AI assistant, it picks whichever it finds first. So, a question gets different answers depending on who asks. Fixing this manually takes months.
ContextMate surfaces every conflict across your BI tools in just 30 minutes. It publishes the definitions your team approves as the only one your AI assistants can use. Every answer traces back to an approved definition, making it reliable.
Take the guesswork out of every AI answer
Every tool in your BI estate defines metrics (like “revenue”) in its own way. When you connect an AI assistant, it picks whichever it finds first. So, a question gets different answers depending on who asks. Fixing this manually takes months.
ContextMate surfaces every conflict across your BI tools in just 30 minutes. It publishes the definitions your team approves as the only one your AI assistants can use. Every answer traces back to an approved definition, making it reliable.
From scattered BI to grounded answers in three steps
Audit
ContextMate connects to your existing BI tools and flags duplicate metrics, naming conflicts, and dead fields across every source.
Standardize
Approve one definition per metric through a governed workflow, documented in an open, portable standard rather than a proprietary format.
Ground
ContextMate publishes the approved definitions into Snowflake or Databricks, then monitors for drift as your estate changes.
Audit
ContextMate connects to your existing BI tools and flags duplicate metrics, naming conflicts, and dead fields across every source.
Standardize
Approve one definition per metric through a governed workflow, documented in an open, portable standard rather than a proprietary format.
Ground
ContextMate publishes the approved definitions into Snowflake or Databricks, then monitors for drift as your estate changes.
Audit
ContextMate connects to your existing BI tools and flags duplicate metrics, naming conflicts, and dead fields across every source.
Standardize
Approve one definition per metric through a governed workflow, documented in an open, portable standard rather than a proprietary format.
Ground
ContextMate publishes the approved definitions into Snowflake or Databricks, then monitors for drift as your estate changes.
Designed for the BI estate you already have
Universal BI Ingestion
ContextMate reads the definitions your teams already built in Looker, Tableau, Power BI, and dbt, so nothing gets rebuilt from raw tables.
Open-Standard Semantic Modeling
Every definition is generated in a portable, standards-based format that travels with you across platforms.
Metric Audit Trail
Every metric traces back to its source file, its original SQL, and the person who approved it.
Secure Deployment
Runs as a native application inside your own account or workspace, so no data or structural logic leaves your environment.
What you gain with ContextMate
Answers Your Business Trusts
Answers Your
Business Trusts
Higher AI Accuracy
Higher AI
Accuracy
Quicker Conflict Visibility
Quicker
Conflict
Visibility
Faster AI Enablement
Faster AI Enablement
Every AI response traces back to a definition a named human approved.
Grounding assistants in approved metrics improves AI accuracy by up to 40%.
See every duplicate and conflicting metric across your BI estate in just 30 minutes.
Cut the time to a trustworthy, AI-ready semantic layer by up to 90%.
Success Stories
Campaign Optimization with Algorithmic Bidding
20%
Surge in net revenue
$10 Million+
Ready to ground your AI in metrics you can trust?
See how ContextMate turns scattered metric definitions into one governed layer.
"*" indicates required fields
Thought Leadership
Rajan Sethuraman
Remadevi Thottathil
Venkat Viswananthan
Prasun Velayudhan
Vivek Singh
Boobesh Ramadurai
Parijat Banerjee
Kaushik Boruah
The New Shift of Global Capability Centers to Innovation Hubs
Global Capability Centers (GCCs) have been an essential part of corporate strategy for decades, offering access to global talent pools that can enhance a company’s organizational capabilities and provide critical support to sustain periods of rapid growth. Traditionally, these centers were designed as a cost-saving option for companies with large-scale operational needs, serving as offshore or nearshore hubs for many services such as finance, IT, and customer service.
READ MOREBack to the Drawing Board: Building India’s Tech Talent Ecosystem
There is high demand and higher supply, yet the two don’t meet for the Indian tech industry. Last year, TCS reported 80,000 vacancies, but the majority of the 1.5 lakh engineering graduates who pass out annually did not suit the job. Similar is the contrast when it comes to the economics of the sector.e
READ MOREA Marathon Of Innovation: 4 AI Technologies To Watch In 2025
Some might agree that the AI advancements in 2024 looked like a page from a science fiction novel. Those great strides have set a precedence for something far more pivotal. In 2025, AI will fundamentally alter how you operate, make decisions, and connect with customers. While it is critical to think bigger and act bolder, Venkat Viswanathan emphasizes the importance of sticking to the most elemental principle—achieving meaningful, scalable impact. Read more
READ MORE3 Core Principles to Drive ROI from GenAI Deployments
Gartner predicts that by 2025, at least 30% of GenAI projects will be abandoned mainly due to poor data quality, and failure to deliver business value.
However, another Gartner survey highlights that successful GenAI deployments have led to impressive outcomes: 15.8% revenue growth, 15.2% cost savings, and 22.6% productivity gains. So, what sets apart the companies that succeed with GenAI from those that fall short?
