AI in Travel

The Smart Way to Stay: How CheQin.AI Is Making Hotels Compete for YOU – Can You Afford Not to Bargain?

Published

6 days ago

July 12, 2025

For as long as I’ve traveled, booking a hotel felt like a game of chance. Hours of searching, endless price comparisons and that lingering suspicion was this really the best deal?
Over time, I started to wonder: why does the process feel so one-sided? And more importantly, why does the industry still accept this status quo?

Uncovering the Real Cost of “Convenience”

Behind the scenes, the hotel booking ecosystem was designed around intermediaries. Every transaction included hidden commissions, sometimes as much as a quarter of the total cost, quietly redirected from guests and hotels alike. The system though efficient on the surface often left travelers with inflated prices and hoteliers with shrinking margins.

This wasn’t just a financial issue; it was a structural one. A cycle emerged hotels either absorbed the commission costs or quietly raised rates, while travelers were left to guess what they were really paying for. At some point I realized: convenience shouldn’t come at the expense of transparency or value.

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A New Model: From Price Takers to Price Setters

Change rarely begins at the center, it starts with frustration at the edges. As technology evolved, so did expectations. The old question—“how do I find the lowest price?”—gave way to a new one: “why can’t hotels compete for my stay?”

This is where CheQin.AI enabled Bargaining for Hotels enters the conversation. Instead of passively hunting for the best offer, travelers can now post their needs and watch as hotels compete for their business in real time. The result is both simple and profound: travelers move from price takers to price setters, shifting the balance of power.

Transparency, Trust and a Learning Curve

The first time I experienced this model, I was skeptical. Could eliminating the middleman really make booking that much clearer? As offers came in each transparent, each competitive it was obvious: direct competition strips away the guesswork.

Of course, transitions come with challenges. Not every hotelier adapts overnight and some travelers may hesitate to trust a process that looks so different from what they know. But over time, the benefits become self-evident: clarity replaces opacity, and every stakeholder understands the rules.

What Real Competition Unlocks—for Everyone

This shift doesn’t just benefit one side. When hotels engage directly with guests, they can focus on value and service rather than gaming an algorithm. Travelers, meanwhile, enjoy more honest pricing and a process built on real choice.

Perhaps the most overlooked outcome is how this dynamic inspires innovation. When every hotel must compete openly, differentiation happens on quality and experience not just on who pays more for a listing.

Looking Forward: The Case for Active Engagement

The hospitality industry is in a rare moment of self-reflection. Technologies that promote transparency and real-time competition are no longer outliers; they’re the first signs of an industry-wide reset. Passive browsing and opaque commissions are fading, replaced by models that reward initiative and openness.

There will be setbacks. Change of this scale is rarely smooth. But the direction is clear: as travelers and hoteliers both demand more from the process, the days of accepting hidden fees and unclear value are numbered.

Conclusion: Agency Is the New Advantage

The core insight is simple: agency knowing you can shape your own experience—is becoming the true currency in travel. The more empowered the traveler, the stronger the entire ecosystem becomes.

For industry leaders and travelers alike, the question isn’t whether to adapt, but how quickly. The future will belong to those who choose clarity, trust and active participation over passive acceptance.

Disclosure: The perspective shared in this article is informed by my personal experience in the travel and hospitality industry, including active involvement in digital innovation for guest booking experiences. I believe this change is good for both travelers and hotels.

AI in Travel

India’s Travel Revolution: How Map My Tour is Transforming Tourism with AI-Powered Personalization in New Delhi and Beyond – Travel And Tour World

Published

1 hour ago

July 18, 2025

the Editor

India’s Travel Revolution: How Map My Tour is Transforming Tourism with AI-Powered Personalization in New Delhi and Beyond Travel And Tour World

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AI in Travel

OpenAI Rolls Out ChatGPT Agent Combining Deep Research and Operator

Published

12 hours ago

July 17, 2025

Siddharth Jindal

OpenAI has launched the ChatGPT agent, a new feature that allows ChatGPT to act independently using its own virtual computer. The agent can navigate websites, run code, analyse data, and complete tasks such as planning meetings, building slideshows, and updating spreadsheets.

The feature is now rolling out to Pro, Plus, and Team users, with access for Enterprise and Education users expected in the coming weeks.

The agent integrates previously separate features like Operator and Deep Research, combining their capabilities into a single system. Operator allowed web interaction through clicks and inputs, while deep research focused on synthesis and summarisation.

The new system allows fluid transition between reasoning and action in a single conversation.

