The patient was admitted to the Critical Care Unit (CCU) at Inamdar Multispeciality Hospital on 1/3/26 under Dr. Amit Mazumdar with a sudden onset of breathlessness and severe oxygen desaturation following the consumption of outside food. She was a high-risk case, with multiple co-morbidities including morbid obesity, diabetes, and multinodular toxic goiter, and was also diagnosed with pneumothorax.

Initial Management (Date: 4/3/26)

An intercostal drainage (ICD) tube was inserted to manage the pneumothorax. The patient was stabilised and maintained on ventilatory support, with a trial on T-piece conducted after initial improvement.

Failed Extubation Attempts (Dates: 5/3/26 / __)

Despite meeting extubation parameters, two separate attempts to wean her off ventilatory support failed due to persistent desaturation, necessitating re-intubation. The inability to sustain spontaneous breathing raised the need for a definitive airway solution.

At this stage, the treating team explained the need for tracheostomy and thyroidectomy to the family. Given the perceived risks associated with thyroid surgery, the relatives initially consented only to tracheostomy, which was considered semi-urgent.

Intraoperative Turning Point (Date of Surgery: 9/3/26)

During surgery at Inamdar Multispeciality Hospital, doctors encountered a critical anatomical challenge. The patient had a massively enlarged thyroid gland extending retrosternally and completely engulfing the trachea, making tracheostomy technically impossible without first removing the thyroid.

This intraoperative finding necessitated an immediate change in surgical plan. The patient’s relatives were counselled again in real time regarding the urgency and inevitability of proceeding with thyroidectomy.

The surgery was led by Dr. Pravin Bhosale, ENT Surgeon, with support from the general surgery team—Dr. Nelson and Dr. Abhijeet Gotkhinde, while the anaesthesia team comprising Dr. Sandeep Patil and Dr. Jyoti Sawant ensured stable intraoperative management.

Following thyroid removal, the team conducted critical intraoperative assessments. The integrity of both recurrent laryngeal nerves was confirmed, the parathyroid glands were preserved, and there was no evidence of tracheomalacia.

Critical Surgical Decision

Based on these findings, the team made a decisive call to avoid tracheostomy and attempt controlled extubation.

Dr. Pravin Bhosale, ENT Surgeon, said, “This was a highly critical case because what appeared to be a routine need for tracheostomy turned into a complex airway emergency inside the operating theatre. The thyroid was massively enlarged and retrosternal, completely engulfing the trachea, leaving no safe option except to change the surgical plan immediately. In such situations, precise judgment, timing, and coordinated teamwork are absolutely crucial to achieving a successful outcome.”

Post-Operative Recovery (Date: 10/3/26)

The patient’s recovery was notably rapid. She required only two days of CCU care post-surgery. Swallowing function was assessed using bedside FEES (Functional Endoscopic Evaluation of Swallowing), following which all supportive lines and tubes, including Ryle’s tube, catheter, and surgical drains, were removed in a phased manner.

Discharge and Outcome (Date of Discharge: 14/3/26)

The patient was discharged in stable condition, marking a successful outcome in what doctors at Inamdar Multispeciality Hospital describe as a rare convergence of airway compromise and endocrine pathology.

Reflecting on her experience, the patient said, “I was struggling to breathe, and it was a very difficult time for my family and me. The doctors explained every step and gave us confidence throughout. I feel grateful to have recovered and to be going home.”

The case involved a multidisciplinary effort, with contributions from Dr. Mulla (Endocrinologist), Dr. Ajinkya Gulave, and Dr. Vrushali (Pulmonologists), along with ICU teams, operation theatre staff, and hospital support departments.

Clinical Significance

Doctors involved in the case emphasised that such outcomes depend heavily on real-time intraoperative judgment, multidisciplinary coordination, and the ability to adapt surgical strategy based on evolving clinical findings.

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BENGALURU: Qlik^®, a global leader in data integration, data quality, analytics, and artificial intelligence, today announced an expanded set of capabilities coming soon in its Qlik Cloud Analytics solution — equipping enterprises with tools to detect anomalies, forecast complex trends, prepare data faster, and take immediate action through embedded decision workflows.