Vivek Singh, Growth Head – Hi-Tech, outlines three key principles to help businesses evaluate, select, and enable GenAI use cases—ensuring risk management, cost control, and transformative results.
READ MOREChanging How We Think About GenAI in the Boardroom: Navigating Short and Long-Term ROI
The hype around GenAI is undeniable, with companies rapidly adopting it. But the question on every boardroom's mind is: when will we see a return on our investment? The answer is more nuanced than simply calculating costs.
Firstly, we must reframe how we perceive ROI in the context of AI/GenAI. While the allure of immediate, transformative results is strong, these technologies are still in their early stages.
Read this article where Prasun Velayudhan, Associate Director at LatentView Analytics, shares insights on what you must focus on for a successful AI/GenAI transformation.
READ MOREWhat if GenAI doesn’t need a funnel at all?
It’s a bold question, but one that is becoming increasingly relevant. In a recent MarketingProfs article, Boobesh R., Vice President, LatentView Analytics, explains how autonomous AI agents are dismantling traditional, staged funnels and replacing them with dynamic, agent-led journeys.
READ MOREAI is already in 84% of US health insurance firms, so why is consumer trust still falling?
While the tech is present, the strategy often isn't.
In his recent Forbes article, Parijat Banerjee, Business Head – Financial Services, shares how insurers can use AI and analytics to reduce fraud, personalize experiences, and support value-based care, without turning AI into a “black box.”
READ MOREEver wondered what goes on behind the scenes when you book a stay at a hotel?
Behind those seamless, perfect-looking screens is a whole system trying to keep up with shifting prices, changing demand, and rising expectations.
In this article published on Hospitality Technology, Kaushik Boruah, Business Head - CPG & Hospitality, LatentView, shares how AI is reshaping the hospitality experience.
READ MORE
The New Shift of Global Capability Centers to Innovation Hubs
Global Capability Centers (GCCs) have been an essential part of corporate strategy for decades, offering access to global talent pools that can enhance a company’s organizational capabilities and provide critical support to sustain periods of rapid growth. Traditionally, these centers were designed as a cost-saving option for companies with large-scale operational needs, serving as offshore or nearshore hubs for many services such as finance, IT, and customer service.
AI is already in 84% of US health insurance firms, so why is consumer trust still falling?
While the tech is present, the strategy often isn’t.
In his recent Forbes article, Parijat Banerjee, Business Head – Financial Services, shares how insurers can use AI and analytics to reduce fraud, personalize experiences, and support value-based care, without turning AI into a “black box.”
What if GenAI doesn’t need a funnel at all?
It’s a bold question, but one that is becoming increasingly relevant. In a recent MarketingProfs article, Boobesh R., Vice President, LatentView Analytics, explains how autonomous AI agents are dismantling traditional, staged funnels and replacing them with dynamic, agent-led journeys.
3 Core Principles to Drive ROI from GenAI Deployments
Gartner predicts that by 2025, at least 30% of GenAI projects will be abandoned mainly due to poor data quality, and failure to deliver business value.
However, another Gartner survey highlights that successful GenAI deployments have led to impressive outcomes: 15.8% revenue growth, 15.2% cost savings, and 22.6% productivity gains. So, what sets apart the companies that succeed with GenAI from those that fall short?
Vivek Singh, Growth Head – Hi-Tech, outlines three key principles to help businesses evaluate, select, and enable GenAI use cases—ensuring risk management, cost control, and transformative results.
Changing How We Think About GenAI in the Boardroom: Navigating Short and Long-Term ROI
The hype around GenAI is undeniable, with companies rapidly adopting it. But the question on every boardroom’s mind is: when will we see a return on our investment? The answer is more nuanced than simply calculating costs.
Firstly, we must reframe how we perceive ROI in the context of AI/GenAI. While the allure of immediate, transformative results is strong, these technologies are still in their early stages.
Read this article where Prasun Velayudhan, Associate Director at LatentView Analytics, shares insights on what you must focus on for a successful AI/GenAI transformation.
A Marathon Of Innovation: 4 AI Technologies To Watch In 2025
Some might agree that the AI advancements in 2024 looked like a page from a science fiction novel. Those great strides have set a precedence for something far more pivotal. In 2025, AI will fundamentally alter how you operate, make decisions, and connect with customers. While it is critical to think bigger and act bolder, Venkat Viswanathan emphasizes the importance of sticking to the most elemental principle—achieving meaningful, scalable impact.
Read more
Back to the Drawing Board: Building India’s Tech Talent Ecosystem
There is high demand and higher supply, yet the two don’t meet for the Indian tech industry. Last year, TCS reported 80,000 vacancies, but the majority of the 1.5 lakh engineering graduates who pass out annually did not suit the job. Similar is the contrast when it comes to the economics of the sector. While the revenue of IT companies has recorded steady growth, entry-level salaries have not kept pace with compensation starting at Rs4 lakh per annum.