LatentView Analytics
Publicly traded (NSE) Chennai analytics firm, ~1,700 people, extending into agentic AI.
Founded 2006 | Chennai, India | 1,001–5,000 employees | Last updated: August 2026
data-analytics-agentsworkflow-integrationenterprise-automation
What is LatentView Analytics?
LatentView Analytics was founded in 2006 by Venkat Viswanathan and Pramad Jandhyala, is headquartered in Chennai, India, publicly traded on the NSE, and has approximately 1,700 employees across six continents. One of the world's largest and fastest-growing digital analytics firms, it applies its existing data science and analytics practice to agentic AI, giving buyers a publicly disclosed financial profile that most agentic AI vendors of similar size don't offer.
LatentView Analytics was founded in 2006 and is headquartered in Chennai, India. The firm employs 1,001–5,000 people and works primarily with clients in Financial Services, Retail & E-commerce, Technology & SaaS, Manufacturing sectors. Its primary differentiator is: Publicly traded (NSE) status gives buyers financial transparency uncommon among firms of similar scale in this niche..
LatentView Analytics tech stack and services
PythonLangChainAWSAzureDatabricksSnowflake
| Service area | Details |
|---|---|
| Building analytical agents that autonomously scan large datasets for business insight | Available for Financial Services, Retail & E-commerce, Technology & SaaS, Manufacturing clients |
| Enterprises wanting a publicly disclosed vendor for financial due diligence | Available for Financial Services, Retail & E-commerce, Technology & SaaS, Manufacturing clients |
| Extending an existing analytics engagement with agentic automation | Available for Financial Services, Retail & E-commerce, Technology & SaaS, Manufacturing clients |
LatentView Analytics use cases
Short answer: LatentView Analytics is best suited for buyers wanting agentic AI from a publicly traded analytics firm with disclosed financials and global delivery scale..
| Use case | Industries | Approach |
|---|---|---|
| Building analytical agents that autonomously scan large datasets for business insight | Financial Services, Retail & E-commerce | Python, LangChain |
| Enterprises wanting a publicly disclosed vendor for financial due diligence | Financial Services, Retail & E-commerce | Python, LangChain |
| Extending an existing analytics engagement with agentic automation | Financial Services, Retail & E-commerce | Python, LangChain |
LatentView Analytics pricing
Short answer: LatentView Analytics uses a retainer, dedicated team pricing approach. Minimum engagement starts at Not published.
| Engagement model | Typical range | Best for |
|---|---|---|
| Retainer | Monthly rate; not public | Ongoing AI engineering |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
LatentView Analytics does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
LatentView Analytics pros and cons
| Advantages | Things to consider |
|---|---|
| +Publicly traded (NSE) status gives buyers disclosed financial transparency | -Agentic AI is a newer application of a longer-standing analytics practice |
| +Two decades of digital analytics history since 2006 | -Minimum engagement figures are not published, requiring direct sales contact for early budgeting |
| +~1,700 employees across six continents gives substantial delivery bench depth | -Public case studies emphasize analytics broadly more than agent-specific outcomes |
| +Existing data science foundation feeds directly into agentic analytical use cases |
LatentView Analytics vs alternatives
How LatentView Analytics compares to the other top Agentic AI companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Vstorm | Buyers wanting a company whose entire practice is... | First AI consultancy accepted into the Agentic AI Foundation, with a named proprietary delivery framework (TriStorm) and standardized AGENTS.md documentation. | 4.6 | Full comparison |
| Tensorway | Companies that want a working agentic AI MVP... | Graph-based memory for multi-step reasoning plus a one-month path to a production MVP, without a platform overhaul. | 4.5 | Full comparison |
| Stride Consulting | Companies that want an autonomous agent to reason... | A named, demonstrable proprietary agent (the '100x agent') that autonomously maps, documents, and refactors legacy monoliths and generates its own tests. | 4.4 | Full comparison |
| Tribe AI | Enterprises wanting frontier-model expertise matched to their specific... | A platform-plus-vetted-network model that staffs each engagement with engineers matched to the specific AI use case. | 4.4 | Full comparison |
| Neurons Lab | Regulated financial-services organizations wanting agentic AI delivered by... | AWS Advanced Tier partner status with named financial-institution delivery experience at a boutique headcount. | 4.3 | Full comparison |
