Our services are designed for regulated and operationally complex industries, including healthcare, BFSI, insurance, manufacturing, logistics, and energy.
Trusted by Leading Organizations
Recognized by ISG Provider Lens® 2025
ISG — a global AI-centered technology research and advisory firm trusted by 75 of the world's top 100 enterprises — independently evaluated our Advanced Analytics & AI capabilities.
What This Recognition Means for You
ISG Provider Lens® is the only service provider evaluation combining empirical, data-driven research with the real-world experience of ISG's global advisory team. Enterprises and ISG advisors use these reports to guide sourcing decisions.
A Product Challenger designation recognizes a provider with a highly attractive service portfolio — evaluated on breadth, depth, technology quality, strategy, and innovation — independently verified, at no cost to the evaluated firm.
Gowtham Kumar Sampath
Assistant Director & Principal Analyst, ISG Research
Chetu continues to demonstrate a grounded, engineering-driven approach to Advanced Analytics and AI, blending multimodal intelligence, regulatory rigor, and practical automation through frameworks like Track2AI and its on-prem Llama assistant. Its execution depth and repeatable design ethos — with the ability to embed agentic logic, real-time retraining, and responsible governance — position it as a credible enterprise partner for Data and AI services.
Watch the Video to See What ISG Says About Our AI & Analytics Capabilities
Gowtham Kumar Sampath, Assistant Director and Principal Analyst at ISG, discusses our practical AI capabilities, engineering-led delivery approach, and why our enterprise-ready solutions were recognized in the 2025 study.
Explore the full ISG evaluation and see why our approach stands out in real enterprise environments.
The Challenges Your Enterprise Is Navigating
ISG's 2025 research across hundreds of enterprises identifies the structural barriers slowing AI and analytics value realization — and why the right partner matters.
Challenge 01
Data Usability Is the #1 Barrier
Inconsistent taxonomies, fragmented data ownership, and poor lineage prevent AI models from interpreting data reliably — ranked as the top enterprise obstacle ahead of integration, scalability, and security.
Challenge 02
ROI Is Hard to Prove
Nearly 25% of enterprises feel they lag peers in AI value outcomes. Without clearly defined business goals, success metrics, and upfront value frameworks, AI pilots often stall in isolated pockets with no clear path to measurable financial impact.
Challenge 03
Application Estate Fragmentation
Large enterprises manage an average of 1,778–1,933 applications, including legacy software and modern business systems, yet fewer than one-third have consistent data architecture standards — making cross-domain governance a serious challenge.
Challenge 04
Security & Compliance Risks Slow Scale
Nearly 40% of organizations limit data retention due to security risks. As AI regulations evolve, enterprises need partners who embed governance and compliance controls from the outset.
Challenge 05
Lifecycle Management Gaps
MLOps, drift monitoring, and automated retraining capabilities vary widely across providers and deployments — particularly in regulated environments where operational predictability is non-negotiable.
Challenge 06
Specialized AI Talent Shortage
Shortages of hybrid technical-business AI roles remain a top challenge through 2026. These gaps slow modernization programs and limit enterprise readiness for self-service analytics.
Challenge 07
AI Literacy & Organizational Readiness
Limited AI literacy across business, operational, and leadership teams often slows adoption, reduces trust in AI-led decisions, and weakens the impact of self-service analytics and enterprise transformation initiatives.
How We Deliver — Validated by ISG
ISG's independent evaluation identified three core capability pillars that differentiate our delivery approach in the Advanced Analytics & AI market.
Industry-Driven AI Delivery
Our analytics and AI capabilities are anchored in solutions built around the operational and regulatory demands of each industry — not generic platforms. This alignment with real workflows enables AI that fits naturally within enterprise operations.
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Healthcare: Diagnostic systems combining image analysis with privacy-aware data handling
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Insurance & BFSI: Multi-agent intake, fraud detection & adjudication flows
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Manufacturing: Multi-agent intake, fraud detection & adjudication flows
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+40% improvement in diagnostic triage speed via AI-based image evaluation
Multi-Modal & Agentic Architectures
We design AI architectures aligned to your enterprise's security posture and workflow demands — integrating text analysis, computer vision, structured data models, and multi-agent orchestration. We assemble multi-component systems with governance and workflow-specific logic built in, not predefined platforms.
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LLMs & SLMs deployable across secure on-premises, hybrid cloud, and distributed enterprise data environments
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Human-in-the-loop validation checkpoints for full auditability
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Data governance and accuracy checks at every layer
Internal Accelerators Strengthening Delivery
We enhance execution through internal assets that improve development speed and consistency — including a Llama-based code assistant and governance enablement tooling — without ever compromising client confidentiality.
