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The Lighthouse: Edition 1 | July 2025
Navigating what’s next in AI, technology, business and everything beyond.
About this newsletter
This edition provides the blueprint for bridging the AI chasm, moving from isolated labs to integrated, value-generating factories.
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The Pilot-to-Profit Gap: Why 85% of AI Projects Never Deliver ROI
The mandate from the board is clear: turn AI potential into P&L impact. Yet most organizations get stuck in “pilot purgatory,” burning capital on experiments that never scale. The challenge isn’t a lack of ideas, but the absence of a production-ready engine. This requires moving beyond just algorithms to a complete operational architecture a repeatable framework for data preparation, model selection, seamless integration with legacy systems, and continuous performance monitoring. The following sections detail how to build this engine, piece by piece.
The Enterprise AI Chasm
Wiring Intelligence into the Enterprise
Fast-Tracking Trust in Regulated Spaces
Building trust and revenue simultaneously is the new benchmark in finance. Leaders are achieving this by embedding AI to make customer onboarding instant and secure. This allows them to eliminate friction, stop fraud before it happens, and deepen relationships through data-driven personalization.
From Insight to Checkout: Intelligence That Sells
The era of reactive retail is ending. We’re seeing front-runners create a single source of truth from their fragmented data streams. This unified view of demand is how they anticipate trends, leading to outcomes like 16% fewer unsold items and a 25% market share gain for their most important brands.
Voices Shaping the Conversation
Altimetrik
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HFS Research
Ready to Bridge YourPilot-to-Profit Gap?
Your AI strategy deserves more than a proof-of-concept. Book a complimentary 30-minute working session with our AI architects to map your specific path to production.
AI Toolkit: Accelerators to Build On
How do we innovate without risking our customer’s data?
In the race to build AI-first solutions, enterprises often run into the same wall: insufficient, biased, or sensitive data. Whether it’s regulatory hurdles, privacy concerns, or sheer lack of volume, these data constraints delay innovation, weaken model performance, and compromise fairness.
But what if enterprises didn’t have to wait for the “perfect” dataset? The answer lies in synthetic data not just as a placeholder, but as a strategic enabler. By generating realistic, diverse, and privacy-preserving datasets, organizations can train, test, and validate AI models with confidence. Synthetic data becomes especially powerful when it’s customizable, scalable, and indistinguishable from real-world data.
By creating a “digital twin” of your dataset. Our Synthetic Data Generator lets you build and test robust AI models using realistic, privacy-safe data. It’s how you accelerate your roadmap by up to 30% while ensuring 100% compliance with regulations like GDPR and CCPA.
Which LLM is truly the best for our specific business needs?
As organizations rush to harness the power of generative AI, they face an increasingly complex question:
Which large language model is right for my business?
With over 200 models in the ecosystem and each differing on performance, latency, safety, cost, and domain fit the process of selecting the “best” LLM can be overwhelming and opaque. Relying on one-size-fits-all comparisons or vendor marketing doesn’t cut it anymore.
What enterprises need is clarity, not complexity.
That’s why leading organizations are shifting from guesswork to intelligent benchmarking. By aggregating quantitative insights from trusted sources like HELM, Vellum, and Chatbot Arena, and evaluating models across 40+ parameters, it’s now possible to align LLM choices with business goals, regulatory needs, and operational constraints.
By moving beyond public leaderboards and comparing models on your terms. Our Benchmarking Dashboard provides a transparent, head-to-head analysis of 200+ models on cost, latency, and performance for your use case, cutting high-stakes evaluation time from weeks to days.
Featured
Conference Spotlight – Governing Data in the
Age of AI
Last week at Zinnov Confluence, our CEO Raj Sundaresan joined a panel on Data Ownership & Accountability. His message was direct: “If governance lags, every AI build risks standing on shifting sand.” From access controls to model observability, Raj outlined the guardrails enterprises must install before scaling GenAI.
Analytics India Magazine projects Altimetrik’s ALTI Lab™ is on a path
to unlock $1 billion in enterprise value through its “production-first” approach.
With the launch of our ALTI Lab™, we’re redefining how enterprises move from AI pilots to production-ready, high-impact solutions. This AIM feature highlights our unique “production-first” approach, emphasizing how ALTI Lab™, with its advanced AI accelerators and robust frameworks, is designed to reduce time-to-value and ensure measurable results for businesses.
To understand more about ALTI Lab™ and our strategy for driving the future of enterprise AI, we invite you to read the full feature:
Altimetrik has been named a Major Contender in Everest Group’s 2025 PEAK Matrix® for BFSI IT Services Specialists.
This recognition reinforces the strength of our AI-first, digital business approach in driving scalable, outcome-based solutions for the banking and financial services sector. From compliance and payments to intelligent onboarding, we’re helping BFS clients modernize faster and deliver measurable value through rapid MVPs and advanced engineering.
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