| RTS Labs | Mid-market and enterprise teams that have an AI... | Architecture-and-guardrails focus aimed specifically at the pilot-to-production gap, not just initial prototyping. | 4.2 | Full comparison |
| Grid Dynamics | Fortune 1000 enterprises that want agentic AI delivered... | Public-company scale (Nasdaq: GDYN) combined with an explicit, named agentic AI practice. | 4.1 | Full comparison |
| MathCo | Enterprises wanting agentic AI from a dual-headquartered US/India... | Genuine dual headquarters (Chicago and Bangalore, not just a sales office over an offshore delivery center) at ~2,000-person scale. | 4.1 | Full comparison |
| Centific | Enterprises wanting agentic AI built on top of... | An AI data foundry specialization — data pipeline and curation infrastructure for training and deploying AI at scale — feeding directly into agentic AI delivery. | 4.0 | Full comparison |
| Markovate | Product teams that already have a generative-AI roadmap... | Generative AI and LLM development as the core practice, with agent work built as a natural extension rather than a separate offering. | 4.0 | Full comparison |
| Azumo | US companies that want nearshore-priced engineering with named... | Explicit, named production experience with LangGraph, CrewAI, and Microsoft AutoGen for multi-agent orchestration. | 4.0 | Full comparison |
| Accenture | Large multinational enterprises needing agentic AI embedded into... | Unmatched global scale and named strategic partnerships (OpenAI, Microsoft/Avanade) for enterprise-wide agentic AI rollouts. | 4.0 | Full comparison |
| Cognizant | Large regulated enterprises needing agentic AI delivered as... | Enterprise-scale AI-led automation (Cognizant Neuro) backed by a 340,000-person global delivery organization. | 3.9 | Full comparison |
| IBM Consulting | Large enterprises already using or considering IBM's watsonx... | Combines its own agent orchestration platform (watsonx Orchestrate) with enterprise consulting and implementation at global scale. | 3.9 | Full comparison |
| Kanerika | Organizations that want agentic AI built on top... | Data-integration and analytics heritage means agents are built directly on top of governed data pipelines, not bolted on separately. | 3.9 | Full comparison |
| Master of Code Global | Brands that need customer-facing conversational agents built by... | Twenty years of conversational AI and chatbot delivery history predating the current agentic AI wave. | 3.9 | Full comparison |
| Matellio | Enterprises that want agentic AI folded into a... | Combines AI/agent development with broader enterprise cloud application engineering under one roof. | 3.8 | Full comparison |
| Deviniti | Enterprises already on the Atlassian ecosystem that want... | Two decades of enterprise systems-integration work, including deep Atlassian-ecosystem expertise, applied to agent workflow integration. | 3.8 | Full comparison |
| Azilen Technologies | Enterprises wanting a full spectrum of agent complexity,... | Covers the full agent complexity spectrum — single-task through multi-agent architectures — under one product-engineering practice. | 3.8 | Full comparison |
| N-iX | Large enterprises that want agentic AI delivered alongside... | Scale (2,400+ engineers) and a two-decade track record across cloud, data, and embedded systems, with AI/agent work layered on top. | 3.8 | Full comparison |
| Innowise | Enterprises wanting agentic AI bundled with large-scale custom... | Full-cycle software development scale (3,500+ engineers) applied to agentic AI as an extension of a broad existing practice. | 3.7 | Full comparison |
| Netguru | Buyers wanting design and engineering bundled under a... | Bundles product design and engineering under one contract, avoiding the separate UX vendor gap common with AI-only specialists. | 3.7 | Full comparison |
| Ideas2IT | Enterprises wanting agentic AI from a mid-large product... | Product engineering scale (800+ employees) combined with an explicit AI-and-innovation practice positioning. | 3.7 | Full comparison |
| EffectiveSoft | Enterprises wanting agentic AI from a long-established custom... | Quarter-century of enterprise custom software delivery history combined with a dedicated, named agentic AI development service line. | 3.7 | Full comparison |
| *instinctools | Fortune 500 and large enterprise clients wanting agentic... | A quarter-century of engineering history serving Fortune 500 clients, with dual German and US headquarters for transatlantic delivery. | 3.7 | Full comparison |
| Signity Solutions | Cost-conscious buyers wanting multi-agent business-process automation from an... | Explicit specialization in multi-agent collaborative systems for business process optimization at an India-based cost point. | 3.6 | Full comparison |
| LeewayHertz | Enterprises wanting multi-agent system design with deep ERP/CRM... | Deep multi-agent architecture and orchestration-framework selection experience, now combined with The Hackett Group's enterprise consulting network post-acquisition. | 3.6 | Full comparison |