“You can use it to effortlessly plan and book travel itineraries, design and book entire dinner parties, or find specialists and schedule appointments,” OpenAI said in a statement. “ChatGPT requests permission before taking actions of consequence, and you can easily interrupt, take over the browser, or stop tasks at any point.”

Users can activate agent mode via the tools dropdown in ChatGPT’s composer window. The agent uses a suite of tools, including a visual browser, a text-based browser, terminal access, and API integration. It can also work with connectors like Gmail and GitHub, provided users log in via a secure takeover mode.

All tasks are carried out on a virtual machine that preserves state across tool switches. This allows ChatGPT to browse the web, download files, run commands, and review outputs, all within a single session. Users can interrupt or redirect tasks at any time without losing progress.

ChatGPT agent is currently limited to 400 messages per month for Pro users and 40 for Plus and Team users. Additional usage is available through credit-based options. Support for the European Economic Area and Switzerland is in progress.

The standalone Operator research preview will be phased out in the coming weeks. Users who prefer longer-form, slower responses can still access deep research mode via the dropdown menu.

While slideshow generation is available, OpenAI noted that formatting may be inconsistent, and export issues remain. Improvements to this capability are under development.

The system showed strong performance across benchmarks. On Humanity’s Last Exam, it scored a new state-of-the-art pass@1 rate of 41.6%, increasing to 44.4% when using parallel attempts. On DSBench, which tests data science workflows, it reached 89.9% on analysis tasks and 85.5% on modelling, significantly higher than human baselines.

In investment banking modelling tasks, the agent achieved a 71.3% mean accuracy, outperforming OpenAI’s o3 model and the earlier deep research tool. It also scored 68.9% on BrowseComp and 65.4% on WebArena, both benchmarks measuring real-world web navigation and task completion.

However, OpenAI acknowledged new risks with this capability. “This is the first time users can ask ChatGPT to take actions on the live web,” the company said. “We’ve placed a particular emphasis on safeguarding ChatGPT agent against adversarial manipulation through prompt injection.”

To counter these risks, ChatGPT requires explicit confirmation before high-impact actions like purchases, restricts actions such as bank transfers, and offers settings to delete browsing data and log out of sessions. Sensitive inputs entered during takeover sessions are not collected or stored.

The new system is classified under OpenAI’s “High Biological and Chemical” capability tier, triggering additional safeguards. The company has worked with external biosecurity experts and introduced monitoring tools, dual-use refusal training, and threat modelling to prevent misuse.

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AI in Travel

Lovable Becomes AI Unicorn with $200 Million Series A Led by Accel in Less than 8 Months

Published

12 hours ago

July 17, 2025

Siddharth Jindal

Stockholm-based AI startup Lovable has raised $200 million in a Series A funding round led by Accel, pushing its valuation to $1.8 billion. The announcement comes just eight months after the company’s launch.

Lovable allows users to build websites and apps using natural language prompts, similar to platforms like Cursor. The company claims over 2.3 million active users, with more than 180,000 of them now paying subscribers.

CEO Anton Osika said the company has reached $75 million in annual recurring revenue within seven months.

“Today, there are 47M developers worldwide. Lovable is going to produce 1B potential builders,” he said in a post on X.

The latest round saw participation from existing backers, including 20VC, byFounders, Creandum, Hummingbird, and Visionaries Club. In February, Creandum led a $15 million pre-Series A investment when Lovable had 30,000 paying customers and $17 million in ARR, having spent only $2 million.

The company currently operates with a team of 45 full-time employees. The Series A round also attracted a long list of angel investors, including Klarna CEO Sebastian Siemiatkowski, Remote CEO Job van der Voort, Slack co-founder Stewart Butterfield, and HubSpot co-founder Dharmesh Shah.

Most of Lovable’s users are non-technical individuals building prototypes that are later developed further with engineering support. According to a press release, more than 10 million projects have been created on the platform to date.

Osika said the company is not targeting existing developers but a new category of users entirely. “99% of the world’s best ideas are trapped in the heads of people who can’t code. They have problems. They know the solutions. They just can’t build them.”

Lovable is also being used by enterprises such as Klarna and HubSpot, and its leadership sees the platform evolving into a tool for building full-scale production applications.

“Every day, brilliant founders and operators with game-changing ideas hit the same wall: they don’t have a developer to realise their vision quickly and easily,” Osika said in a statement.

Osika also said on X that he has become an angel investor in a software startup built using Lovable.

In another recent example, Osika noted that a Brazilian edtech company built an app using Lovable that generated $3 million in 48 hours.

Lovable’s growth trajectory suggests increased adoption among both individual users and enterprise customers, positioning it as a significant player in the growing AI-powered software creation market.

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