Modern systems aren’t a luxury; they’re the backbone of tomorrow’s healthcare

Every denied claim in healthcare is more than just a piece of paperwork; it represents delayed revenue, wasted resources, and added stress for operational teams. For many practices, denials pile up faster than they can be processed, creating bottlenecks that affect cash flow and overall efficiency. Understanding why claims are denied and addressing the problem proactively is no longer optional — it’s essential for a resilient and profitable
healthcare system.

CrewAI vs Semantic Kernel: Decoding Agentic AI for Healthcare

We’re entering a new era of healthcare AI—one where technology doesn’t just assist but actively takes initiative. Agentic AI is starting to make waves in the industry. These smart agents can handle complex medical tasks step by step, reason through challenges, and choose the next best action—all with little need for constant human direction.

Transforming Healthcare Intake Forms with Agentic AI Power

In healthcare, patient intake forms are often the first step in a patient’s journey, yet they are a common source of inefficiency. These forms gather essential information including personal demographics, insurance details, medical history, consent agreements, and pre-visit questionnaires. While they may seem straightforward, errors and delays at this stage can ripple throughout the revenue cycle, causing claim denials, delayed payments, increased administrative burden, and frustrated patients.

Building GenAI Use Cases in HealthTech: Playbook to Production, Not Just POCs

At 10decoders, we’ve seen a clear adoption pattern. Instead of fragmented pilots, healthtech leaders need a structured playbook that balances quick wins with long-term scalability—while meeting HIPAA and regulatory requirements.

In this blog, we present a 7-step playbook that shows how healthcare enterprises can start with retrieval-based assistants and scale all the way to personalized, compliant, and decision-ready AI systems.

AI Agents in Drug Discovery- Turning Science Fiction into Reality

The pharmaceutical industry has long been plagued by time-consuming and costly drug discovery processes. Traditional methods take years to develop a single viable drug, with billions of dollars invested in research and development. However, the emergence of AI agents, a new paradigm of artificial intelligence capable of autonomous decision-making and action-taking, is reshaping the landscape of drug discovery. AI agents are revolutionizing how new medicines are identified, tested, and optimized. And most importantly, AI in drug discovery is transforming the way researchers approach pharmaceutical breakthroughs, reducing inefficiencies and enhancing precision.

How is Explainable AI Revolutionizing Sanctions Screening

In today’s interconnected global economy, financial institutions are at the forefront of combating financial crime, a task that grows more challenging with each passing day. Governments and international bodies rely heavily on sanctions as a powerful tool to deter illegal activities and uphold global security.

The AI Advantage- Preparing for a Future Driven by Innovation

In the not-so-distant past, artificial intelligence (AI) was seen as a futuristic concept, often associated with science fiction. Fast forward to today, and AI is not only a reality but an integral part of our daily lives. From voice-activated assistants to personalized recommendations, AI has permeated various aspects of our existence. But what’s next? How AI is shaping the future of business? How can AI become truly accessible to everyone, everywhere? Let’s explore the transformative potential of AI for all.

Peering Into AI Insights- Rise of Explainable Artificial Intelligence

In a world where health tech is booming and innovations seem endless, a large part of our population is still waiting for basic, consistent care—rural patients with chronic conditions. While urban hospitals march ahead with digital dashboards, AI predictions, and teleconsultations, rural patients struggle with a lack of monitoring, rare specialist access, and reactive treatment.

The real question is: How do we bring chronic care to the last mile?

This blog dives into the chronic care crisis in rural regions, the burden it places on hospitals, and how IoT integration paired with intelligent alerting can finally flip the script from reactive to proactive care.

RAG’s Impact on AI’s Roadmap to Riches and Rewards

Large Language Models (LLMs) are a cornerstone of natural language processing (NLP). These AI algorithms leverage deep learning techniques and vast datasets to understand, summarize, and generate text-based content. From conversational answering to text generation and classification, LLMs are reshaping how we interact with information. ChatGPT is a prime example, showcasing the potential to generate human-like responses. However, challenges remain, particularly in ensuring these models have access to up-to-date and accurate information—a gap that Retrieval-Augmented Generation (RAG) AI aims to bridge.

RAG Magic- Transforming How We Find and Use Information

The way we search for information is evolving rapidly, driven by advancements in technology that are transforming the very fabric of how businesses manage and utilize their data. From the early days of manual folder structures to the latest in retrieval-augmented generation (RAG), the journey has been marked by significant milestones that have each added layers of sophistication to the search process. As we stand on the brink of a new era, it’s clear that RAG technology is set to revolutionize our search experiences in ways previously unimaginable. Integrating concepts like AI in information systems and machine learning in search, RAG is paving the way for innovative solutions.

Dynamizing Biopharma with Gen AI’s Transformative Impact

Navigating the intricate terrain of biopharmaceuticals, the incorporation of Generative AI signals a revolutionary shift in the development, production, and commercialization of novel treatments. While the advantages are evident, leveraging Gen AI in biopharma, characterized by a convoluted value chain and rigorous regulatory oversight, poses considerable challenges. This exploration into the transformative capabilities of Gen AI sheds light on how 10decoders is spearheading the evolution of biopharma.

Ethical Considerations in Generative AI: Addressing Bias and Fairness

In the realm of artificial intelligence, particularly within the groundbreaking field of Generative AI, the journey towards innovation is accompanied by the responsibility to uphold ethical standards. As we delve into the complex web of algorithms and data, it becomes imperative to critically examine the ethical considerations, with a specific focus on addressing bias and ensuring fairness. In this blog, we will navigate the intricate landscape of bias and fairness in generative AI, shedding light on the challenges, implications, and strategies to ensure an ethical and inclusive AI future.