While organizations continue to invest heavily in AI and data, most still struggle to turn insight into impact. Dashboards pile up, but real-time execution remains elusive. Only 26% of enterprises have deployed AI at scale, and fewer still have embedded it into operational workflows. The problem isn’t access to static intelligence — it’s the ability to act on it. Dashboards aren’t decision engines, and predictive models alone won’t prevent risk or drive outcomes. What businesses need is intelligence that anticipates, explains, and enables action, without added tools, delays, or friction.

“Enterprises struggle making intelligence accessible and actionable for their business users,” said Brendan Grady, Executive Vice President and General Manager of Qlik’s Analytics Business Unit. “Too many systems deliver insights and answers after the fact. We’re building something different: a platform where AI detects what matters, surfaces it in context, and lets you act — all within the analytics environment itself.”

With these planned launches, Qlik will be introducing a new layer of intelligence across its platform — one that doesn’t just report what’s happening, but anticipates what’s next and enables action in the moment. Discovery agent, multivariate time series forecasting, write table, and table recipe work in concert to solve a singular problem: how to move from fragmented insight to seamless execution, at scale.

These launches, along with the renaming of Qlik AutoML to Qlik Predict^TM and Qlik Application Automation to Qlik Automate^TM, reflect a broader shift toward more intuitive, outcome-driven experiences across the Qlik platform. Each capability targets a critical enterprise bottleneck — from delayed awareness to inaccurate forecasting, data prep bottlenecks to disconnected workflows — delivering a cohesive solution that closes the gap between data and decisions.

• See what others miss before it’s too late — with the discovery agent. Executives no longer need to manually track business changes or sift through data. Discovery agent continuously scans performance across applications and datasets, automatically surfacing critical risks and opportunities before they intensify. Insights are delivered through a personalized feed that clarifies what’s happening, why it matters, and suggested next steps.
• Forecast reality, not just trends — with multivariate time series forecasting. Built into Qlik Predict (formerly AutoML), this capability moves beyond single-variable projections to model the full complexity of business conditions. By analyzing relationships across interdependent variables — like pricing, campaign activity, seasonality, and economic signals — it delivers sharper forecasts that reflect real-world dynamics. The result: more confident planning, faster scenario testing, and better decisions.
• Annotate and update data live — with a write table. Write table enables users to add context to data records directly in analytics tables, with instant sync across sessions and no reloads required. This capability enhances in-context data review and lays the groundwork for governed writeback into systems like SAP, Salesforce, and Snowflake — part of Qlik’s long-term vision for integrated, action-ready analytics.
• Prep data faster with no code — using a table recipe. Table recipe provides a streamlined, spreadsheet-like experience for preparing single-table datasets — no scripting or complex modeling required. Users can clean, convert, and format data with over 60 visual functions, seeing changes in real time. It empowers non-technical users to prep high-quality data quickly, accelerating the path to reliable insights.

“We’ve spent too much time reacting to what already happened — and not enough time getting ahead of what’s next,” said Olga Garagonich, Lead Manager, Data Visualisation, BT Group. “With these new capabilities in Qlik, we’ll be able to catch issues earlier, forecast more accurately, and take action — all without disconnected workflows or delays. That’s a game-changer for how we operate.”

Together, these capabilities transform Qlik from a system of insight into a system of execution — building the foundation for what comes next in enterprise AI: decision-making that’s not just intelligent, but contextual, automated, and embedded at the point of need.

Discovery agent, multivariate time series forecasting, write table, and table recipe will be available for private preview for select customers this year. General availability will begin rolling out in phases starting in summer 2025.

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ORLANDO, FL: Qlik^®, a global leader in data integration, data quality, analytics, and artificial intelligence, today introduced its new agentic experience at Qlik Connect^® 2025. The agentic experience will provide a single, conversational interface allowing users across the enterprise to interact naturally with data, using specialized AI agents to quickly uncover insights, drive faster decisions, and boost productivity, bringing new simplicity to complex data-driven workflows.