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Track2AI™ — our structured, repeatable AI adoption framework
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On-prem Llama assistant accelerates development while protecting data privacy
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Structured data validation and compliance practices built into every engagement
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+40% shorter development cycles via secure LLM code assistant
Analytics & AI in Action
Case Study 1
AI-Powered Eye Pathology Detection & Recommendation System
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Developed an AI-powered diagnostic platform using computer vision and ML models for automated eye pathology screening
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Enabled real-time image analysis and segmentation for faster clinician decision-making
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Reduced diagnostic workflow time by up to 70% through intelligent automation
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Improved patient engagement by nearly 60% with guided digital experiences
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Delivered faster, more accurate diagnostic recommendations with reduced manual intervention
Case Study 2
AI-Powered Field Data Collection & Management Platform
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Built a centralized cloud-based AI validation platform for field and office teams
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Integrated GIS, AI, and machine learning for real-time data verification
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Enabled predictive insights and operational intelligence across energy workflows
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Improved data accuracy, compliance, and asset visibility through automated validation
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Delivered scalable, real-time dashboards for enterprise decision support
What Advanced Analytics & AI Can Deliver
When analytics and AI are properly implemented — with governed pipelines, clean data foundations, and lifecycle management — organizations see tangible results.
Faster, Better Decisions
Operational decision intelligence, forecasting accuracy, and workflow automation that improve speed and consistency across business units.
Measurable ROI
Value tracing, KPI frameworks, and outcome-linked delivery — so every analytics and AI investment is tied to cost savings, revenue growth, and productivity from day one.
Compliance-Ready AI
Auditability, explainability, and regulatory governance are built into every deployment — essential for healthcare, BFSI, and manufacturing environments.
Operational Efficiency
Automate processes, reduce manual review burden, and streamline analytics pipelines to free your teams for higher-value strategic work.
Scalable Data Foundations
Modern data architectures, such as lakehouse architectures, semantic layers, and lineage frameworks — built to grow with your organization's AI ambitions.
Production-Grade AI
MLOps, drift monitoring, and machine learning model deployment pipelines that ensure models perform reliably in production — not just during the pilot phase.
Deep Domain Expertise Across Regulated Verticals
Our ISG-recognized sweet spot is in environments where data risk, operational complexity, and model accountability are highest.
Healthcare
Diagnostic AI, image analysis, EHR analytics, clinical decision support
BFSI & Insurance
Fraud detection, claims automation, adjudication flows, risk analytics
Manufacturing
Predictive maintenance, sensor analytics, reliability planning, IoT-driven AI
Logistics
Real-time visibility, predictive alerting, supply chain optimization
Our End-to-End AI Implementation & Advanced Analytics Services
A full lifecycle of end-to-end AI services covering every phase of your analytics and AI journey — from data modernization through production AI.
Strategy & Consulting
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Analytics & AI strategy development
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Use case identification & prioritization
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Data readiness assessments
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ROI & value definition frameworks
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Technology roadmapping
Data Modernization
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Data lake & lakehouse implementation
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Hybrid cloud data migration & integration
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Data pipeline & DataOps engineering
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Metadata & lineage management
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Master data management (MDM)
AI & Machine Learning
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Machine learning model development & deployment
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Generative AI & language model integration (LLM / SLM)
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Agentic AI architectures
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MLOps, LLMOps & SLMOps lifecycle management
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Computer vision & NLP solutions
Where We're Headed
ISG's report highlights our forward roadmap — focused on strengthening scalability, repeatability, and governance maturity across our analytics and AI portfolio.
1
LLMOps & SLMOps Automation
Advancing telemetry, drift monitoring, and rollback capabilities to ensure production AI models stay reliable over time.
2
Track2AI™ Expansion
Evolving Track2AI™ into modular, client-facing adoption toolkits tailored for specific industry use cases and maturity levels.
3
Enhanced Lineage & Metadata
Increasing modernization reliability through automated lineage tracking and metadata governance tooling.
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Hyperscaler & ISV Partnerships
Strengthening strategic partnerships with hyperscalers and ISVs to expand cloud, AI, and ecosystem co-delivery capabilities.
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Outcome-Driven Benchmarks
Building standardized benchmarks that quantify analytics and AI value realization for clients across verticals and use cases.
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Explainability & Compliance Scale
Extending governance frameworks to support AI explainability and regulatory compliance at enterprise scale.
What Our Clients Say
“The regular updates have been helpful, and the way the team explained their machine learning approach — especially the reasoning behind the selected algorithms — made the process much easier for us to follow. The visibility into imputed property data has been a valuable addition.”
— David McMullan, Senior Software Engineer, Schneider Geospatial
“Thank you for your hard work in keeping Connect updated. The last-minute and standalone tasks have been especially important, and I truly appreciate the team’s diligence in getting them completed quickly.”
— Tara Brown, Enterprise Systems Director, CGRS Inc.
Frequently Asked Questions
We build governance, lineage, explainability, human-in-the-loop validation, and security controls into every engagement to support compliance-ready AI deployments.
Yes. We support on-premises, public cloud, and hybrid cloud environments, including deployments across major hyperscalers and enterprise-owned infrastructure.
Yes. Our services cover strategy, data modernization, model development, deployment, MLOps, LLMOps, and lifecycle governance.
We define outcome-linked KPIs, value benchmarks, and ROI frameworks upfront so each engagement is tied to measurable business outcomes.
Yes. We help enterprises modernize fragmented data estates, integrate legacy systems, and build scalable data foundations for production AI.
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