| Softermii | Product teams wanting agentic AI folded into a... | Full-cycle web and mobile application development discipline applied to agent-powered product features. | 3.6 | Full comparison |
| DevCom | Companies wanting agentic AI handled with the same... | Full-lifecycle software delivery discipline — planning through production support — applied to agentic AI projects. | 3.6 | Full comparison |
| Intuz | Budget-conscious teams wanting production-grade multi-agent systems with real... | Named production experience across four agent frameworks (LangGraph, CrewAI, AutoGen, n8n), including observability and guardrails as standard. | 3.6 | Full comparison |
| Cogniteq | Cost-conscious buyers wanting a boutique European team for... | Boutique full-cycle development shop with two decades of Baltic-region delivery history at a lower cost base than Western European or US firms. | 3.6 | Full comparison |
| Codebridge Technology | Teams already running a .NET or web stack... | .NET and web development specialization applied to agentic AI, aimed at teams already standardized on that stack. | 3.6 | Full comparison |
| Riseup Labs | Startups and budget-constrained teams needing a lower-cost entry... | South Asian cost base combined with 15+ years of IT services history, aimed at budget-conscious agent projects. | 3.6 | Full comparison |
| Uvik Software | Smaller teams and startups that want senior Python... | Python-and-Django engineering depth carried directly into AI and agent development, at boutique scale. | 3.6 | Full comparison |
LatentView Analytics FAQ
What is LatentView Analytics?
LatentView Analytics was founded in 2006 by Venkat Viswanathan and Pramad Jandhyala, is headquartered in Chennai, India, publicly traded on the NSE, and has approximately 1,700 employees across six continents. One of the world's largest and fastest-growing digital analytics firms, it applies its existing data science and analytics practice to agentic AI, giving buyers a publicly disclosed financial profile that most agentic AI vendors of similar size don't offer.
How much does LatentView Analytics charge?
LatentView Analytics uses retainer, dedicated team pricing. Minimum engagement starts at Not published. A discovery call is required to get project-specific quotes.
What tech stack does LatentView Analytics use?
LatentView Analytics works with Python, LangChain, AWS, Azure, Databricks, Snowflake. Primary industries served include Financial Services, Retail & E-commerce, Technology & SaaS, Manufacturing.
Is LatentView Analytics right for enterprise?
Buyers wanting agentic AI from a publicly traded analytics firm with disclosed financials and global delivery scale.. 1,001–5,000 team size. Key consideration: Agentic AI is a newer application of a longer-standing analytics practice.
What are the best LatentView Analytics alternatives?
The best alternatives to LatentView Analytics depend on your use case. Top options are:
- Vstorm: first ai consultancy accepted into the agentic ai foundation, with a named proprietary delivery framework (tristorm) and standardized agents.md documentation.
- Tensorway: graph-based memory for multi-step reasoning plus a one-month path to a production mvp, without a platform overhaul.
- Stride Consulting: a named, demonstrable proprietary agent (the '100x agent') that autonomously maps, documents, and refactors legacy monoliths and generates its own tests.
Compare LatentView Analytics with other Agentic AI companies
LatentView Analytics vs Vstorm LatentView Analytics vs Tensorway LatentView Analytics vs Stride Consulting LatentView Analytics vs Tribe AI LatentView Analytics vs Neurons Lab LatentView Analytics vs RTS Labs LatentView Analytics vs Grid Dynamics LatentView Analytics vs MathCo LatentView Analytics vs Centific LatentView Analytics vs Markovate LatentView Analytics vs Azumo LatentView Analytics vs Accenture LatentView Analytics vs Cognizant LatentView Analytics vs IBM Consulting LatentView Analytics vs Kanerika LatentView Analytics vs Master of Code Global LatentView Analytics vs Matellio LatentView Analytics vs Deviniti LatentView Analytics vs Azilen Technologies LatentView Analytics vs N-iX LatentView Analytics vs Innowise LatentView Analytics vs Netguru LatentView Analytics vs Ideas2IT LatentView Analytics vs EffectiveSoft LatentView Analytics vs *instinctools LatentView Analytics vs Signity Solutions LatentView Analytics vs LeewayHertz LatentView Analytics vs Softermii LatentView Analytics vs DevCom LatentView Analytics vs Intuz LatentView Analytics vs Cogniteq LatentView Analytics vs Codebridge Technology LatentView Analytics vs Riseup Labs LatentView Analytics vs Uvik Software
Last reviewed: August 2026. Verify all details directly with LatentView Analytics before making a decision.