Qlik has consistently pushed forward the possibilities of data exploration, visualization, and analytics. At the heart of this continuous innovation is the Qlik engine—a unique technology that indexes relationships across data, enabling the discovery of unexpected connections. The agentic experience builds directly on this engine, expanding the ability of both users and agents to intuitively access these relationships, surface insights, and take action across diverse data.

The agentic experience will enable users to access insights and take action simply by engaging in natural language dialogue. Operating seamlessly across Qlik Cloud—including data integration, data quality, and analytics solutions—the experience removes friction, providing fast, intuitive visibility for smarter decisions and higher productivity.

At Qlik Connect, the company demonstrated how specialized AI agents will support users within this new experience:

• Introduced last year for unstructured data, Qlik Answers will bring together structured and unstructured data in a single natural language experience, delivering trusted answers and enabling automated actions.
• Revealed for the first time at the event, a discovery agent will proactively identify critical risks and opportunities across applications and datasets, presenting insights and recommended actions through a personalized feed.
• Demonstrated as a concept, a pipeline agent will allow users to describe desired business outcomes conversationally, prompting automated recommendations and the design of necessary data pipelines.

As enterprises face unpredictable market conditions and increasing pressure to make critical decisions rapidly, investments in AI have grown. With its agentic experience, Qlik is focused on helping customers turn data into timely, high-quality decisions and results. Qlik’s agentic experience is specifically designed to empower teams to accelerate both decisions and productivity in rapidly changing environments.

“This new agentic experience is about removing the distance between data, decisions, and outcomes,” said Mike Capone, CEO of Qlik. “People want a seamless, conversational way to engage with their data—one that fits naturally into their work and delivers clear, trusted answers in context. We’ve built this experience to reflect how business decisions are made.”

“There’s a growing demand for AI that does more than generate responses—enterprises want systems that can reason across complex data, explain their outputs, and drive action,” said Megha Kumar, Research Vice President, Worldwide Analytics & AI, IDC. “Qlik Answers combines structured and unstructured data with automation in a governed, explainable framework. It’s a strong example of how agentic AI can support real enterprise decision-making.”

“We’re under constant pressure to make faster, better decisions with data that’s scattered across the business,” said Yuzuru Fukuda, Corporate Executive Officer – Senior EVP, Enterprise Division CEO, Fujitsu. “The ability to ask a question and get a trusted, contextual answer—across structured reports, unstructured content, and automated workflows—is exactly the kind of capability we’ve been waiting for. It has the potential to remove a lot of friction from how decisions get made.”

The Qlik agentic experience is scheduled to begin rolling out this summer, starting with private previews. Through live demos and executive briefings, teams attending Qlik Connect can experience the agentic capabilities firsthand.

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The case, Suluki v. Credit One Bank, NA, involves a consumer who disputed information on her credit report that she claimed resulted from multiple credit card accounts that her mother opened in her name without her permission or knowledge. The credit reporting agencies (CRAs) sent the dispute to the credit card companies for investigation. After Credit One refused to remove the information and purportedly verified the consumer as the accountholder, she sued the company under the FCRA.

The FCRA requires that, upon being notified of a dispute by a CRA, furnishers investigate whether the disputed information can be verified. If such an investigation is inconclusive, the FCRA requires the furnisher to delete from the data that the furnisher submits to CRAs the information that cannot be verified.

The consumer appealed after the district court granted Credit One’s request for summary judgment and held that she could not show harm from any failure by Credit One to conduct a reasonable investigation.

In their brief, the FTC and CFPB disputed the district court’s interpretation of the FCRA. They noted that under the FCRA, if a furnisher of credit information cannot determine whether the disputed consumer information is accurate, it must tell the CRAs that the information could not be verified and must delete it from the data that it reports to the CRAs.

The FTC and CFPB maintain that the lower court’s decision could impact consumers’ rights under the FCRA to dispute the completeness or accuracy of information and have it removed if a furnisher cannot verify that it is accurate.

Inaccurate information on a consumer report can hamper people’s ability to get housing, employment, and credit. The FTC and CFPB’s amicus brief aims to protect consumers’ rights under the FCRA and ensure that furnishers of credit information comply with the law.

The Commission voted 3-0 to join the CFPB amicus brief.

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